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PMC9545238 | 35491752 | Shan Liu,Camille J. G. Lenoir,Tiago M. M. M. Amaro,Patricia A. Rodriguez,Edgar Huitema,Jorunn I. B. Bos | Virulence strategies of an insect herbivore and oomycete plant pathogen converge on host E3 SUMO ligase SIZ1 | 28-05-2022 | aphid,E3 SUMO ligase,effector,host susceptibility,oomycete,virulence strategy | Summary Pathogens and pests secrete proteins (effectors) to interfere with plant immunity through modification of host target functions and disruption of immune signalling networks. The extent of convergence between pathogen and herbivorous insect virulence strategies is largely unexplored. We found that effectors from the oomycete pathogen, Phytophthora capsici, and the major aphid pest, Myzus persicae target the host immune regulator SIZ1, an E3 SUMO ligase. We used transient expression assays in Nicotiana benthamiana as well as Arabidopsis mutants to further characterize biological role of effector–SIZ1 interactions in planta. We show that the oomycete and aphid effector, which both contribute to virulence, feature different activities towards SIZ1. While M. persicae effector Mp64 increases SIZ1 protein levels in transient assays, P. capsici effector CRN83_152 enhances SIZ1‐E3 SUMO ligase activity in vivo. SIZ1 contributes to host susceptibility to aphids and an oomycete pathogen. Knockout of SIZ1 in Arabidopsis decreased susceptibility to aphids, independent of SNC1, PAD4 and EDS1. Similarly SIZ1 knockdown in N. benthamiana led to reduced P. capsici infection. Our results suggest convergence of distinct pathogen and pest virulence strategies on an E3 SUMO ligase to enhance host susceptibility. | Virulence strategies of an insect herbivore and oomycete plant pathogen converge on host E3 SUMO ligase SIZ1
Pathogens and pests secrete proteins (effectors) to interfere with plant immunity through modification of host target functions and disruption of immune signalling networks. The extent of convergence between pathogen and herbivorous insect virulence strategies is largely unexplored. We found that effectors from the oomycete pathogen, Phytophthora capsici, and the major aphid pest, Myzus persicae target the host immune regulator SIZ1, an E3 SUMO ligase. We used transient expression assays in Nicotiana benthamiana as well as Arabidopsis mutants to further characterize biological role of effector–SIZ1 interactions in planta. We show that the oomycete and aphid effector, which both contribute to virulence, feature different activities towards SIZ1. While M. persicae effector Mp64 increases SIZ1 protein levels in transient assays, P. capsici effector CRN83_152 enhances SIZ1‐E3 SUMO ligase activity in vivo. SIZ1 contributes to host susceptibility to aphids and an oomycete pathogen. Knockout of SIZ1 in Arabidopsis decreased susceptibility to aphids, independent of SNC1, PAD4 and EDS1. Similarly SIZ1 knockdown in N. benthamiana led to reduced P. capsici infection. Our results suggest convergence of distinct pathogen and pest virulence strategies on an E3 SUMO ligase to enhance host susceptibility.
The plant immune system is complex, featuring different classes of receptors to detect pathogens and pests and initiate multi‐layered defence responses. Pattern recognition receptors (PRRs) recognize conserved pest and pathogen molecules, called pathogen‐associated molecular patterns (PAMPs), to activate immune responses and fight off the intruder (Jones & Dangl, 2006; Monaghan & Zipfel, 2012). Pathogens and pests deliver an arsenal of effector proteins inside their host to counter these and other plant defence pathways to promote effector‐triggered susceptibility (ETS) through modulation of host protein activities. In addition, these effectors likely contribute to effective infection or infestation strategies by promoting the release of nutrients to support pathogen or pest growth. Another layer of plant immunity may be activated upon recognition of these effectors, or their activities, by nucleotide‐binding leucine‐rich repeat (NLR) proteins, which usually is associated with the activation of a hypersensitive response (HR). Given that plants carefully balance energy allocation between growth, development and reproduction, any effective immune responses need to be appropriate and controlled (Huot et al., 2014). The identification of effector host targets and their effector‐induced modification(s) can reveal the mechanistic basis of virulence and the biological processes that lead to susceptibility. Moreover, the identification of effector host targets for a range of pathogens pointed to convergence on key host proteins. For example, Avr2 from the fungal pathogen Cladosporium fulvum, EPIC1 and EPIC2B from the oomycete Phytophthora infestans, and Gr‐VAP1 from the plant‐parasitic nematode Globodera rostochiensis target the same defence protease Rcr3pim in tomato (Song et al., 2009; Lozano‐Torres et al., 2012). In addition, the effector repertoires of distinct plant pathogens, such as the bacterium Pseudomonas syringae, oomycete Hyaloperonospora arabidopsidis, and the ascomycete Golovinomyces orontii disrupt key components of immune signalling networks (Mukhtar et al., 2011; Weßling et al., 2014). Specifically, transcription factor TCP14 is targeted by effectors from Pseudomonas syringae, H. arabidopsidis and Phytophthora capsici, and contributes to plant immunity (Weßling et al., 2014; Stam et al., 2021). These findings suggest that molecular virulence strategies have evolved independently in distinct pathogens and converged on a small set of regulators with central roles in immunity. While over the past decades our understanding of pathogen virulence strategies and susceptibility has increased dramatically, the extent with which host targets of plant–herbivorous insects overlap with other pathogens remains to be investigated. Effector biology has recently emerged as a new area in plant–herbivorous insect interactions research, leading to the identification of effector repertoires in several species (Carolan et al., 2009; Bos et al., 2010b; Kaloshian & Walling, 2016; Thorpe et al., 2018; Rao et al., 2019), several host targets, and insights into their contribution to the infestation process (Rodriguez et al., 2017; Chaudhary et al., 2019; Wang et al., 2019; Xu et al., 2019). These studies support an extension of the effector paradigm in plant–microbe interactions to plant–herbivorous insect interactions. Whether plant pathogenic microbes and insects adopt similar strategies to attack and reprogram their host to redirect immune responses is yet to be determined. Here, we show that Myzus persicae (aphid) effector, Mp64, and P. capsici (oomycete) effector CRN83_152 (also called PcCRN4) (Stam et al., 2013a; Mafurah et al., 2015), associate with the immune regulator SIZ1 in the plant nucleus. SIZ1 stability and cell death activation in Nicotiana benthamiana are differentially affected by these effectors, suggesting these proteins feature distinct activities via this immune regulator. SIZ1 is an E3 SUMO ligase involved in abiotic and biotic stress responses, including salicylic acid (SA)‐mediated innate immunity and EDS1/PAD4‐mediated resistance gene signalling (Miura et al., 2005, 2007, 2009; Catala et al., 2007; Lee et al., 2007; Jin et al., 2008; Ishida et al., 2012; Lin et al., 2016). Additionally, SIZ1 regulates plant immunity partially through the immune receptor SNC1 (Gou et al., 2017) and controls the trade‐off between SNC1‐dependent immunity and growth in Arabidopsis at elevated temperature (Hammoudi et al., 2018). By using Arabidopsis knockout lines and gene silencing in N. benthamiana we show that SIZ1 negatively regulates plant immunity to aphids and an oomycete pathogen, and is required for pathogen infection and pest infestation. Moreover, Arabidopsis siz1‐2 displayed reduced susceptibility to aphids and an oomycete pathogen. Critically, the observed immunity phenotype is independent of SNC1‐signalling suggesting that immunity is not specified by previously characterized SIZ1‐immune signalling pathways. Our results suggest that the effector target convergence principle can be extended to herbivorous insects and raise important questions about mechanisms of action.
Nicotiana benthamiana plants were grown in a glasshouse with 16 h of light, at 25°C during daytime. Transgenic Arabidopsis lines siz1‐2, eds1‐2 (backcrossed into Col‐0) (Bartsch et al., 2006), pad4‐1 (Glazebrook et al., 1997), snc1‐11 (Yang & Hua, 2004) and NahG (Delaney et al., 1994), siz1‐2/NahG (Lee et al., 2007), siz1‐2/eds1‐2 (Hammoudi et al., 2018), siz1‐2/pad4‐1 (Lee et al., 2007), and siz1‐2/snc1‐11 (Hammoudi et al., 2018) were kindly provided by Dr H.A. van den Burg, The University of Amsterdam, The Netherlands. Arabidopsis thaliana plants were grown in growth chambers with an 8 h : 16 h, light : dark cycle at 22°C : 20°C (day : night), with a light intensity of 100–200 µmol m−2 s−1 and relative humidity of 60%.
Myzus persicae (JHI_genotype O; Thorpe et al., 2018) was maintained on oil seed rape (Brassica napus) plants in a Perspex growth chamber, with 12 h light, at 17°C and 50% relative humidity. Phytophthora capsici isolate LT1534 (obtained from Kurt Lamour, University of Tennessee, Knoxville, TN, USA) was maintained on V8 agar cubes at room temperature. For zoospore collection, P. capsici LT1534 was grown on V8 agar plates at 25°C.
The coding sequence of Mp64, lacking the region encoding the N‐terminal signal peptide, was amplified from M. persicae (JHI_genotype O) complementary DNA (cDNA) by PCR with gene‐specific primers DONR‐Mp64_F and DONR‐Mp64_Rev (Supporting Information Table S1). The amplicon was cloned into entry vector pDONR207 (Invitrogen) using Gateway cloning technology. Cloning of the P. capsici effector CRN83_152 and the CRN83_152_6D10 mutant was previously described (Stam et al., 2013a; Amaro et al., 2018). For in planta expression, both effectors were cloned into destination vector pB7WGF2 (N‐terminal green fluorescent protein (GFP) tag) (Karimi et al., 2002). For yeast‐two‐hybrid (Y2H) assays, effectors were cloned into destination vector pLexA (Dual Systems Biotech, Grabenstrasse, Switzerland) via LR reactions using Gateway technology (Invitrogen). Vector specific primers pDONR207‐F, pDONR207‐R, p35s‐F, GFP‐Nter‐F, pLexA‐N‐F and pLexA‐N‐R used in plasmid construction are listed in Table S1. An entry clone carrying AtSIZ1 was kindly provided by Dr H.A. van den Burg, The University of Amsterdam. NbSIZ1 (Niben101Scf04549g09015.1; Solgenomics, https://solgenomics.net/) was amplified from N. benthamiana cDNA with gene‐specific primers NbSIZ1‐attB1 and NbSIZ1‐attB2 or NbSIZ1‐attB2‐nostop (Table S1). Amplicons were cloned into entry vector pDONR207 (Invitrogen) using Gateway technology. For in planta expression, AtSIZ1 and NbSIZ1 were cloned into destination vectors pB7FWG2 (C‐terminal GFP tag) (Karimi et al., 2002), pK7RWG2 (C‐terminal mRFP tag) (Karimi et al., 2005), and pGWB20 (C‐terminal 10xMyc tag) (Nakagawa et al., 2007). For Y2H assays, AtSIZ1 and AtSIZ1 mutants were cloned into destination vector pGAD‐HA (Dual Systems Biotech) via LR reactions using Gateway technology (Invitrogen). Vector specific primers pDONR207‐F, pDONR207‐R, p35s‐F, GFP‐Cter‐a‐R, RFP‐RevSeq, pGWB‐F, pGAD‐HA‐F2 and pGAD‐HA‐R2 used in plasmid construction are listed in Table S1. An entry clone carrying AtSUMO1 was kindly provided by Dr H.A. van den Burg, The University of Amsterdam (van den Burg et al., 2010). For in planta SUMOylation assays, AtSUMO1 was cloned into destination vector pK7WGR2 (N‐terminal mRFP tag) (Karimi et al., 2002) by LR reactions using Gateway technology (Invitrogen). Vector specific primer p35s‐F used in plasmid construction are listed in Table S1. All plasmids generated in this study are listed in Table S2.
Y2H screening of effectors against a N. benthamiana library was based on the Dualsystems Y2H system (Dual Systems Biotech) following manufacturer’s instructions. Bait vectors (pLex‐N) carrying effector sequences (lacking the signal peptide encoding sequence) were transformed into yeast strain NMY51. The prey library was generated in pGAD‐HA from cDNA obtained from a combination of healthy leaves, leaves infected with P. capsici, and leaves infested with aphids. Transformants were selected on media plates lacking leucine, tryptophan, and histidine (‐LWH) with addition of 2.5 mM 3‐amino‐1,2,4‐triazole (3‐AT). Yeast colonies were subjected to the β‐galactosidase reporter assays according to manufacturer’s instructions. The inserts of selected yeast colonies were sequenced and analysed. The Mp64/CRN83_152‐SIZ1 interaction was validated in yeast by independent co‐transformation experiments and reporter assays.
Arabidopsis Col‐0 were grown in the glasshouse under long‐day conditions (16 h of light) until flowering. The flowers were dipped three times (1‐wk interval) in an Agrobacterium GV3101 (carrying pB7WG2‐Mp64 or pB7WG2) suspension of optical density at 600 nm (OD600) = 0.8–2. T1 transformants were selected using 100 µg ml−1 BASTA (glufosinate‐ammonium) spray, and T2 seed were selected on Murashige–Skoog media containing 10 μg ml−1 BASTA. Homozygous T3 plants (predicted single insertion based on 3 : 1 segregation in T2) were used for aphid performance experiments. Primers Mp64‐int‐F/Mp64‐int‐Rev and Mp64‐qPCR‐F/Mp64‐qPCR‐R were used to confirm the presence of Mp64 in transgenic Arabidopsis by PCR and reverse transcription‐polymerase chain reaction (RT‐PCR), respectively (Table S1).
Agrobacterium GV3101 cultures carrying C‐terminal RFP‐tagged AtSIZ1, NbSIZ1 or GUS were infiltrated into N. benthamiana leaves with an OD600 of 0.3, together with silencing suppressor p19 (OD600 = 0.1). For co‐expression assays, mixtures of Agrobacterium cultures carrying N‐terminal GFP tagged Mp64, CRN83_152_6D10 or GUS with cultures carrying C‐terminal red fluorescent protein (RFP) tagged AtSIZ1, NbSIZ1 or GUS, respectively, were infiltrated into N. benthamiana leaves (OD600 = 0.3 for each construct; for p19, OD600 = 0.1). Cell death was scored 4–7 d post‐inoculation using a scale of 0–3 based on the severity of the phenotype. Infiltration sites were scored for no symptoms (score 0), chlorosis with localized cell death (score 1), < 50% of the site showing visible cell death (score 2), over 50% of the infiltration site showing cell death (score 3). Statistical analyses were conducted by using rstudio v.1.2.5001 running R‐3.6.1. Differences between treatments were analysed using the Kruskal–Wallis test with post hoc Dunn’s test for multiple comparisons.
Two 2‐d‐old M. persicae nymphs (age‐synchronized) were placed on 4–6‐wk‐old Arabidopsis plants. The plants were placed in a large plastic tube sealed with a mesh lid and placed in a growth cabinet (8 h of light, 22°C : 20°C for day : night, 60% humidity). Aphids were counted 10 d post‐infestation. Phytophthora capsici isolate LT1534 was grown in V8 agar plate for 3 d in the dark at 25°C and exposed to continuous light for 2 d to stimulate sporulation. Sporangia were collected in ice‐cold water and incubated under light for 30–45 min to promote zoospore release. For Arabidopsis infection, 4–6‐wk‐old plants were spray‐inoculated with 100 000 spores ml−1. The percentage of infected leaves was scored 8 d after inoculation. Statistical analyses were carried out using rstudio v.1.2.5001 running R‐3.6.1. A linear mixed effects model, with experimental block and biological replicate incorporated as random factors, was used for aphid fecundity assays. A linear mixed effects model, with biological replicates as a random factor, was used for P. capsici infection assays. ANOVA was used to analyse the final models, by using emmeans package calculating the least squares means as a post hoc test.
Phytophthora capsici infection assays were performed on N. benthamiana leaves expressing CRN83_152_6D10, Mp64 or the vector control upon agroinfiltration (OD600 = 0.3 each). Two days after infiltration, leaves were drop inoculated with 5 µl of zoospore solution (50 000 spores ml−1) from strain LT1534. Lesion diameters were measured at 2 d post‐inoculation.
Tobacco rattle virus (TRV)‐based virus‐induced gene silencing (VIGS) was used to silence NbSIZ1 in N. benthamiana. The VIGS construct was generated by cloning a 249‐bp fragment of NbSIZ1, amplified with primers Sumo_Vigs_Phusion_Frag3_F and Sumo_Vigs_Phusion_Frag3_R (Table S1). To generate a TRV control, a GFP fragment was amplified using the primers eGFP_Fw and eGFP_Rv (Table S1). Amplified fragments were cloned into the TRV vector (pTRV2) (Lu et al., 2003) using the In‐Fusion HD cloning kit (Clontech, Mountain View, CA, USA). Agrobacterium strains containing desired pTRV2 constructs were co‐infiltrated with strains carrying pTRV1 at OD600 = 0.5 into N. benthamiana plants. Three weeks post infiltration, leaves at the same position of different plants were detached for quantification of NbSIZ1 transcripts by quantitative reverse transcription‐polymerase chain reaction (qRT‐PCR) and P. capsici infection assays. Six independent plants were used for each VIGS construct in each replicated experiment, with a total of three replicated experiments. For infection assays, leaves were drop‐inoculated with 5 μl of zoospore suspension (50 000 spores ml−1) of P. capsici strain LT1534, or for data corresponding to Fig. S7 with 10 µl of zoospore suspension (100 000). Lesion diameter was recorded 2–3 d post‐inoculation. Data analyses was carried out by using rstudio v.1.2.5001 running R‐3.6.1. Group comparison was conducted by Mann–Whitney U test for nonnormally distributed data.
Agrobacterium strains carrying desired constructs were infiltrated individually or in combination in N. benthamiana plants with an OD600 of 0.1. Cells were imaged at c. 36 h post‐infiltration using Leica TCS SP2 AOBS (Leica Microsystems, Wetzlar, Germany) and Zeiss 710 confocal microscopes with HC PL FLUOTAR 63X0.9 and HCX APO L U‐V 40X0.8 water‐dipping lenses. GFP was excited with 488 nm from an argon laser, and emissions were detected between 500 and 530 nm. The excitation wavelength for mRFP was 561 nm and emissions were collected from 600 to 630 nm. Nicotinana benthamiana Histone (H2B) fused to mRFP was used as a nuclear marker (Goodin et al., 2007). Single optical section images or z‐stacks images were collected from leaf cells those have relatively low expression level to minimize the potential artefacts. Images were projected and processed using the imagej 1.52p‐fiji (Wayne Rasband, National Institute of Health, Bethesda, MD, USA).
Agrobacterium strain GV3101 expressing N‐terminal GFP‐tagged Mp64/CRN83_152/CRN83_152_6D10 and C‐terminal 10xMyc‐tagged AtSIZ1/NbSIZ1 were co‐infiltrated in N. benthamiana leaves (OD600 = 0.3, with p19 OD600 = 0.1). Leaf samples were harvested 48 h later. For detection of GFP and RFP fusion proteins used in localization experiments, Laemmli loading buffer (addition of 10 mM DTT) was directly added to ground leaf samples followed by sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS‐PAGE) and Western blotting. For co‐immunoprecipitation (co‐IP), equal amounts of plant material (12 leaf discs of 1.5 cm diameter) were extracted in 2 ml GTEN buffer (10% glycerol, 25 mM Tris–HCl, pH 7.5, 150 mM NaCl, 1 mM EDTA) supplemented with protease inhibitor (S8820; Sigma‐Aldrich), 2% PVPP, 0.1% NP‐40 detergent and fresh 10 mM DTT. Samples were incubated on ice for 10 min. The lysate was centrifuged at 14 460 g for three times, 4 min per each time and supernatants were subjected to co‐IP with GFP‐Trap®‐M magnetic beads (Chromotek, Am Klopferspitz, Germany). Western blotting was performed with a monoclonal GFP antibody (G1546; Sigma‐Aldrich) and a monoclonal cMyc antibody (both at 1 : 3000 dilution; SC‐40; Santa Cruz, Dallas, TX, USA) followed by anti‐mouse Ig‐HRP antibody (1 : 5000 dilution; A9044; Sigma‐Aldrich) and blots were incubated with SuperSignal Femto substrate (Thermo Scientific, Waltham, MA, USA) and exposed to X‐ray film for chemiluminescence detection.
To determine whether ectopic/overexpression of SIZ1 alone or in combination with effectors altered SUMOylation, we made use of a plant expression construct expressing RFP‐AtSUMO1 (van den Burg et al., 2010). Agrobacterium GV3101 strains carrying constructs to express AtSIZ1‐myc/NbSIZ1‐myc or myc‐GUS (control) with or without GFP‐Mp64/GPF‐CRN83_152_6D10 or GFP (control) were combined with strains expressing RFP‐AtSUMO1 for infiltration of N. benthamiana leaves. An OD600 of 0.3 was used for each construct, with the addition of an Agrobacterium strain expressing the silencing suppressor p19 (OD600 = 0.1). Forty‐eight hours post infiltration, the N. benthamiana plants were exposed to heat stress by placing them in a 37°C incubator for 1 h. For detection of SIZ1 protein levels in the absence/presence of effectors, side‐by‐side infiltrations were performed as mentioned earlier but without the presence of RFP‐AtSUMO1 and without heat stress. Protein was extracted from two leaf discs (1.5 cm diameter) in 200 µl GTEN buffer as described earlier. The protein lysate was mixed with 4× protein loading buffer (928‐40004; Li‐Cor, Lincoln, NE, USA) (with addition of 100 mM DTT) by a ratio of 3 : 1. For each sample, 5 µl was loaded into 4–20% Mini‐Protean® TGX Gels (4561096; Bio‐Rad), followed by SDS‐PAGE (20 mA per each gel, run for c. 1 h) after denaturation at 65°C for 5 min. The protein was subsequently transferred to polyvinylidene fluoride (PVDF) membranes for 90 min at 90 V using a wet transfer system. After transfer, the membranes were stained using Revert™ 700 Total Protein Stain (926‐11021; Li‐Cor) following the manufacturer’s manual for detection of total amounts of protein. The membranes were immediately imaged in the 700 nm channel using an Odyssey® CLx Imaging System (Li‐Cor). For subsequent detection of epitope tagged proteins, membranes were blocked with Intercept® (phosphate‐buffered saline (PBS)) Blocking Buffer (927‐70001; LI‐COR) for an hour at room temperature, following an hour of primary antibody incubation in Intercept® (PBS) Blocking Buffer with 0.2% Tween® 20 (P1379; Sigma‐Aldrich) at room temperature. After washing with PBS buffer (three times, 5 min per each), the membranes were incubated with IRDye secondary antibody in Intercept® (PBS) Blocking Buffer with addition of 0.02% SDS and 0.2% Tween® 20 (P1379; Sigma‐Aldrich) for an hour at room temperature. After three washes with PBS buffer, the target proteins were detected in the 800 nm channel with an Odyssey® CLx Imaging System. For detection of RFP‐SUMO1 and SUMO1 conjugates, a monoclonal RFP antibody raised in Rat (5F8; Chromotek), followed by IRDye® 800CW goat anti‐Rat IgG secondary antibody (926‐32219; Li‐Cor) was used at a dilution of 1 : 3000 and 1 : 10 000, respectively; For detection of GFP‐effectors and SIZ1‐myc, a monoclonal GFP antibody raised in mouse (G1546; Sigma‐Aldrich) and a monoclonal cMyc antibody raised in mouse (SC‐40; Santa Cruz) were used at a dilution of 1 : 3000, respectively, followed by IRDye® 800CW goat anti‐mouse IgG secondary antibody (926‐32210; Li‐Cor) at 1 : 10 000 dilution. Protein quantification was done by normalizing the band intensity of SIZ1 against the total protein amounts for the SIZ1 stability assays using empiria studio v.2.1. Quantification of SUMO conjugates was done by normalizing the signal intensity of the selected molecular weight (MW) area of the blot corresponding to SUMO conjugates against the total protein amounts. Relative ratios of signal intensity within experimental set‐ups we calculated based on comparisons to relevant control samples (e.g. GFP, myc‐GUS).
Total RNA was extracted by using RNeasy Mini Kit (Qiagen) and DNase I treated (Invitrogen). Briefly, 1 µg RNA was reverse‐transcribed using SuperScript III reverse transcriptase (Sigma‐Aldrich) following the manufacturer’s protocol. RT‐qPCR was designed following the MIQE guidelines (Bustin et al., 2009) with gene specific primers (Table S1). EF1α (accession no. TC19582 (At5g60390)) and PP2A (accession no. TC21939 (At1g13320)) (Liu et al., 2012) were used as reference genes in N. benthamiana and PEX4 (or UBC; accession no. AT5G25760) in Arabidopsis thaliana (Dekkers et al., 2012). Each 12.5 μl reaction contained 1× GoTaq® qPCR Master Mix, 1 μM of each primer, 1.4 mM magnesium chloride (MgCl2), 2.4 μM CXR reference dye and a cDNA quantity of c. 25 ng. The PCR program was set on a StepOne™ Real‐Time PCR Machine (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA) as follows: 95°C for 15 min followed by 40 cycles of 15 s at 95°C, 30 s at 60°C, and 30 s at 72°C. A melting curve was generated at the end of the PCR program and 2‐ΔΔCt value (Livak & Schmittgen, 2001) was calculated to determine the relative expression of NbSIZ1. Three technical replicates were performed in each run and three biological replicates were carried out.
To gain novel insight into pathogen and pest effectors function towards virulence, we successfully applied Y2H screens to identify candidate host targets (Rodriguez et al., 2017). We identified the E3 SUMO ligase SIZ1 in screens against a N. benthamiana library (generated from aphid infested and P. capsici infected leaves) with M. persicae (aphid) effector Mp64 and P. capsici (oomycete) effector CRN83_152 as baits. Mp64 was screened against an estimated 5 × 106 cDNAs and revealed two independent prey clones with an insert showing similarity to SIZ1, whilst the effector CRN83_152 screen of 4 × 106 yeast transformants, identified three independent prey clones with an insert similar to SIZ1. All putative interactors identified in the two effector screens are summarized in Table S3. Since all NbSIZ1 (N. benthamiana SIZ1) prey clones from the Mp64 and CRN83_152 screens were partial‐length, we designed primers to amplify and clone the full‐length NbSIZ1. Although we were unable to amplify NbSIZ1 based on the two best Blast hits against the N. benthamiana genome (Niben101Scf15836g01010.1 and Niben101Scf04549g09015.1) due to poor/no primer annealing at the 3′ end, we successfully amplified NbSIZ1 sequences based on the 3′ end of SIZ1 sequences from Nicotiana attenuata (XP_019237903) and Nicotiana tomentosiformis (XP_018631066). The full‐length NbSIZ1 sequence we cloned was identical to our partial yeast prey clones and NbSIZ1 database sequences, except for a 27 amino acid insertion at position 225–252. A direct comparison between NbSIZ1 and the well characterized AtSIZ1 showed 60% identity between proteins (Fig. S1). Given that AtSIZ1 is well characterized and helps regulate plant immunity (Miura et al., 2005; Catala et al., 2007; Lee et al., 2007; Hammoudi et al., 2018), we included AtSIZ1 in our efforts to further validate effector‐SIZ1 interactions and characterize the role of SIZ1 in plant–aphid/oomycete interactions using both Arabidopsis and N. benthamiana resources. It should be noted that whilst Arabidopsis is a host for M. persicae, this plant species is not a natural host for P. capsici. We first tested whether Mp64 and CRN83_152 interact with full‐length NbSIZ1 and AtSIZ1 in yeast. Whilst yeast reporter assays showed interaction of Mp64 with both full‐length SIZ1 versions (Fig. S2), we were unable to obtain yeast co‐transformants expressing both CRN83_152 and full‐length SIZ1 in repeated transformation experiments that included transformation controls. We also included a mutant of CRN83_152, called CRN83_152_6D10 (Amaro et al., 2018), which does not trigger CRN‐cell death activation but retains virulence activity, in co‐transformation experiments with similar results. Based on further data presented later, we hypothesize that the lack of CNR83_152/SIZ1 yeast co‐transformants is due to enhanced E3 SUMO ligase activity of SIZ1 in the presence of this effector which may affect yeast cell viability. To test for in planta effector–SIZ1 interactions, we co‐expresssed GFP‐Mp64 and GFP‐CRN83_152_6D10 with either AtSIZ1‐myc or NbSIZ1‐myc in N. benthamiana (Fig. 1a,b). Immunoprecipitation of both effectors resulted in the co‐purification of NbSIZ1, suggestive of an association in planta (Fig. 1b). Co‐IP of the effectors with AtSIZ1 gave similar results, however, with CRN83_152 and CRN83_152_6D10 only showing a weak band corresponding to AtSIZ1 upon co‐purification (Fig. 1a). Altogether our data demonstrate that effectors from two distinct plant parasites associate with the same host protein, SIZ1, in planta, prompting us to further investigate the contribution of SIZ1 and the effectors to susceptibility.
To assess the contribution of SIZ1 to immunity in a P. capsici host species, we made use of VIGS in N. benthamiana (Ratcliff et al., 2001; Lu et al., 2003). Our TRV‐NbSIZ1 construct, designed to silence NbSIZ1, reduced transcripts levels by around 60% compared with plants expressing the TRV‐GFPfrag control (a fragment of GFP) (Fig. S3). Silenced plants showed a slight reduction in growth compared with the TRV‐GFPfrag control and cell death in older leaves (Fig. S3). In our hands, VIGS assays based on TRV in N. benthamiana are incompatible with aphid assays (TRV infection causes aphids to die), therefore, we only performed infection assays with P. capsici on NbSIZ1 silenced plants. Detached leaves were used for P. capsici infection assays based on zoospore droplet inoculations, followed by lesion size diameter measurements. P. capsici lesion size on NbSIZ1 silenced leaves was significantly reduced 2–4 d after inoculation when compared to control plants (Mann–Whitney U test, P < 0.001; Figs 2, S3). These results indicate that NbSIZ1 contributes to host susceptibility to this oomycete plant pathogen.
Since AtSIZ1 negatively regulates plant innate immunity in Arabidopsis to the bacterial plant pathogen Pseudomonas syringae pv Tomato DC3000 (Pst) (Lee et al., 2007), we tested whether this also applies to interactions with M. persicae and P. capsici. We performed aphid performance assays, based on fecundity measurements, as well as P. capsici infection assays on the Arabidopsis loss‐of‐function mutant siz1‐2. Given that siz1‐2 mutants have a dwarf phenotype, associated with SA hyper‐accumulation, we included Arabidopsis line siz1‐2/NahG, in which this phenotype is (partially) abolished (Lee et al., 2007). While Arabidopsis is a host for the aphid M. persicae, only few P. capsici isolates infect Arabidopsis under controlled environmental conditions and high levels of inoculum (Wang et al., 2013), suggesting that Arabidopsis is not a natural host. Aphid performance assays showed a significant reduction in fecundity on the siz1‐2 and siz1‐2/NahG lines compared to the Col‐0 (ANOVA, P < 0.0001; Fig. 3a) and NahG controls (ANOVA, P < 0.01; Fig. 3a), respectively, with only few aphids surviving on the siz1‐2 line. The siz1‐2 reduced susceptibility to aphids is largely maintained in the NahG background, implying that this phenotype is largely independent of SA accumulation. For P. capsici infection assays, plants were spray inoculated with a zoospore solution and the percentage of symptomatic leaves was counted 10 d later. The percentage of symptomatic siz1‐2 leaves was reduced by 83% compared with the Col‐0 control (ANOVA, P < 0.0001; Figs 3b, S4). We did not observe a difference in P. capsici infection levels between the NahG line and Col‐0 but did note a slight increase in infection on siz1/NahG compared to the NahG background (ANOVA, P < 0.01; Figs 3b, S4).
EDS1, PAD4 and SNC1 are required for siz1‐2 enhanced resistance to P. syringae pv tomato DC3000 (Lee et al., 2007; Gou et al., 2017; Hammoudi et al., 2018). To explore whether these signalling components also contribute to reduced aphid infestation and P. capsici infection on siz1‐2, we performed aphid infestation and infection assays on Arabidopsis siz1‐2/eds1‐2, siz1‐2/pad4‐1 and siz1‐2/snc1‐11 double mutants. Aphid infestation on the siz1‐2/eds1‐2 mutant was reduced by 75% compared with the eds1‐2 mutant (ANOVA, P < 0.0001, Fig. 3c), and was comparable to siz1‐2 (Fig. 3c), suggesting that the reduced susceptibility of siz1‐2 to aphids is independent of EDS1. In addition, aphid fecundity was reduced on siz1‐2/pad4‐1 by around 65% compared with the pad4‐1 mutant (ANOVA, P < 0.0001; Fig. 3c), and was comparable to siz1‐2. These data suggest that siz1‐2 reduced susceptibility to aphids is also independent of PAD4. In line with previous reports (Wang et al., 2013) the eds1‐2 and pad4‐1 mutants were less resistant to P. capsici than Col‐0 (ANOVA, P < 0.0001; Figs 3d, S4), indicating EDS1 and PAD4 contribute to Arabidopsis nonhost resistance to this pathogen. The percentage of symptomatic siz1‐2/eds1‐2 and siz1‐2/pad4‐1 leaves was around 60% and 55% less compared to the eds1‐2 (ANOVA, P < 0.0001; Figs 3d, S4) and pad4‐1 (ANOVA, P < 0.0001; Figs 3d, S4) mutants, respectively. Similar to our aphid data, Arabidopsis siz1‐2 enhanced resistance to P. capsici was maintained in the eds1‐2 and pad4‐1 mutant backgrounds when compared to the appropriate controls (eds1‐2 and pad4‐1, respectively). Aphid fecundity on siz1‐2/snc1‐11 was approximately 85% reduced compared with the snc1‐11 control (ANOVA, P < 0.0001), and was comparable to siz1‐2 (Fig. 3e), suggesting that siz1‐2 reduced susceptibility to aphids is independent of SNC1. The siz1‐2/snc1‐11 double mutant also showed enhanced resistance to P. capsici, with 55% less symptomatic leaves compared to the snc1‐11 mutant (ANOVA, P < 0.0001; Figs 3b, S4). The percentage of symptomatic leaves on siz1‐2/snc1‐11 was slightly higher compared with the siz1‐2 mutant (ANOVA, P < 0.05; Figs 3b, S4). With the siz1‐2 enhanced resistance to P. capsici largely maintained in the snc1‐11 background, this phenotype is likely independent of the immune receptor SNC1. Overall, siz1‐2 reduced susceptibility to both M. persicae and P. capsici is independent of defence signalling components previously implicated in SIZ1 immune functions. These data are in line with a model wherein SIZ1 contributes to host susceptibility to certain pests and pathogens, perhaps upon effector‐mediated modulation.
While the nuclear PcCRN83_152 effector from P. capsici was previously shown to be essential for pathogen virulence and promotes plant susceptibility (Stam et al., 2013a; Mafurah et al., 2015), the role of aphid effector Mp64, which was identified as a candidate effector in Acyrthosiphon pisum and M. persicae through bioinformatics pipelines (Carolan et al., 2011; Thorpe et al., 2016; Boulain et al., 2018), is unknown. Mp64 is a protein of unknown function with a predicted nuclear localization based on ProteinPredict (Yachdav et al., 2014) and NLStradamus (Nguyen Ba et al., 2009), and Mp64 homologues are present in other aphid species (Fig. S5). We investigated the subcellular localization of Mp64 by confocal microscopy of N. benthamiana leaves transiently expressing GFP‐Mp64 (lacking the predicted signal peptide). Imaging of epidermal cells expressing Mp64 revealed accumulation of GFP‐Mp64 in the nucleus and nucleolus, with no signal detectable in the cytoplasm (Fig. 4a). Nuclear localization of GFP‐Mp64 was confirmed upon co‐localization with the nuclear marker Histone 2B (H2B) (Fig. 4b). In addition, we observed dots within the nucleoplasm corresponding to GFP‐Mp64. To confirm that Mp64 contributes to aphid virulence, we generated Arabidopsis transgenic lines expressing the mature Mp64 protein driven by the 35S promoter. Arabidopsis lines expressing Mp64 showed no developmental or growth phenotypes (Fig. S6) and were subjected to aphid fecundity assays. Two age‐synchronized M. persicae aphids were placed on transgenic Mp64 lines and Col‐0 control plants, and progeny was counted after 10 d. The average number of aphids on two independent transgenic Mp64 lines (25.6 and 29.5) was around 30% higher than on the Col‐0 control (Kruskal–Wallis test with multiple comparisons Benjamini–Hochberg correction based on false discovery rate (FDR); Fig. 4c), indicating that Mp64 enhances Arabidopsis host susceptibility to M. persicae. While our two Mp64 transgenic lines showed different levels of Mp64 expression, with line 29.5 showing lower expression than line 25.6. We did not find a correlation between higher expression and virulence effect, with both lines showing a similar increase in aphid numbers. To test whether Mp64 also affects P. capsici infection, we transiently overexpressed Mp64 and a vector control in N. benthamiana and challenged infiltration sites with a zoospore suspension. While P. capsici effector CRN83_152 enhanced N. benthamiana susceptibility to P. capsici, in line with previous reports (Stam et al., 2013b; Mafurah et al., 2015; Amaro et al., 2018) aphid effector Mp64 did not affect host susceptibility to P. capsici (Fig. S7), pointing to distinct virulence activities of these effectors.
Since both Mp64 and CRN83_152 are nuclear effectors, and their host interacting protein SIZ1 is reported to localize and function in the plant nucleus (Miura et al., 2005), we determined whether the effectors co‐localize with SIZ1 in this subcellular compartment. We performed confocal imaging of N. benthamiana leaves transiently co‐expressing SIZ1‐mRFP and GFP‐effector fusions. We did not detect signal corresponding to the effectors or SIZ1 outside the nucleus (Figs 4, 5, S8). In line with previous reports, mRFP signal corresponding to both AtSIZ1 and NbSIZ1 was visible in the plant nucleoplasm, along with distinct speckles in the nucleolus (Fig. 5, S8). Expression of full‐length SIZ1‐RFP was confirmed by Western blotting (Fig. S9). GFP signal corresponding to GFP‐Mp64 and CRN83_152 was detectable in the nucleus, with GFP‐Mp64 more localized within the nucleolus and in speckles within the nucleoplasm, and GFP‐CRN83_152 present only in the nucleoplasm (Figs 4, 5, S8). Indeed, GFP‐CRN83_152 co‐localizes with AtSIZ1‐RFP and NbSIZ1‐RFP in the nucleoplasm, whereas GPF‐Mp64 shows a more distinct localization in the nucleus that only partially overlaps with nucleoplasm localization of SIZ1. Interestingly, nucleolar speckles corresponding to SIZ1‐RFP occasionally coincided with loss of GFP‐Mp64 signal, and GFP‐Mp64 speckles within the nucleoplasm coincided with loss of SIZ1‐RFP signal. However, we did not find evidence for altered localization of SIZ1 in the presence of the effectors, and vice versa (Figs 5, S8). With the effectors and SIZ1 only detected within the nucleus, this likely is the compartment where interactions take place.
In co‐IP experiments, we consistently observed increased protein levels of AtSIZ1 in input samples upon co‐expression with Mp64 but not CRN83_152_6D10 (Fig. 1a,b). To test whether Mp64 indeed stabilizes SIZ1 in planta, we performed co‐expression assays of both effectors with SIZ1 in parallel in three independent experiments. Western blot analyses combined with quantitative analyses of band intensities, showed that AtSIZ1 levels were higher than NbSIZ1 levels among all replicates. In addition, we consistently observed an increase in SIZ1 protein levels in the presence of Mp64 compared to the GFP‐GUS control (Fig. 6a, additional replicates in Fig. S10), indicating that Mp64 stabilizes SIZ1 in planta. Although not consistent across replicates, we did observe slightly decreased AtSIZ1 levels in the presence of CRN83_152_6D10, compared to the GFP control, but this observation was not consistent across replicated experiments (Fig. 6a, additional replicates in Fig. S10). Overall, we noted that full length AtSIZ1 and NbSIZ1 are rather difficult to detect by Western blotting, suggesting low expression and/or low protein stability. Indeed, Lin et al. (2016) previously showed that the 26S proteasome inhibitor MG132 reduces degradation of GFP‐AtSIZ1 mediated by the ubiquitin E3 ligase COP1 (CONSTITUTIVE PHOTOMORPHOGENIC 1), an ubiquitin E3 ligase. In line with this we show that both AtSIZ1 and NbSIZ1 are more readily detected by Western blotting upon MG132 treatment (Fig. 6b), suggesting that the levels of both these SIZ1 versions is tightly regulated in planta.
When performing transient expression assays in N. benthamiana with AtSIZ1 and NbSIZ1, we observed the onset of cell death starting from 3 d after infiltration specifically upon expression of AtSIZ1. We investigated whether co‐expression of the aphid and oomycete effectors with SIZ1 would either enhance or reduce this cell death activation. In the absence of any effectors, AtSIZ1 consistently activated cell death from 3 to 4 d after infiltration, whereas only occasional microscopic cell death was visible in infiltration sites expressing NbSIZ1. Both AtSIZ1 and NbSIZ1 fusion proteins, with a C‐terminal RFP tag, were detectable in transient expression assays (Fig. S9). While co‐expression of Mp64 with SIZ1 did not affect the cell death phenotype, co‐expression of CRN83_152_6D10 with AtSIZ1 led to a stronger cell death response compared to the AtSIZ1 and CRN83_152_6D10 controls (Figs 7, S11). These data suggest that CRN83_152_6D10 but not Mp64 enhances AtSIZ1‐triggered cell death.
To assess whether both AtSIZ1 and NbSIZ1 are active upon transient expression in N. benthamiana and whether effectors CRN83_152 and Mp64 alter any E3 SUMO ligase activity, we performed co‐expression assays with RFP‐tagged AtSUMO1. First, we co‐infiltrated Agrobacterium strains carrying constructs for AtSIZ1‐myc, NbSIZ1‐myc and myc‐GUS (control) with RFP‐SUMO1, to assess whether ectopic/overexpression of SIZ1 increased detectable SUMO profiles upon heat treatment. Western blot analyses showed an increase in the presence of SUMO profiles, as detected with RFP‐antibodies against RFP‐SUMO1, upon expression of SIZ1 compared to the GUS control, with the strongest and most consistent increase upon expression with AtSIZ1 (Figs 8a, S12). We then performed similar co‐expression assays and Western blot analyses in the presence and absence of effectors Mp64 and CRN83_152_6D10. As described earlier, we observed increased levels of SIZ1 in the presence of Mp64, as well as a slight decrease in the presence of CRN83_152_6D10 (Fig. 8b). Furthermore, in the presence of both SIZ1 and CRN83_152_6D10 we noted an increase in SUMO profile levels compared to the no effector (GFP) control (Figs 8b, S12). We detected no increase in SUMO profile levels in the presence of CRN83_152_6D10 in combination with the GUS (control) indicating that that the observed increase in SUMOylation mediated by this effector is dependent on SIZ1 ectopic/overexpression. Our data suggest that the P. capsici effector CRN83_152_6D10 enhances SIZ1 activity, most likely to enhance host susceptibility.
Pathogen infection strategies involve extensive modification of host cell biology, which rely on the modulation of hubs that control plant immunity. We show that effectors from an herbivorous insect and oomycete plant pathogen target the host E3 SUMO ligase SIZ1. Our findings suggest that the virulence strategies of two plant parasites, with distinct evolutionary histories and lifestyles, convergence on an important host immune component. We show that SIZ1 is a key target of distinct plant parasites, which is in line with a recent study on the cyst nematode Globodera pallida, which shows that effector GpRbp1 associates with potato SIZ1 in planta (Diaz‐Granados et al., 2019). StSIZ1 emerged as a negative regulator of immunity in plant–nematode interactions (Diaz‐Granados et al., 2019), but the signalling requirements for this immunity have not yet been reported. We propose that SIZ1 is an important regulator of susceptibility to a broad range of plant parasites, including herbivorous insects. Indeed, Arabidopsis siz1‐2 plants show reduced susceptibility not only upon pathogen infection as reported here (Fig. 3) and previously (Lee et al., 2007) but also upon aphid infestation. In contrast to siz1‐2 enhanced resistance to Pseudomonas syringae pv tomato DC3000, which is dependent on SA, EDS1, PAD4 and SNC1, we find that resistance to the aphid M. persicae and the oomycete P. capsici is largely independent from these signalling components. These results point to (1) the involvement of a yet to be identified SIZ1‐dependent signalling pathway that regulates plant immunity, and/or (2) a yet to be characterized role of SIZ1 in promoting pathogen and pest susceptibility. Although PAD4 has been reported to play an important role in plant defence against M. persicae (Pegadaraju et al., 2007), in line with Lei et al. (2014), we did not observe an enhanced susceptibility phenotype of Arabidopsis pad4‐1 in our aphid performance assays. This may be due to differences in experimental design and conditions. A reduction of SA levels in the NahG line did not enhance defence against the aphid M. persicae (this study and previous reports Pegadaraju et al., 2007; Lei et al., 2014), nor did this reduce nonhost resistance to the oomycete P. capsici, in contrast to an earlier report by Wang et al. (2013). However, we did observe a trend towards reduced resistance of the transgenic NahG line to P. capsici, but this reduction was not statistically significant and may be less pronounced due to differences in experimental set‐up and infection conditions compared to Wang et al. (2013). Arabidopsis defence to insect herbivores is mediated predominantly through jasmonic acid (JA)‐signalling, whereas defence against (hemi‐)biotrophic pathogens tend to rely on SA‐signalling (Howe & Jander, 2008; Pieterse et al., 2012). In the Arabidopsis–M. persicae interaction, siz1‐2 reduced susceptibility is largely independent of SA accumulation, with the siz1‐2/NahG line being more resistant to aphids than the NahG control and Col‐0 (Fig. 3). Therefore, and in contrast to Lee et al. (2007), SIZ1‐regulated immunity to aphids is independent of SA‐signalling. Interestingly, the Arabidopsis siz1‐2 mutant features changes in cell division, cell expansion and secondary cell wall formation, including reduced secondary cell wall thickening (Miura et al., 2010; Liu et al., 2019). Aphid feeding can trigger changes in cell wall composition that are associated with defences (Rasool et al., 2017), and therefore changes in cell wall formation can be responsible for altered susceptibility. However, reduced cell wall thickening most likely would lead to a reduction in defence against aphids rather than an increase as observed in the siz1‐2 mutant. With SIZ1 comprised of several conserved domain involved in different stress responses (Cheong et al., 2009), it is possible that Mp64 and CRN83_152 target different protein regions and functions. Arabidopsis and N. benthamiana SIZ1 domains include the SAP (scaffold attachment factor A/B/acinus/PIAS) domain, PINIT (proline‐isoleucine‐asparagine‐isoleucine‐threonine) domain, an SP‐RING (SIZ/PIAS‐RING) domain, SXS motif (serine‐X‐serine), and a PHD (plant homeodomain). Functional analyses, using a set of (deletion) mutants revealed that these domains contribute differently to the wide range of SIZ1 functions in both abiotic and biotic stress (Cheong et al., 2009). The SP‐RING domain of AtSIZ1 contributes to the nuclear localization, SUMOylation activity, as well as the regulation of SA levels and associated plant defence responses. This domain is the suggested SIZ1 target site of the nematode effector GpRbp1 to interfere with SA‐mediated defences (Diaz‐Granados et al., 2019). Our Arabidopsis–M. persicae interaction assays though suggest that SIZ1 may also regulate immunity/susceptibility in a SA‐independent manner where other domains may play an important role. Interestingly, SIZ1‐mediated SUMOylation is involved in regulating sugar signalling independent of SA (Castro et al., 2015, 2018), with the siz1‐2 mutant showing reduced starch levels and increased expression of starch and sucrose catabolic genes. Aphid infestation affects sugar metabolism as reflected for example by an increase in sucrose and starch in infested Arabidopsis plants (Singh et al., 2011). With sugars in phloem sap also being the main aphid food source, it will be interesting to further explore a possible link between the role of SIZ1 in regulating sugar signalling and host susceptibility. Our data support a key role for SIZ1 in host susceptibility to P. capsici and M. persicae that is targeted during infection and infestation, and point to potential different mechanisms by which effectors CRN83_152 and Mp64 modulate SIZ1 function. The presence of host SIZ1 is required for infestation/infection as knockout of AtSIZ1 and knockdown of NbSIZ1 result in reduced host susceptibility phenotypes. Therefore, we propose that Mp64 and CRN83_152 redirect and perhaps enhance SIZ1 function rather than inhibit its signalling activity. Indeed, we show that CRN83_152_6D10 increased SIZ1‐mediated SUMOylation in planta, indicating that this effector modulates E3 SUMO ligase activity (Fig. 8). However, Mp64 but not CRN83_152_6D10 enhanced stability of SIZ1 (Fig. 6). In line with these results, we found that Arabidopsis transgenic lines expressing Mp64 do not show a reduced growth phenotype similar to the siz1‐2 mutant (Fig. S4 and S6). However, expression of CRN83_152 but not Mp64 in N. benthamiana led to an increase in P. capsici infection. Based on these observations, we propose that while both virulence strategies have converged onto SIZ1, their mechanisms of action are distinct. In this context, we cannot rule out that additional candidate targets of Mp64 and CRN83_152 identified in our Y2H screens (Table S1) explain our observed differences in effector virulence activities. As an E3 SUMO ligase, SIZ1 is required for SUMOylation of a range of substrates including chromatin modifiers, co‐activators, repressors, and transcription factors that are associated with biotic and abiotic stress responses (Rytz et al., 2018). Similar to ubiquitination, SUMOylation involves three key steps (Verma et al., 2018). First, the SUMO precursor is cleaved and the SUMO moiety is linked to a SUMO‐activating enzyme (E1). Activated SUMO is then transferred to the SUMO‐conjugating enzyme (E2), after which it is linked to target substrates with the help of SUMO‐ligases (E3). In the SUMO cycle, SUMO proteases are responsible for processing of the SUMO precursor and release of SUMO from target substrates. Given that CRN83_152 enhances SIZ1 E3 SUMO ligase activity, we hypothesize that the cell death triggered by AtSIZ1 upon transient expression in N. benthamiana is linked to its enzyme activity. Perhaps AtSIZ1 expression in a different plant species than Arabidopsis leads to mis‐targeting of substrates, and subsequent activation of cell death. Although Mp64 did not enhance the cell death triggered by AtSIZ1, this effector did increase SIZ1 protein stability. Similarly, the effector AVR3a from Phytophthora infestans interacts with and stabilizes the E3 ubiquitin ligase CMPG1, likely by modifying its activity, to suppress plant immunity (Bos et al., 2010a). The mechanism underlying the stabilization of SIZ1 by Mp64 is yet unclear. However, we hypothesize that increased stability of SIZ1, which functions as an E3 SUMO ligase, leads to increased SUMOylation activity towards its substrates and will likely affect SIZ1 complex formation with other key regulators of plant immunity. SUMOylation indeed regulates key immune signalling components, as recently shown for NPR1 (nonexpressor of pathogenesis‐related (PR) genes 1) (Saleh et al., 2015). Whether NPR1 is a substrate of SIZ1 remains to be investigated. SUMOylation of target proteins plays an important role in plant immunity and is known to be targeted as part of bacterial plant pathogen infection strategies (Verma et al., 2018). For example, effector XopD from Xanthomonas campestris pv vesicatoria (Xcv) functions as a SUMO protease inside host cells to modulate host defence signalling (Hotson et al., 2003; Kim et al., 2008). SUMOylation sites are predicted in Mp64 (Fig. S5) and CRN83_152 (1 SUMO interaction motif: SVEKGANILSVEVPGCDVD; SUMOylation site: VKMLIEVKREVKSAS) using prediction software GPS‐SUMO (Zhao et al., 2014). However, using similar assays with RFP‐SUMO1 described in this study, we have not detected any SUMOylation forms of Mp64 and CRN83_152, suggesting that these effectors are not SUMOylation targets themselves. Overall, our data suggest that modification of host SUMOylation is a common strategy of plant parasites to enable host colonization, and that the targeting strategies have evolved independently in distinct plant‐feeding organisms including herbivorous insects. A detailed analyses of changes in the SIZ1‐dependent host plant SUMOylome and their impact on susceptibility and immunity is needed to understand how distinct plant parasites promote virulence through SIZ1 targeting.
JIBB and EH conceived the study, SL, CJGL, TMMMA, PAR, JIBB and EH designed the research, SL, CJGL, TMMMA, PAR, and JIBB performed the experiments, SL, CJGL, TMMMA, PAR, JIBB and EH analyzsed the data, SL, JIBBB and EH wrote the manuscript with input from all authors. CJGL and TMMMA contributed equally to this work.
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PMC9546575 | 36161949 | Menglan He,Alvin C. Y. Kuk,Mei Ding,Cheen Fei Chin,Dwight L.A. Galam,Jie Min Nah,Bryan C. Tan,Hui Li Yeo,Geok Lin Chua,Peter I. Benke,Markus R. Wenk,Lena Ho,Federico Torta,David L. Silver | Spns1 is a lysophospholipid transporter mediating lysosomal phospholipid salvage | 26-09-2022 | phospholipid,transporter,Mfsd2a,autophagy,lysosome | Significance Lysosomes mediate the hydrolysis of macromolecules for which the breakdown products must be transported out, failure of which could result in lysosomal storage diseases. While lysosomal transporters for amino acids, monosaccharides, and ions have been characterized, less is known about the identity of lipid transporters, particularly whether lysosomes export lysophospholipids that are breakdown products of phosphatidylcholine and phosphatidylethanolamine, the most abundant membrane phospholipids. This study combined a cell-based screen with biochemical, cell, and in vivo models to identify SPNS1, a previously orphaned transporter, as the transporter that mediates the rate-limiting lysosomal efflux of lysophospholipids for their recycling into cellular phospholipid pools. The deorphanization of SPNS1 sets a foundation for studying the role of lysolipid transport and recycling in physiology and disease. | Spns1 is a lysophospholipid transporter mediating lysosomal phospholipid salvage
Lysosomes mediate the hydrolysis of macromolecules for which the breakdown products must be transported out, failure of which could result in lysosomal storage diseases. While lysosomal transporters for amino acids, monosaccharides, and ions have been characterized, less is known about the identity of lipid transporters, particularly whether lysosomes export lysophospholipids that are breakdown products of phosphatidylcholine and phosphatidylethanolamine, the most abundant membrane phospholipids. This study combined a cell-based screen with biochemical, cell, and in vivo models to identify SPNS1, a previously orphaned transporter, as the transporter that mediates the rate-limiting lysosomal efflux of lysophospholipids for their recycling into cellular phospholipid pools. The deorphanization of SPNS1 sets a foundation for studying the role of lysolipid transport and recycling in physiology and disease.
The lysosome is an acidic degradative organelle that receives macromolecular cargo such as proteins, polysaccharides, and lipids from endocytosis, phagocytosis, and autophagy. The catabolic products of these macromolecules re-enter the cytoplasm to be used in biosynthesis reactions in the cell. The myriad forms of lysosomal storage diseases highlight the crucial role that catabolism and export of lysosomal macromolecules play in cell and organ functions (1). While lysosomal transporters for amino acids, monosaccharides, and ions have been characterized, less is known about the identity of lipid transporters (2–4), with the exception of Niemann-Pick C1 protein and Niemann-Pick C2 protein that critically mediate cholesterol transport out of lysosomes (5, 6). While not as well studied as for cholesterol, a similar lysosomal salvage pathway is known for sphingolipids (7) that is important for the metabolism of sphingolipid-like drugs such as FTY720 (8). Remarkably, there is a lack of information on the fate of glycerophospholipids within lysosomes, the main components of cellular membranes. In 1969, Fowler et al (9) were the first to describe that the end products of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) catabolism in lysosomes are lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), and fatty acid, consistent with the existence of lysosomal phospholipase A1 and A2 activities, with PLA2G15 being the only biochemically characterized mammalian lysosomal phospholipase A2 (PLA2) to date (10–12). We reasoned that because LPC and LPE molecules are zwitterionic and do not readily diffuse across membranes, they require a transporter to egress out of lysosomes to be reacylated by membrane bound O-acyltransferases (MBOATs) and LPC acyltransferases (LPCATs) located in the endoplasmic reticulum (ER) to form PC and PE (13) (Fig. 1A). Mfsd2a, a sodium-dependent LPC transporter and a member of the major facilitator superfamily (MFS), establishes the precedence for the requirement of a transporter for LPC and LPE across the plasma membrane of many cell types (14, 15). The other known lysolipid transporters that are part of the MFS family are Mfsd2b and Spns2, which both transport sphingosine-1-phosphate (S1P) at the plasma membrane (16, 17). These findings raise the possibility that an MFS transporter exists to mediate lysosomal efflux of LPC and LPE for phospholipid salvage.
We therefore screened a panel of ubiquitously expressed orphan MFS proteins that are known to be localized to the lysosome and that have amphipathic binding pockets suitable for lysolipid transport (15, 18–21). Since many lysosomal transmembrane proteins traffic through the plasma membrane (PM) before entering the endocytic pathway (22), an exporter protein at the lysosome membrane can function as an importer at the PM if it is exposed to substrate and a proton gradient (Fig. 1B). We took advantage of this cellular phenomenon to devise a cell surface uptake assay to screen for LPC transporters. We overexpressed orphan candidate transporters in HeLa cells and verified that they accumulated at the PM by using cell surface biotin cross-linking (SI Appendix, Fig. S1A). Placing cells in buffer at pH 5 to mimic the acidic luminal environment of lysosomes and measuring the uptake of [14C]-LPC-oleate into cells, we found that Spns1 was the only MFS in the panel that showed a significant increase in [14C]-LPC-oleate uptake relative to control (Fig. 1C). Spns1 did not mediate the uptake of [3H]-sphingosine, a lysolipid-like molecule structurally different from LPC (SI Appendix, Fig. S1B). Alanine mutagenesis of phylogenetically conserved residues arginine 76 (R76), glutamate 164 (E164), and histidine 427 (H427), which are predicted to form salt bridges with the choline and phosphate moieties of LPC (Fig. 1D), abolished or significantly reduced the uptake of [14C]-LPC-oleate (Fig. 1E). We verified that all mutants were expressed at the PM and that H427A mutant was expressed at levels similar to those of wild-type (WT) Spns1 (SI Appendix, Fig. S1 C and D). Henceforth, we chose H427A as a negative control. Spns1 is also able to transport [14C]-LPC-DHA and [3H]-LPC-palmitate, indicating a general activity toward LPCs with saturated, monounsaturated, and polyunsaturated fatty acids (Fig. 1 F and G). We further demonstrated that WT Spns1, but not the H427A mutant, can mediate mass uptake of LPC-DHA and increase the cellular mass of PC-DHA as revealed by thin-layer chromatography (SI Appendix, Fig. S1E). The increase in PC-DHA indicated that LPC-DHA was bio-incorporated into PC, further supporting the conclusion that Spns1 mediates LPC transport and not simply LPC binding to Spns1 at the PM. The uptake of [14C]-LPC-oleate by Spns1 was concentration dependent and saturable, with a pH optimum between pH 5.0 and 6.0 (Fig. 1 H and I), indicating that Spns1 is a proton-coupled LPC transporter. To define the ligand specificity of Spns1 transport, we used our cell surface transport assay coupled with lipidomics to quantify uptake of lysolipids and their bio-incorporation into re-esterified phospholipid species, using Mfsd2a as a positive control (Fig. 1J and SI Appendix, Fig. S2). Spns1 transported lysophospholipids with zwitterionic headgroups such as LPC and LPE. That Spns1 transported lyso-plasmalogen, an LPC with a fatty alcohol, indicated that the carbonyl group of the fatty acyl chain is not an essential feature of an Spns1 ligand. With the exception of lysophosphatidylglycerol (LPG), we could not detect transport of the anionic lysophospholipids lysophosphatidylserine (LPS), lysophosphatidylinositol (LPI), and lysophosphatidic acid (LPA). Lyso-sphingomyelin (lyso-SM) and S1P were not transported by Spns1, indicating it has a distinct substrate selectivity primarily for LPCs and LPEs, unlike its paralog Spns2 which transports S1P (23). The observed higher activity of Mfsd2a over Spns1 in this assay for LPC and LPE is likely explained by the higher cell surface expression of Mfsd2a, which evolved to function at the PM, while Spns1 transiently traffics through the PM. Overall, our results highlight an exquisite substrate selectivity of Spns1 for LPC, LPE, and LPG.
To investigate the function of endogenous Spns1 in the lysosome, we generated Spns1 knockout (KO) HEK293T cells using CRISPR/Cas9. Importantly, Spns1 KO cells displayed increased levels of total LPC and LPE, as determined by mass spectrometry (SI Appendix, Fig. S3 B and C), providing the first biochemical evidence that Spns1 deficiency leads to cellular accumulation of LPC and LPE. On the basis of Spns1 KO efficiency and the extent of LPC and LPE accumulation, we chose to use KO1 (gRNA1) for further investigation and henceforth designated it as Spns1 KO (SI Appendix, Fig. S3 A–C). Spns1 KO cells showed enlarged lysosomes detected as Lysotracker-positive compartments (Fig. 2A) and increased basal LC3b levels (Fig. 2B), indicating that Spns1 deficiency leads to defects in lysosome size and autophagy, phenotypes previously seen in Spns1-deficient cells (24–26). We next investigated the effects of Spns1 deficiency on the lysosome lipidome by using superparamagnetic iron oxide nanoparticles (SPIONs) to obtain lysosome-enriched fraction (SI Appendix, Fig. S3 D–F). As a first approach to determine whether Spns1 deficiency would lead to elevation of lysosomal LPCs, we metabolically labeled cellular phosphatidylcholine, SM, and LPC pools with [14C]-choline and isolated lysosomes. Remarkably, [14C]-labeled LPC was increased approximately fivefold in lysosome-enriched fraction from Spns1 KO cells relative to control cells (Fig. 2 C and D). In an independent label-free lipidomic approach, we observed a 1.48- to ∼4.91-fold increase of all quantified LPCs and LPEs in the lysosome-enriched fraction of Spns1 KO cells relative to control cells, which was rescued by re-expressing Spns1, which is consistent with these phenotypes being Spns1 dependent (Fig. 2 E and F). We also noted a large increase in the level of lysosomal sphingosine (Fig. 2E). Since sphingosine is not transported by Spns1 (SI Appendix, Fig. S1B), this increase is interpreted as a secondary effect of Spns1 deficiency. A similar accumulation of LPCs and LPEs was found in whole cells (Fig. 2F). Taken together, these data indicate that endogenous Spns1 mediates the transport of LPCs and LPEs out of lysosomes and is critical for maintaining cellular homeostasis of LPCs and LPEs.
We reasoned that since Spns1 is required for lysosomal efflux of LPC and LPE, that loss of Spns1 should lead to less LPC and LPE available for re-acylation by LPCATs, the rate-limiting enzymes of the Lands’ cycle in the ER. To test this hypothesis, we pulse-labeled control and Spns1 KO cells with [14C]-oleic acid, which is used in re-acylation of LPCs into PC (SI Appendix, Fig. S4A). Spns1 KO cells exhibited 25% less [14C]-oleic acid incorporated into PC relative to control cells during a 30-min labeling time (SI Appendix, Fig. S4B). Chemical inhibition of autophagosome formation and fusion or inhibition of lysosomal phospholipase activity that produces LPC normalized the level of [14C]-oleic acid incorporation into PC between Spns1 KO and control cells (SI Appendix, Fig. S4 B–D). Taken together, these findings indicate a Spns1-dependent contribution to lysosomal LPC efflux used for re-acylation into PC. We next sought to directly measure the in vivo flux of LPCs out of lysosomes and their subsequent re-acylation by following the fate of stable isotope-labeled PC (d9-PC 36:2; structure shown in Fig. 3A) delivered to lysosomes. If Spns1 indeed transports LPC out of lysosomes, we predicted that lysosome-derived d9-LPC species will be re-acylated by LPCATs at the ER to produce d9-containing PC species with various types of fatty acyl chains in addition to 18:1 (Fig. 3A). To selectively deliver d9-PC 36:2 to lysosomes, we took advantage of the specific binding of apolipoprotein E (apoE) to low-density lipoprotein receptor (LDLR) and generated d9-PC 36:2 nanodiscs containing apoE to drive LDLR-dependent endocytosis and subsequent delivery to lysosomes (27). Enrichment of d9-PC 36:2 over nondeuterated PC 36:2 in the lysosome-enriched fraction was significantly higher when cells were loaded for 3 h with apoE-complexed d9-PC 36:2 nanodiscs compared with cells loaded with d9-PC 36:2 nanodiscs without apoE (Fig. 3B), demonstrating apoE-dependent targeting of lysosomes. Importantly, and in agreement with Spns1 KO cells accumulating LPC (Fig. 2 E and F), d9-LPC 18:1 accumulated to a greater extent in the lysosome-enriched fraction of Spns1 KO cells relative to control cells treated with d9-PC 36:2 apoE-complexed nanodiscs (Fig. 3C). These findings further support the hypothesis that LPC is the breakdown product of PC in lysosomes (9) and that Spns1 regulates the levels of lysosomal LPC. We next measured the amount and diversity of d9-containing phospholipid species after loading cells with d9-PC 36:2 apoE nanodiscs. The total amount of d9-choline–containing lipid species was similar between Spns1 KO and control cells at all time points tested (Fig. 3D), indicating that there is no defect in the LDLR-dependent endocytosis pathway in Spns1 KO cells. Critically, Spns1 KO cells accumulated d9-LPC 18:1 at all time points relative to control cells (Fig. 3E). As early as the first hour of d9-PC 36:2 loading, control cells synthesized twofold more d9-PC 32:1, d9-PC 34:1, and d9-PC 34:2 relative to Spns1 KO cells (Fig. 3 F–H). These PC species are generated by re-acylation of lysosome-derived d9-LPC 18:1 with 14:0, 16:0, and 16:1 fatty acyl-coenzyme A (acyl-CoA) donors, respectively. The reduction in d9-PC formation in Spns1 KO cells persisted up to the 6-h time point. Furthermore, Spns1 KO cells produced less d9-containing sphingomyelin (SM) (d9-SM), particularly at later time points, which is consistent with the formation of this lipid requiring an additional step of d9-choline transfer from PC onto ceramide to form SM by SM synthase (Fig. 3I). While d9-PC species in Spns1 KO cells were reduced compared with those in control cells, we still observed low but significant production of d9-PC species in Spns1 KO cells, which can likely be attributed to lysosome-independent uptake of apoE nanodiscs as surmised by the cellular uptake of nanodiscs devoid of apoE (Fig. 3B). Taken together, data from our flux analysis support the conclusion that LPCs are transported out of lysosomes by Spns1 and re-acylated into PC pools, thus constituting a lysosomal salvage pathway for LPC, and by extension LPE, another abundant lysophospholipid produced in the lysosome and transported by Spns1 (Fig. 1J).
To test the role of Spns1 in mediating lysosomal LPC and LPE efflux in a multicellular organism, we first used zebrafish as a model system. Spns1 knockdown (KD) in zebrafish embryos has been reported to cause yolk sac opacity and lethality at early larval stages (28), but a molecular explanation for this phenotype was unknown. Lipidomic analysis on Spns1-deficient whole embryos revealed significant accumulation of LPC and LPE species relative to control embryos (SI Appendix, Fig. S5), consistent with the molecular function of Spns1 as an LPC and LPE transporter. Because there is no information on Spns1 function in mammals, we performed short hairpin RNA (shRNA)-mediated KD of Spns1 in livers of adult mice using adeno-associated virus 8 (AAV8). Liver is rich in lysosome activity for lipoprotein processing, autophagy, and energy metabolism and can thus serve as a model for studying the function of Spns1 at the organ level. Spns1 KD efficiency was verified by qRT-PCR and western blot of a lysosome-enriched fraction (SI Appendix, Fig. S6 A–C). The level of serum alanine aminotransferase (ALT) was significantly elevated in Spns1 KD mice, indicating liver damage (Fig. 4A). Serum cholesterol, but not triglycerides, was also elevated in Spns1 KD mice (Fig. 4B). While there were no noticeable pathological changes upon histological examination of liver sections (Fig. 4C), immunofluorescent staining with lysosomal markers LAMP1 and cathepsin B revealed a remarkable increase in lysosome clusters at the perinuclear region of hepatocytes from Spns1 KD mice relative to control mice (Fig. 4D). Consistent with these findings, density gradient fractionation of Spns1 KD liver homogenate revealed enrichment of lysosomes in low-density fractions (fractions 1 and 2), while control showed enrichment of lysosomal markers in higher-density fractions (i.e., fraction 6) (SI Appendix, Fig. S6 D–F). Furthermore, these low-density lysosomes in Spns1 KD livers showed an increased ratio of glycosylated:de-glycosylated form of cathepsin B (Fig. 4E and SI Appendix, Fig. S6F), indicative of lysosome alkalinization (29). In addition, Spns1 KD liver showed an increased level of LC3b-I and LC3b-II (Fig. 4F), suggesting a block in autolysosome formation. We next tested whether Spns1 KD in liver resulted in elevated lysosomal LPCs and LPEs. Lipidomics analysis of lysosome-enriched fractions (sum of F1, F2, and F6) revealed an 8-fold to 13-fold accumulation of total and individual species of LPCs, LPEs, and LPGs in Spns1 KD lysosome-enriched fractions (Fig. 4G and SI Appendix, Fig. S6G), consistent with the function of Spns1 as a lysosomal lysophospholipid exporter. Such accumulation was significant enough to be observed in whole-cell lysates without subcellular fractionation, especially for LPCs and LPEs containing saturated fatty acyl chains, such as LPC 16:0 and LPC 18:0 (Fig. 4G and SI Appendix, Fig. S6G). We also observed enrichment of other lipid classes in Spns1 KD lysosomes. In fact, the total lipid content normalized to protein content was threefold higher in Spns1 KD lysosomes, consistent with an increase in lysosome number as revealed by an increase in LAMP1 immunofluorescence (Fig. 4 D and G). Bismonoacylglycerophosphate (BMP), a characteristic anionic glycerophospholipid found exclusively in intraluminal membranes of late endosomes and lysosomes, was 12-fold higher in Spns1 KD lysosomes compared with control lysosomes, suggesting an expansion of intralysosomal membranes (Fig. 4G). Notably, SM and ganglioside metabolites, including hexosylceramide, ceramide, and sphingosine, as well as cholesterol and cholesteryl esters, were highly enriched in Spns1 KD lysosomes (Fig. 4G and SI Appendix, Fig. S6G). Such changes in lipid profile resemble other lysosomal lipid storage diseases such as Niemann-Pick C2 disease and Gaucher disease (6, 30, 31). The observed lipid enrichment cannot be fully attributed to the increase in size and number of lysosomes because structural phospholipids, including PC and PE, showed only a modest twofold to threefold accumulation relative to controls, similar to the fold change observed for total lipid content (Fig. 4G). It is likely that Spns1 deficiency leads to lysosomal dysfunction such as luminal alkalization, which is expected to negatively impact the functions of enzymes involved in sphingolipid and cholesteryl ester metabolism. To investigate the longer-term effects of Spns1 deficiency, we examined mice at 8 wk after injection of AAV8. The enlargement of lysosomes, elevation of LC3b-II, and tissue level accumulation of LPCs and LPEs persisted (SI Appendix, Fig. S7 A–F). Notably, there was lobular inflammation in liver shown by increased number and clustering of galectin 3–positive immune cells, and elevated serum ALT (SI Appendix, Fig. S7G and Fig. 7B). Gene enrichment analysis derived from RNA sequencing from these livers was in agreement with increased inflammation (SI Appendix, Fig. S7H).
This study identifies Spns1 as the transporter that mediates the rate-limiting lysosomal efflux of LPC and LPE, which uncovered the existence of a lysosomal salvage pathway for LPC and LPE derived from catabolism of PC and PE, the two most abundant phospholipids of eukaryotic membranes. We observed that Spns1 deficiency had pleiotropic effects in cells and mouse liver, including inflammation, secondary accumulation of multiple lipid species in lysosomes, and impaired autophagy, similar to other lysosomal lipid storage diseases such as Niemann-Pick disease type C (NPC) , GM1 gangliosidosis, and Gaucher disease (32). The majority of lysosomal lipid storage diseases are due to mutations in luminal enzymes that break down lysosomal lipids, with NPC1 being the only known lipid transporter directly linked to a lysosomal lipid storage disease. Spns1 deficiency could represent another example of a lysosomal storage disease that results from the loss of lipid transporter activity, but whether such a disease resulting from mutations in Spns1 exists in humans remains to be determined. Previous reports demonstrated that Spns1 deficiency leads to defective autophagosome-lysosome fusion in zebrafish (25) and defective autophagic lysosome reformation after starvation in a cultured cell line (24). Moreover, deficiency of Spin, the drosophila ortholog of Spns1, resulted in defects in endosome-to-lysosome trafficking with synaptic dysfunction (33). However, because the ligand for Spns1 was not known and hence its function was unknown, the molecular basis for explaining these phenotypes remained unclear. An asymmetrical distribution of lysolipids, including cone-shaped LPC, can lead to positive membrane curvature, which is important for membrane fusion and is proposed to be important for autophagosome-lysosome fusion (34). Importantly, model membrane systems have shown that high levels of LPC can inhibit membrane fusion (35, 36). It is plausible that the defects in autophagosome-lysosome fusion and lysosome reformation in Spns1-deficient cells could in part be a result of the effects of markedly elevated lysosomal LPC and LPE on membrane dynamics. Consistent with negative effects of elevated LPC on lysosomal membrane dynamics, CRISPR/Cas9 genome-wide screens identified that Spns1 deficiency reduced host cell infection by a common cold coronavirus and Ebola virus that require fusion with the lysosome membrane during the infection process (37, 38). This discovery that Spns1 is an LPC/LPE transporter in contrast to the S1P transporter Spns2 remarkably mirrors that of Mfsd2a (LPC/LPE transporter) and Mfsd2b (S1P transporter) (17, 23). It is notable from an evolutionary perspective that despite being functionally similar, the LPC/LPE transporters Spns1 and Mfsd2a (also Spns2 and Mfsd2b) lack sequence similarity beyond being in the same superfamily, which suggests that parallel evolutionary processes are at play for selecting the same substrate specificity, albeit for transporters expressed at different subcellular locations. A recently solved cryo-electron microscopy structure of Mfsd2a bound to LPC suggested that it functions as a lysolipid flippase (15). It is possible that Spns1 may function by an analogous mechanism, although biochemical evidence for such a mechanism remains to be determined for both Mfsd2a and Spns1. Interestingly, LPS is transported by Mfsd2a but not by Spns1. This substrate specificity correlates with the finding that LPS might not be generated from PS in lysosomes (9), suggestive of a lack of selective pressure for binding LPS. We also note from our mass uptake lipidomics data that both Spns1 and Mfsd2a seem to transport LPG, a ligand that we had not tested in previous studies of Mfsd2a. This suggests hitherto undetermined aspects in the substrate specificity of these lipid transporters. Whether LPG is a physiological ligand for Spns1 and what role LPG recycling may play in cellular function require further study. Given the centrality of lysosomes in cellular homeostasis, the deorphanization of Spns1 provides new opportunities for studying the role of lysolipid transport and recycling in physiology and disease.
HEK293T and HeLa cells were obtained from the American Type Culture Collection and grown in Dulbecco’s modified Eagle medium (DMEM; HyClone) supplemented with 10% heat inactivated fetal bovine serum (FBS) (Gibco) plus penicillin and streptomycin (Gibco) at 37 °C with 5% CO2. FBS was delipidated according to Hannah et al (39) and used at 5% delipidated FBS in DMEM in experiments that used delipidated media.
Codon optimized complementary DNAs (cDNAs) for human SPNS1, SPNS3, MFSD1, MFSD2A, MFSD8, MFSD12, and CLN3 were synthesized by GenScript and cloned into a pcDNA3.1 plasmid with or without a C-terminal Myc-6His Tag. Mouse Spns1 cDNA was isolated by PCR from a cDNA library of an RAW264.7 cell and cloned into pcDNA3.1 plasmid. SPNS1 mutants were generated by the QuikChange site-directed mutagenesis method (Agilent) (40).
HeLa cells transfected with plasmid encoding indicated constructs for 24 h were washed once with reaction buffer before incubating with the indicated concentration of radiolabeled ligands in 0.5 mL reaction buffer for 30 min at 37 °C with 5% CO2. Cells were washed twice with 0.5% (wt/vol) fatty acid–free bovine serum albumin (BSA) (Sigma) in reaction buffer and then extracted twice with 1% Triton X-100 in tris(hydroxymethyl)aminomethane (Tris)-buffered saline. Extracts were transferred to 4 mL of EcoLite(+) scintillation fluid (Avantor) for scintillation counting using a Tri-Carb 2910 TR Liquid Scintillation Analyzer (PerkinElmer). List of and preparation of radiolabeled lipids are found in SI Appendix, Supplementary Methods. The following are reaction buffer compositions for each specified pH: pH 5.0: 25 mM sodium acetate, 150 mM NaCl, 5 mM glucose, 1 mM MgCl2; pH 5.5: 25 mM sodium citrate, 150 mM NaCl, 5 mM glucose, 1 mM MgCl2; pH 6.0 and pH 6.5: 25 mM sodium 2-(N-morpholino)ethanesulfonate (MES), 150 mM NaCl, 5 mM glucose, 1 mM MgCl2; pH 7.0 and pH 7.5: 25 mM sodium N-2-hydroxyethylpiperazine-N′-2-ethanesulfonic acid (HEPES), 150 mM NaCl, 5 mM glucose, 1 mM MgCl2. For the bulk transport assay, cells were incubated with 50 µM of each specified lipid in pH 6.0 buffer for 1 h. Cells were then washed twice with 0.5% (wt/vol) fatty acid–free BSA in phosphate-buffered saline (PBS) to remove excess ligand and washed once again with PBS to remove BSA. After lipid extraction, the remaining cell skeleton on plates after hexane:isopropanol extraction was dissolved in 0.1% sodium dodecyl sulfate in 0.1 M NaOH for 4 h to determine protein concentration with the Pierce BCA Protein Assay Kit. Radiolabeled ligands and lipids used in the experiments are listed in SI Appendix, Supplementary Methods.
Homology model of the luminal-facing conformation of human Spns1 was constructed by I-TASSER (41) using the outward-facing crystal structure of human MFSD10 (Protein Data Bank ID: 6S4M) as a preferred template. Model of the cytosol-facing conformation of human Spns1 was obtained from the AlphaFold database (42). In silico docking of LPC-oleate to Spns1 was performed as described in SI Appendix, Supplementary Methods.
KO cell lines were generated by infecting HEK293T cells with lentivirus carrying single guide RNA (sgRNA) directed against exon 1 of SPNS1 in lentiCRISPRv2 plasmid (Addgene, 52961). Guide RNA (gRNA) sequences are as follows: gRNA1: 5′-CTACATGGACCGCTTCACCG-3′; gRNA2: 5′- CCGTTCGGCTCTCATAGTGG-3′; gRNA3: 5′-CGTGGACCCTGGCAACCCCG-3′; gRNA4: 5′-CCGCCACTATGAGAGCCGAA-3′; gRNA5: 5′-CGGGGTTGCCAGGGTCCACG-3′; gRNA6: 5′-CTCGGACTTCGGGTTCCCCG-3′. The scrambled gRNA used for control cells was 5′-GTGTAGTTCGACCATTCGTG-3′. For SPNS1 WT rescued plasmid, a codon-optimized SPNS1 sequence under a minipTK promoter (from pTK-HSV-BP2; ATCC), followed by internal ribosome entry site (IRES; from pIRES2-EGFP) was cloned by the Gibson Assembly (43) method into a lentiCas9-Blast plasmid (Addgene, 52962) which has the cytomegalovirus (CMV) promoter and Cas9 sequence excised. Procedures for viral particle production, cell infection, and selection are described in SI Appendix, Supplementary Methods.
Cells were stained with 50 nM LysoTracker Red (Thermo Fisher Scientific) in medium for 30 min. Hoechst 33342 (1:1,000) (Thermo Fisher Scientific) was added to the medium in the final 10 min. Cells were imaged live using an LSM710 confocal microscope (Carl Zeiss).
Isolation of lysosomes from cultured cells was carried out according to Thelen et al (44). Details are provided in SI Appendix. To prepare lysosome enriched fraction from mouse liver, freshly harvested mouse livers were minced in 10 mL/g of liver weight of homogenization buffer (HB; 0.25 M sucrose, 10 mM HEPES, 1 mM ethylenediaminetetraacetic acid [EDTA], cOmplete Protease Inhibitor), and homogenized with six strokes in a glass homogenizer. The homogenate was centrifuged at 1,000 g for 10 min. The resulting pellet was homogenized again in 5 mL/g of liver weight of HB and centrifuged again to generate postnuclear supernatant (PNS). These two PNSs were combined and centrifuged for 10 min at 3,000 g to remove heavy mitochondria. The resulting supernatant was centrifuged at 20,000 g for 20 min to pellet a light mitochondria fraction (LMF). The LMF was resuspended and loaded into a discontinuous OptiPrep density gradient (with density steps of 8%, 12%, 16%, 19%, 22.5%, 27%) and ultracentrifuged at 150,000 g for 4 h in an SW41 rotor (Beckman Coulter). The gradient was collected from the top of the gradient to the bottom. β-N-acetylglucosaminidase activity of PNS, LMF, and each fraction was determined by using a β-N-acetylglucosaminidase assay kit (Sigma, CS0780). Protein concentration was determined by Pierce BCA Protein Assay Kit. For SI Appendix, Fig. S6F, 2.5% (by volume) of each fraction was loaded for western blot analysis. Equal amounts of protein were loaded for Fig. 4E and SI Appendix, Figs. S3D and S6C.
For metabolic labeling of cells with [14C]-choline, cells were grown in 10-cm dishes and were labeled with 4 mL of choline-deficient DMEM plus 10% FBS containing 0.2 µCi of [14C]-choline (American Radiolabeled Chemicals, specific activity: 50 mCi/mmol) for 24 h before harvesting for lysosome isolation.
A total of 1.079 mg of d9-PC 36:2 (L-1182d, Echelon Biosciences) was dried in a nitrogen stream and reconstituted in 18.53 µL of Tris-buffered saline (TBS) (10 mM Tris HCl [pH 7.4], 150 mM NaCl, 0.25 mM EDTA, 0.0005% NaN3). A total of 42.2 µL of sodium cholate (30 mg/mL) was added to the lipid suspension and incubated at room temperature for 30 min with shaking; then 100 µL of 5 mg/mL apoE3 (900010, Sigma) was added to the mixture and incubated at room temperature with rotation mixing for 1 h for apoE incorporation with into lipid discs. Sodium cholate was removed by incubating with 0.2215 g of BioBeads SM2 (Bio-Rad) overnight. The stock concentration of apoE-d9 PC-36:2 nanodiscs was 0.5 mg/mL apoE plus 1 mg/mL d9-PC-36:2, and aliquots were snap frozen and stored at −80 °C until further use. Nanodiscs with d9-PC-36:2 only were constructed in the same way, except that 100 µL of TBS was used instead of apoE3. For delivery of apoE-d9 PC-36:2 nanodiscs into cells, cells were grown in delipidated medium for 24 h to upregulate LDLR before incubating with apoE-d9-PC-36:2 nanodiscs. For time course analysis, cells grown in 12-well plates were incubated with 15 µg apoE-d9 PC-36:2 nanodiscs/mL of medium (based on apoE concentration in the discs and equivalent to 22.6 nmol of d9-PC-36:2). For equivalent experiments that required lysosome isolation, cells were grown in 6-cm dishes and incubated with 12.5 µg apoE-d9 PC-36:2 nanodiscs/mL of medium (based on apoE concentration and equivalent to 67.85 nmol of d9-PC 36:2) for 3 h before SPION-mediated lysosome isolation.
All mice were bred and maintained at the Duke-National University of Singapore animal facility. The experimental protocols were performed in concordance and approved by SingHealth Institutional Animal Care and Use Committee (IACUC protocol #2015/SHS/1416). All mice were housed in 12-h light:12-h dark cycles with humidity and temperature-controlled environment at 23 °C. The mice were fed ad libitum with standard normal chow diet consisting of 12% fat, 23% protein, and 65% carbohydrate based on caloric content and given free access to water. For the AAV8-SPNS1 shRNA KD experiment, AAV8-SPNS1 shRNA (5′-GCAGTTCTTTAACATCGGAGA-3′ (Vector Biolabs) or AAV8-scrambled shRNA control (Vector Biolabs) were injected into 8-wk-old C57BL/6NTAC mice via a retro-orbital venous route at a concentration of 5 × 1011 genome copies per mouse. Four weeks after injection of AAV, mice fasted overnight and were then euthanized. Before being euthanized, mice were anesthetized with 200 mg/kg ketamine and 20 mg/kg xylazine in PBS, followed by blood collection via cardiac puncture to generate serum. Mice were then perfused with PBS before the liver was collected for lysosome isolation, snap-frozen in liquid nitrogen, or fixed in buffered formaldehyde solution. Measurement of blood parameters, histology, immunofluorescence, and immunohistochemistry of mouse tissue was performed as described in SI Appendix, Supplementary Methods. RNA from mouse liver was extracted using TRIzol and Rneasy spin column (QIAGEN) and reverse transcribed using iScript RT Supermix (Bio-Rad). qPCR was performed using SensiFAST SYBR Hi-ROX (Bioline Agrosciences) with the following primers: for mouse SPNS1, forward: 5′- ACCTCCTGAACTACATGGAC-3′, reverse: 5′- CCATGTAACTGGAGATGAAC-3′; for mouse β actin, forward: 5′-GGCTGTATTCCCCTCCATCG-3′, reverse: 5′-CCAGTTGGTAACAATGCCATGT-3′ (PrimerBank ID: 6671509a1).
Sample preparation for lipidomics is described in SI Appendix, Supplementary Methods. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and data analysis were performed as previously reported (45). Targeted analysis was performed in dynamic multiple reaction monitoring MS-positive and -negative (only when measuring LPA species) ion mode. Labeled lipids (PC, LPC, and SM) were monitored by increasing the mass divided by charge number of the precursor and fragment ion (when containing the labeled portion of the precursor) by 9 Da as a result of incorporation of the labeled choline group. Internal standards were used to normalize the raw peak areas in the corresponding lipid class, and concentrations were further normalized to the protein concentration in the original sample. For SPION or liver tissue fractionation, concentrations were further normalized to sample volume.
Statistical analysis was performed using Graphpad PRISM for two-sided unpaired Student t test, and one-way ANOVA with Dunnett’s test or with Tukey’s test as indicated in the figure legends. Additional information can be found in SI Appendix, Supplementary Methods. | true | true | true |
PMC9546645 | 36213832 | Ran Zhao,Xin Zhou,Wencan Zhang,Le Li | Effect of Long Noncoding RNA HULC on Proliferation, Migration, and Invasion of Osteosarcoma Cells | 30-09-2022 | Background Previous studies had shown that lncRNA HULC exhibited different effects in human cancers. However, the role of HULC was not reported in osteosarcoma. Hence, we designed this research to explore the function of HULC in osteosarcoma. Methods Firstly, HULC expression was measured in osteosarcoma tissues and cells via the RT-qPCR assay. The protein expression was detected through western blot. Then, CCK-8 and Transwell assays were conducted to measure cell proliferation, migration, and invasion. Results The expression of HULC was obviously higher in osteosarcoma tissues and cells compared with normal control. Moreover, cell proliferation, migration, and invasion were inhibited by HULC knockdown in osteosarcoma cells. HULC overexpression markedly increased osteosarcoma cell proliferation and tumor size in vivo. Furthermore, HULC increased the activity of AKT-PI3K-mTOR pathway by blocking PTEN in osteosarcoma cells. LY294002 inhibited the phosphorylation of AKT, mTOR, and PI3K. Overexpressing HULC enhanced cell migration and invasion of SAOS-2 cells and MG63 cells, while LY294002 reversed the effects. Conclusion HULC enhanced the progression of osteosarcoma through targeting PTEN. | Effect of Long Noncoding RNA HULC on Proliferation, Migration, and Invasion of Osteosarcoma Cells
Previous studies had shown that lncRNA HULC exhibited different effects in human cancers. However, the role of HULC was not reported in osteosarcoma. Hence, we designed this research to explore the function of HULC in osteosarcoma.
Firstly, HULC expression was measured in osteosarcoma tissues and cells via the RT-qPCR assay. The protein expression was detected through western blot. Then, CCK-8 and Transwell assays were conducted to measure cell proliferation, migration, and invasion.
The expression of HULC was obviously higher in osteosarcoma tissues and cells compared with normal control. Moreover, cell proliferation, migration, and invasion were inhibited by HULC knockdown in osteosarcoma cells. HULC overexpression markedly increased osteosarcoma cell proliferation and tumor size in vivo. Furthermore, HULC increased the activity of AKT-PI3K-mTOR pathway by blocking PTEN in osteosarcoma cells. LY294002 inhibited the phosphorylation of AKT, mTOR, and PI3K. Overexpressing HULC enhanced cell migration and invasion of SAOS-2 cells and MG63 cells, while LY294002 reversed the effects.
HULC enhanced the progression of osteosarcoma through targeting PTEN.
Osteosarcoma is caused by bone cell abnormal differentiation and proliferation. Consistent with medicine information, the incidence of osteogenic sarcoma is around 0.2–3/100000 per annum [1]. It is the foremost common primary bone tumor in youngsters and adolescents with a high degree of malignancy. Osteosarcoma typically shows a high tendency to pathologic process spread [2]. Osteosarcoma is commonly treated with a mixture of therapies that may embody surgery, therapy, and radiotherapy [3]. However, in recent years, the survival rate of patients with osteosarcoma amid distant metastasis has not been considerably improved, and also the impact of therapy has not been considerably improved, and also the treatment of osteosarcoma remains controversial [4, 5]. Thus, new therapeutic targets ought to be found to produce clinical treatment choices to enhance the survival rate [6]. High-throughput transcriptome sequencing analysis has shown that only 2% of the human genome can be transcripted into proteins, and 98% can be transcripted into noncoding RNAs [7]. The function of these noncoding RNAs is still poorly understand. The long noncoding RNA is a type of noncoding RNA that is longer than 200 nt [8]. lncRNAs have been shown to be involved in a large number of cellular processes, such as cell proliferation, transcriptional and posttranscriptional modification, epigenetic modification, and invasion [9]. The large number of studies shows that lncRNA could play an important role in many types of cancer [10]. For example, Chen et al. showed that lncRNA HULC was overexpressed in epithelial ovarian carcinoma and target ATG7 [11]. Zheng et al. showed that lncRNA HULC was highly expressed in HeLa cells and promotes cell migration and invasion [12]. lncRNA HULC was first reported by Panzitt et al. in 2007, which was overexpressed lncRNA in human hepatocellular carcinoma [13]. HULC gene is located on chromosome 6p24.3 with approximately 500 nucleotides in length and contains two exons [14]. Since then, the function of HULC has been demonstrated in multiple cancer types [15, 16]. HULC could promote cancer cell survival, proliferation, and invasion. These studies indicated that HULC played an important role in the development of cancer [16, 17]. HULC was overexpressed in human osteosarcoma cell which has been shown in the previous studies. However, the mechanism of HULC involved in the progression of osteosarcoma is unknown, and the interaction of HULC and PTEN has not been proved in osteosarcoma. Therefore, we investigated the interaction of HULC and PTEN in promoting osteosarcoma cell proliferation and migration.
The human osteosarcoma cell lines, including Saos-2, U-2OS, and MG63, were selected as subjects for subsequent analysis. All cells were purchased from the American Type Culture Collection (ATCC) (Manassas, VA, USA).
Total RNA was extracted by TRIzol reagent (Invitrogen Inc., Carlsbad, CA, USA). Subsequently, the RNA was reversely transcribed to the cDNA. The M-MLV reverse transcriptase (Promega, Madison, WI, USA) was used for reverse transcription reaction. SYBR-Green Real-Time Master Mix (Toyobo, Tokyo, Japan) was applied for qRT-PCR reaction. Finally, the data were calculated with 2−ΔΔCt method. HULC P1: 5′-AACCTCCAGAACTGTGAT-3′ and HULC P2: 5′-CATAATTCAGGGAGAAAG-3′ β-Actin P1: 5′-CTTCCTTCCTGGGCATGGAG-3′ and β-actin P2: 5′-GGAACGCTTCACGAATTTGC-3′
The cells were treated with RAPA buffer (Beyotime, Jiangsu, China) on ice for 30 min. BCA kit (Pierce, Rockford, IL, USA) was applied for the measurement of protein concentration. Subsequently, total proteins were separated by 12% SDS-polyacrylamide gel electrophoresis (SDS-PAGE) and then were transferred on polyvinylidene fluoride membranes (Millipore, Billerica, MA, USA). The membranes were treated with 5% fat-free milk for 2 h and then were incubated with the antibodies of AKT (PTG, USA, 1 : 1000), p-AKT (PTG, USA, 1 : 10000), PI3K (CST, USA, 1 : 1000), p-PI3K (CST, USA, 1 : 1000), mTOR (PTG, USA, 1 : 20000), p-mTOR (PTG, USA, 1 : 10000), PTEN (ABclonal, China, 1 : 1000), or β-actin (CST, USA, 1 : 1000). After washing and incubating with the second antibodies, the abundance of the proteins was analyzed by enhanced chemiluminescence (ECL).
In short, the specific oligonucleotides targeting HULC were synthesized by Genepharmacy Technology (China): sense: 5′-GATCCGCCACATGAACGCCCAGAGATTTTCAAGAGAAATCTCTGGGCGTTCATGTGGTTTTTTG-3′ and antisense: 5′-AATTCAAAAAACCACATGAACGCCCAGAGATTTCTCTTGAAAATCTCTGGGCGTTCATGTGGCG-3′. After that, the plasmids and control were transfected into Saos-2 and MG63 cells. RT-qPCR was performed to confirm the knockdown efficiency of HULC.
The cell viability was detected using Cell Counting Kit-8 (CCK-8). Briefly, 1 × 104 cells were seeded into 96-well plates and cultured for 1, 2, 3, and 4 d. Subsequently, osteosarcoma cells were incubated with CCK-8 at 37°C for 1 h. The absorbency at 450 nm of the cells was measured with microplate reader Thermo Plate (Rayto Life and Analytical Sciences Co., Ltd., Germany).
For migration assay, 2 × 104 cells and 100 μl serum-free medium were injected into upper chamber. For Transwell invasion assay, Matrigel-coated chamber was used for invasion assay, and 3 × 104 cells were plated in 100 μl serum-free medium in the upper. In both assays, 500 μl of the medium and 20% FBS were added to the lower chamber. Subsequently, the cells were cultured at 37°C and 5% CO2 for 24 h. After that, the cells were fixed with 100% methanol for 30 min, and then, the cells in upper chamber were removed. Finally, the cells were stained with 0.5% crystal violet (Sigma, St. Louis, MO, USA) for 20 min for cell count.
Male BALB/c nude mice (6 weeks) were obtained from HFK Biosciences and maintained under pathogen-free conditions. The experiment was approved by the Shandong Provincial Hospital Affiliated to Shandong First Medical University. For tumor propagation analysis, the mice accepted the subcutaneous injection including 2 × 106 HULC overexpression cells. After 5 week, the weight of the tumors was measured.
SPSS 20.0 (SPSS Inc., Chicago, IL, USA) was applied for data analyses. The Kaplan-Meier method and log-rank test were applied for the visualization of survival curves. Moreover, one-way analyses of variance and two-tailed Student's t-tests were applied for difference analysis. P < 0.05 was considered statistically significant.
First, the expression of lncRNA HULC abundance was examined in osteosarcoma tissue and normal tissue using RT-qPCR. The expression of HULC in tumor tissues was higher than normal tissues (Figure 1(a)). Similarly, the expression of HULC was also increased in tumor cell lines Saos-2, MG63, and U-2OS in contrast to normal cell (hFOB 1.19) (Figure 1(c)).
Then, the effect of downregulation HULC on osteosarcoma cells was investigated. First, HULC was knockdown in osteosarcoma cell lines successfully (Figures 2(a) and 2(b)). In CCK-8 assay, we found that HULC knockdown significantly reduced cell proliferation in osteosarcoma cell lines (Figures 2(a) and 2(d)). We used Transwell assay to detect cell migration and invasion. HULC knockdown notably inhibited the migration of osteosarcoma cell lines, including SAOS-2 (Figure 3(a)) and MG63 (Figure 3(c)). HULC knockdown markedly inhibited the invasion of osteosarcoma cell lines, including SAOS-2 (Figure 3(b)) and MG63 (Figure 3(d)).
Overexpression experiment was performed to detect the effect of HULC in osteosarcoma cell proliferation. In SAOS-2 (Figure 4(a)) and MG63 cells (Figure 4(b)), we successfully overexpressed HULC using overexpression vectors. Overexpression of HULC significantly increased cell proliferation of SAOS-2 (Figure 4(c)) and MG63 cells (Figure 4(d)). Then, we injected the cultured cells into nude mice for tumorigenesis. As shown in Figure 4(e), HULC overexpression markedly raised tumor size. As observed by statistical data, HULC overexpression markedly raised tumor weight (Figure 4(f)) and volume (Figure 4(g)).
In order to investigate the interaction between HULC and PTEN, we overexpressed HULC, and western blot was applied to detect the expression of PTEN and other proteins (Figure 5(a)). We found that overexpression of HULC could result in decreased expression of PTEN protein (Figure 5(b)). Moreover, excessive HULC increased the phosphorylation of AKT (Figure 5(c)), mTOR (Figure 5(d)), and PI3K (Figure 5(e)), while overexpressed PTEN fully abrogated the HULC's action. This suggested that HULC interacts in vivo with signaling pathways that promote cancer formation. However, the overexpression of PTEN cancels the role of HULC. Together, PTEN determined the carcinogenic function of HULC in liver cancer cells.
To explore whether the effect of HULC on osteosarcoma cells depends on PI3K/Akt/mTOR signaling pathway, we added LY294002, an inhibitor of PI3K signaling pathway. LY294002 inhibited the phosphorylation of AKT, mTOR, and PI3K (Figure 6(a)). Overexpressing HULC enhanced cell migration and invasion of SAOS-2 cells (Figure 6(b)) and MG63 cells (Figure 6(c)), while LY294002 reversed the effects of overexpressing HULC on the cell migration and invasion.
Of all bone cancers, osteosarcoma is the second leading cause of death in children [2]. Osteosarcoma is a fibrogenic malignant bone tumor that can directly or indirectly form tumor bone-like tissue and bone tissue during development, which is a common primary tumor of bone [3]. Osteosarcoma has atypical clinical symptoms in the early stage of onset, which is easy to be confused with other traumatic swelling and pain diseases. Due to the invasive growth of osteosarcoma and early rapid proliferation, the cure rate and prognosis of osteosarcoma are poor. Recent studies have shown that the occurrence, development, and biological characteristics of osteosarcoma are the result of polygenic and multifactorial abnormalities dominated by oncogene activation or tumor suppressor gene inactivation [18]. Therefore, to study the occurrence and development of osteosarcoma, we need to understand the changes of its gene level. For the treatment of osteosarcoma, there are mainly radiotherapy, chemotherapy, and combination therapy, but the prognosis is still not improved [5]. Despite numerous studies, the pathogenic mechanisms of osteosarcoma are still not fully understood. Previous reports have shown that lncRNA is involved in the formation and development of a variety of tumors [19], mainly because it is involved in important cellular processes such as regulating genome expression, transcription, and translation [20]. lncRNA can participate in the pathological process of tumor cell proliferation, metastasis, and invasion [21, 22]. As the lncRNA located on human chromosome 6p24.3, HULC is primarily located in the cytoplasm and can play an important role in various physiopathological processes by binding to the ribosome. Previous reports have shown that HULC was involved in various processes of tumor formation and metastasis. Plasma HULC is considered to be a biomarker for detecting liver cancer [23]. In gastric cancer, high expression of HULC promotes cell proliferation, inhibits apoptosis of cancer cells, and enhances tumor metastasis [24]. Xu et al. found that HULC regulates PTPRO/NF-κB signaling pathway that promotes the development of lung squamous cell carcinoma [25]. The present study also found that the expression of lncRNA HULC was obviously increased in human osteosarcoma tissues and cells. The present study was investigating the role of HULC in malignant behaviors of osteosarcoma. This study reflected that downregulation of HULC impeded the proliferation, migration, and invasion of osteosarcoma cells. In addition, HULC overexpression markedly increased osteosarcoma cell proliferation and tumor size in vivo. Thus, HULC can promote the malignant behavior of osteosarcoma cells. PI3 kinase and PTEN are major modulators of the PI3K pathway, regulating cell growth, proliferation, and survival. PTEN regulates PI3K signaling by dephosphorylating the lipid signaling intermediate PIP3 [26]. Mutations in the PTEN gene have been linked to many cancers. Studies have shown that in liver cancer, HULC can inhibit PTEN and accelerate cancer development [15]. Whether a similar mechanism exists in osteosarcoma is unknown. In order to investigate the interaction between HULC and PTEN, we overexpressed HULC, and western blot was applied to detect the expression of PTEN and other proteins. We found that overexpression of HULC obviously decreased expression of PTEN protein. Moreover, excessive HULC increased the phosphorylation of AKT, mTOR, and PI3K while overexpressed PTEN fully abrogated the HULC's action. This suggested that HULC interacts in vivo with signaling pathways that promote cancer formation. However, the overexpression of PTEN cancels the role of HULC. In addition, the present study found that LY294002 inhibited the phosphorylation of AKT, mTOR, and PI3K. Overexpressing HULC enhanced cell migration and invasion of SAOS-2 cells and MG63 cells, while LY294002 reversed the effects. A large number of literature reports pointed out that PI3K/Akt/mTOR signaling pathway is an important signaling pathway in cells, which is widely involved in the regulation of cell functions such as cell proliferation, apoptosis, and invasion [27]. The abnormal activation of PI3K/Akt/mTOR signaling pathway has been confirmed in a variety of cancer cells. Miao et al. believed that PI3K/Akt/mTOR signaling pathway is the key to driving tumor cell proliferation and invasion, and emp1 can promote glioblastoma cell proliferation by activating PI3K/Akt/mTOR signaling pathway [28]. In conclusion, this study supported that the expression of lncRNA HULC was increased in osteosarcoma, which enhanced the progression of osteosarcoma in vivo and in vitro. | true | true | true |
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PMC9546670 | 36212996 | Mengxian Shu,Chunhui Xiang | Relationship between Peripheral Blood miR-181c, miR-101, and Cognitive Impairment in Patients with Diabetes Mellitus Complicated with Acute Stroke | 30-09-2022 | Objectives To explore the relationship between peripheral blood microRNA-181c (miR-181c), microRNA-101 (miR-101), and cognitive impairment (CI) in patients with diabetes mellitus (DM) complicated with acute stroke (AS). Methods A retrospective analysis was performed on 70 patients with DM complicated with AS admitted to the hospital between January 2019 and December 2021. According to presence or absence of CI, they were divided into CI group (41 cases) and non-CI group (29 cases). The clinical characteristics and general data (blood glucose and blood lipid) of patients were statistically analyzed. The relative expression levels of miR-181c and miR-101 in peripheral blood were detected by real-time fluorescence quantitative PCR. The risk factors of CI were analyzed by logistic regression analysis. The diagnostic value of peripheral blood miR-181c and miR-101 for CI was evaluated by receiver operating characteristic (ROC) curves. Results The relative expression levels of peripheral blood miR-181c and miR-101 in the CI group were lower than those in the non-CI group (P < 0.05). The occurrence of CI was related to age, course of DM, AS location, time from onset to admission, HbA1c, TG, UA, and Hcy levels (P < 0.05). Logistic regression analysis showed that age, AS location, HbA1c, miR-181c, and miR-101 were related influencing factors of CI in patients with DM complicated with AS (P < 0.05). The results of ROC curves analysis showed that AUC, sensitivity, and specificity of miR-181c combined with miR-101 for predicting CI were 0.865, 73.17%, and 89.66%, respectively (P < 0.05). Conclusions The peripheral blood miR-181c and miR-101 are low expressed in patients with DM complicated with AS, and advanced age, intracortical AS lesions, increased HbA1c, and low expression of miR-181c and miR-101 are all independent risk factors for CI in patients with DM complicated with AS. Besides, the combined detection of miR-181c and miR-101 expression has a good diagnostic value for CI. | Relationship between Peripheral Blood miR-181c, miR-101, and Cognitive Impairment in Patients with Diabetes Mellitus Complicated with Acute Stroke
To explore the relationship between peripheral blood microRNA-181c (miR-181c), microRNA-101 (miR-101), and cognitive impairment (CI) in patients with diabetes mellitus (DM) complicated with acute stroke (AS).
A retrospective analysis was performed on 70 patients with DM complicated with AS admitted to the hospital between January 2019 and December 2021. According to presence or absence of CI, they were divided into CI group (41 cases) and non-CI group (29 cases). The clinical characteristics and general data (blood glucose and blood lipid) of patients were statistically analyzed. The relative expression levels of miR-181c and miR-101 in peripheral blood were detected by real-time fluorescence quantitative PCR. The risk factors of CI were analyzed by logistic regression analysis. The diagnostic value of peripheral blood miR-181c and miR-101 for CI was evaluated by receiver operating characteristic (ROC) curves.
The relative expression levels of peripheral blood miR-181c and miR-101 in the CI group were lower than those in the non-CI group (P < 0.05). The occurrence of CI was related to age, course of DM, AS location, time from onset to admission, HbA1c, TG, UA, and Hcy levels (P < 0.05). Logistic regression analysis showed that age, AS location, HbA1c, miR-181c, and miR-101 were related influencing factors of CI in patients with DM complicated with AS (P < 0.05). The results of ROC curves analysis showed that AUC, sensitivity, and specificity of miR-181c combined with miR-101 for predicting CI were 0.865, 73.17%, and 89.66%, respectively (P < 0.05).
The peripheral blood miR-181c and miR-101 are low expressed in patients with DM complicated with AS, and advanced age, intracortical AS lesions, increased HbA1c, and low expression of miR-181c and miR-101 are all independent risk factors for CI in patients with DM complicated with AS. Besides, the combined detection of miR-181c and miR-101 expression has a good diagnostic value for CI.
Diabetes mellitus (DM) is a glucose, lipid, and protein metabolic disorder syndrome caused by genetic, immune disorders, microbial infection, and other pathogenic factors, which can lead to increased cholesterol levels, decreased red blood cell deformability, and hypercoagulable state of organism, and promote thrombosis, thus easily inducing the occurrence of acute stroke (AS) [1, 2]. Some studies have found that DM microvascular complications are a high-risk factor for cognitive impairment (CI), which can cause neuronal degeneration and induce CI by inhibiting the insulin post-transport receptor signaling pathway, which has a serious impact on the work and life of patients [3, 4]. In recent years, microRNAs (miRNAs), which are widely present in brain tissue and have a regulatory effect on post-transcriptional protein expression, have become a research hotspot for their roles in neurogenesis, angiogenesis, and other cell biology [5]. MicroRNA-181c (miR-181c) is a member of the miR-181 family, and its overexpression increases reactive oxygen species production and affects mitochondrial genome protein coding [6]. Micro RNA-101 (miR-101) is sensitive to hypoxia, participates in cellular amino acid response, and plays an important regulatory role in neural tissue [7]. Previous studies have reported the changes of serum miR-181c levels in patients with acute cerebral infarction and the protective effect of miR-101 on cerebral ischemia-reperfusion injury, but there are relatively few studies reporting the changes of miR-181c and miR-101 levels in peripheral blood of patients with DM complicated with AS [8]. In addition, there is also a lack of research on the correlation between serum miR-181c and miR-101 levels and CI degree in patients with DM complicated with AS. In order to provide a molecular biological reference index for the prediction of cognitive dysfunction and early intervention planning in diabetes and patients, this study analyzed the relationship between the levels of miR-181c and miR-101 in peripheral blood and CI degree in patients with DM complicated with AS and the predictive value of the two on CI occurrence.
A retrospective analysis of 70 patients with DM complicated with AS admitted to our hospital from January 2019 to December 2021 was performed. Inclusion criteria were as follows: patient has a history of DM [9], patient met the diagnostic criteria for AS (the patient developed acute symptoms such as limb numbness and decreased muscle strength, and the appearance of cerebral infarction was confirmed by cranial CT or magnetic resonance imaging) and was admitted within 48 hours of developing AS [10], and patient's clinical medical records are complete. Exclusion criteria were as follows: patients with severe organ dysfunction or malignant tumor; patients with combined craniocerebral trauma, cerebrovascular malformation, or cerebral hemorrhage; patients with previous cognitive dysfunction; and patients with acute and chronic infectious diseases in various tissues and organs of the body. The patients were divided into 41 cases in the CI group and 29 cases in the non-CI group according to whether CI occurred or not, and the diagnosis [11] of CI was made by combining diagnostic criteria from the authoritative literature, the patient's history, physical examination and cognitive screening results.,
The general data of the included subjects were collected through the hospital electronic medical record system, including gender, age, education level, body mass index (BMI), combined underlying diseases (hypertension and coronary heart disease), smoking history, drinking history, DM duration, AS location (subtentorial, subcutaneous, and cortical), type of AS, time from onset to admission, National Institute of Health Stroke Scale (NIHSS) score, fasting blood glucose (FBG), glycated hemoglobin (HbA1c), triacylglycerol (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total bilirubin (TBIL), direct bilirubin (DBIL), uric acid (UA), homocysteine (Hcy), thyroid-stimulating hormone (TSH)), and cysteine (Cys).
In the morning of the next day after admission, 5 mL of fasting venous blood was collected from all the included subjects through the cubital vein and then anticoagulated and stored at low temperature. Total RNA was extracted by adding TRIzol and reverse transcribed into cDNA. miR-181c and miR-101 with cDNA as template were amplified, and PCR was used to perform fluorescence quantitative PCR reaction. The reaction conditions are as follows: 3 replicate wells for all samples, 95°C for 15 min, 94°C for 15 s, 60°C for 35 s, repeated 40 times. Using U6 as the internal reference, primer sequences are as follows: miR-181c upstream 5′-AACAUUCAACCUGUCGGUGAGU-3′, downstream 5′-UCACCGACAGGUUGAAUGUUUU-3′; miR-101 upstream 5′-CGTGCCAGACATGGACCTAT-3′, downstream 5′-CGGGGTAGGTGAAGACGAAG-3′; U6 upstream 5′-TCAGTTTGCTGCTGTTCTGGGTG-3′, downstream 5′-GGGTTGGCTGGAAAGGA-3′. The relative expression levels of miR-181c and miR-101 were calculated by 2-△△CT method. All steps were carried out in strict accordance with the instructions of each instrument and reagent.
SPSS 22.0 statistical software was used for data analysis, measurement data were expressed by (), differences between groups were expressed by two-sample independent t-test, count data were expressed by rate, and differences between groups were expressed by χ2 test. Univariate analysis and binary logistic regression were used to analyze the risk factors for the occurrence of CI in patients with DM complicated with AS. The receiver operator characteristic curve (ROC) was used to detect the diagnostic value of miR-181c and miR-101 expression in peripheral blood for the occurrence of CI in patients with DM complicated with AS. Two-sided P < 0.05 was considered to be statistically significant.
The relative expressions of miR-181c and miR-101 in peripheral blood of patients with DM complicated with AS in the CI group were significantly lower than those in the non-CI group (t = 8.534, 14.279, P < 0.05), as shown in Figure 1.
The occurrence of CI in patients with DM combined with AS was related to age, duration of DM, AS location, time from onset to admission, and levels of HbA1c, TG, UA, and Hcy (P < 0.05). There was no relationship with gender, education level, BMI, underlying disease, smoking history, drinking history, duration of DM, AS type, NIHSS score, and FBG, TC, LDL-C, HDL-C, TBIL, DBIL, TSH, and Cys levels (P > 0.05), as shown in Figure 2 and Table 1.
The difference variables that affected the cognitive function of patients with DM and AS were assigned and divided according to the mean value of all patients as the critical value, and the detection level was α = 0.05. The assignments of dependent and independent variables are shown in Table 2. Logistic regression analysis showed that age (OR = 2.784, P=0.038), AS location (OR = 2.697, P=0.024), HbA1c (OR = 2.751, P=0.031), miR-181c (OR = 2.759, P=0.024) = 0.032), and miR-101 (OR = 2.702, P=0.047) were related factors affecting the occurrence of CI in patients with DM complicated with AS, as shown in Table 2.
The ROC Table 3 results showed that the AUC of miR-181c and miR-101 in peripheral blood for predicting the occurrence of CI in patients with DM complicated with AS was 0.816 and 0.783, respectively, and the cutoff values were 0.91 and 1.01, respectively. Combined detection was used to predict the area under the curve of CI in patients with DM complicated with AS (area under curve, AUC) which was 0.865, and the sensitivity and specificity were 73.17% and 89.66%, respectively (P < 0.05), as shown in Figure 3 and Table 4.
DM patients often suffer from AS and other acute complications due to endocrine disorders, glycolipoprotein metabolism imbalance, and microvascular disease. Some studies have found that more than half of DM patients with AS can have CI, which seriously affects their quality of life [12, 13]. Therefore, finding simple and noninvasive biomarkers for early screening and diagnosis of cognitive impairment in DM patients with AS is of great significance to the clinical health management of DM patients. miRNA is a key regulatory molecule that plays an important role in the development and function of the nervous system [14]. This study mainly explored the relationship between the expression of miR-181c and miR-101 in peripheral blood and CI occurrence in patients with DM complicated with AS. The results of this study showed that the relative expressions of miR-181c and miR-101 in the peripheral blood of patients with DM combined with AS in the CI group were significantly lower than those in the non-CI group, indicating that the expressions of miR-181c and miR-101 in peripheral blood of patients with DM complicated with AS were downregulated, which might lead to the occurrence of CI. Studies by Lian et al. [15] and others found that CI was related to neuronal apoptosis and mitochondrial dysfunction, and studies by Meng et al. [16] found that miR-181c was downregulated in AS patients. MiR-181c is an miRNA widely expressed in the central nervous system, and it is often abnormally expressed in a variety of neurodegenerative and neuropsychiatric diseases with cognitive deficits. The abnormal expression of miR-181c can participate in the regulation of neuronal function by regulating mitochondrial histone coding [17]. The hippocampus is the key and basis for the formation of long-term memory and is closely related to cognitive functions such as learning and memory. miR-101 is extremely sensitive to hypoxia and highly expressed in synapses, and it participates in the proliferation and apoptosis of hippocampal neurons by negatively regulating the degradation of amyloid precursor in hippocampal neurons, and thus plays a neuroprotective role. miR-101 may participate in the regulation of hippocampal neuron apoptosis and regeneration through endogenous antioxidant pathways, affecting synaptic function and structure, and then regulating cognitive function in patients [18]. The results of this study showed that the occurrence of CI in patients with DM combined with AS was related to age, duration of DM, AS location, time from onset to admission, and levels of HbA1c, TG, UA, and Hcy, similar to the results of other studies, suggesting that cognitive function in patients with DM combined with AS may be related to factors such as age, duration of disease, damage to cerebral cortex, treatment delay, blood sugar control, and blood lipid level. Further multiple linear regression analysis was used to analyze the influencing factors of cognitive function in patients with DM complicated with AS. The results showed that age, AS location, HbA1c, miR-181c, and miR-101 were independent influencing factors on cognitive function of DM patients with AS, which indicated that the elderly, high HbA1c level, cortex, miR-181c, and miR-101 expression level were more likely to have CI. Elderly patients are often accompanied by decreased cerebral cortical cells and decreased cerebral perfusion, which increase the risk of CI. Cognitive function is generated and maintained in the complex system network of the brain. Current research generally believes that the brain functional area of cognitive function is located in the cerebral cortex, and the cerebral cortex damage is most closely related to CI in the site of AS occurrence [19]. The level of HbA1c reflects the glycemic control of patients. The toxic effect of hyperglycemia on the brain tissue of AS patients can lead to severe cerebral ischemia and hypoxia, which significantly increases the risk of CI [20]. miR-181c and miR-101 are involved in the occurrence and development of CI by regulating mitochondrial gene histone coding and neuronal apoptosis in the hippocampus in patients with DM combined with AS [6, 20]. In this study, ROC curve was used to evaluate the diagnostic value of peripheral blood miR-181c and miR-101 expression for CI in patients with DM complicated with AS. The results showed that the AUC of miR-181c and miR-101 in peripheral blood for predicting the occurrence of CI in patients with DM complicated with AS was 0.816 and 0.783, respectively. The AUC of combined detection for predicting the occurrence of CI in patients with DM complicated with AS was 0.865, with a sensitivity and specificity of 73.17% and 89.66%, respectively. This indicates that the combined detection of miR-181c and miR-101 in peripheral blood has high specificity in diagnosing the occurrence of CI in patients with DM complicated with AS and has the best diagnostic performance for CI. It suggested that the abnormal expression of miR-181c and miR-101 in peripheral blood could be used as a reliable indicator for predicting the occurrence of CI in patients with DM complicated with AS. In conclusion, advanced age, intracortical AS lesions, increased HbA1c, and low expression of miR-181c and miR-101 are all independent risk factors for CI in patients with DM complicated with AS. Besides, the combined detection of miR-181c and miR-101 expression in peripheral blood has a good diagnostic value for CI in patients with DM complicated with AS. The disadvantage of this study is that the number of selected samples is limited, and the correlation between the severity of CI and the expression of miR-181c and miR-101 in patients with DM complicated with AS has not been compared and analyzed. | true | true | true |
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PMC9546693 | 36213837 | Xin Jin,Haida Shi,Zhi Li,Huixing Li,Huanxian Ma,Xianjie Shi | Characterizing PTP4A3/PRL-3 as the Potential Prognostic Marker Gene for Liver Hepatocellular Carcinoma | 30-09-2022 | Background A large number of cancer-related deaths in the world can be attributed to liver hepatocellular carcinoma (LIHC). The purpose of this study is to explore protein tyrosine phosphatase type IV A member 3 (PTP4A3/PRL-3) as a new and reliable biomarker to predict the prognosis of LIHC and determine the potential therapeutic targets or drugs that can be used for treating LIHC. Methods We included three LIHC datasets with clinical information and expression profiles from public databases. The expression level of PTP4A3 was analyzed, and based on the results, the samples were divided into high- and low-expression groups. The Kaplan–Meier survival analysis method was used to determine the relationship between PTP4A3 and prognosis. The enrichment differences among the functional pathways associated with the high- and low-expression groups were determined using the gene set enrichment analysis (GSEA) method. Five methods were used to determine the differences among the tumor microenvironment in the low- and high-expression groups. The sensitivity of the low- and high-expression groups toward different drug treatment methods was predicted by analyzing the Tumor Immune Dysfunction and Exclusion (TIDE) scores and determining the biochemical half-maximal inhibitory concentration (IC50). Results The expression levels of the LIHC and adjacent samples were analyzed, and it was observed that the expression level of PTP4A3 in tumor tissue was significantly higher than the expression level of the same gene in the adjacent samples. It was also inferred that it might be a cancer-promoting gene. It was concluded that high-expression results in a significantly poor prognosis. The high-expression group was significantly enriched in the tumor-related pathways, such as the PI3K-AKT signaling pathway. In addition, the results obtained by conducting immune infiltration analysis revealed a significant positive correlation between some immune scores and the gene PTP4A3. The drug KIN001−135 and gene PTP4A3 were also found to correlate positively with each other. CP466722, Pyrimethamine, AKT inhibitor VIII, Embelin, Cisplatin, QS11, Bexarotene, and Midostaurin negatively correlated with PTP4A3 associated with the three datasets. Moreover, the drugs Cisplatin, QS11, Midostaurin, and CP466722 were more sensitive toward the high-expression group than the low PTP4A3 expression group. Significant differences were observed in these cases. Conclusion PTP4A3/PRL-3 is potentially associated with the progression, metastasis, and invasion of LIHC. The prognosis of LIHC patients is negatively impacted by the high-expression levels of the gene. The results indicate that PTP4A3/PRL-3 is an important prognostic factor for LIHC and is a new potential prognostic detection target. The discovery of the 8 drugs that were negatively associated with PTP4A3 provided a new direction that can be developed in the future for the treatment of LIHC. | Characterizing PTP4A3/PRL-3 as the Potential Prognostic Marker Gene for Liver Hepatocellular Carcinoma
A large number of cancer-related deaths in the world can be attributed to liver hepatocellular carcinoma (LIHC). The purpose of this study is to explore protein tyrosine phosphatase type IV A member 3 (PTP4A3/PRL-3) as a new and reliable biomarker to predict the prognosis of LIHC and determine the potential therapeutic targets or drugs that can be used for treating LIHC.
We included three LIHC datasets with clinical information and expression profiles from public databases. The expression level of PTP4A3 was analyzed, and based on the results, the samples were divided into high- and low-expression groups. The Kaplan–Meier survival analysis method was used to determine the relationship between PTP4A3 and prognosis. The enrichment differences among the functional pathways associated with the high- and low-expression groups were determined using the gene set enrichment analysis (GSEA) method. Five methods were used to determine the differences among the tumor microenvironment in the low- and high-expression groups. The sensitivity of the low- and high-expression groups toward different drug treatment methods was predicted by analyzing the Tumor Immune Dysfunction and Exclusion (TIDE) scores and determining the biochemical half-maximal inhibitory concentration (IC50).
The expression levels of the LIHC and adjacent samples were analyzed, and it was observed that the expression level of PTP4A3 in tumor tissue was significantly higher than the expression level of the same gene in the adjacent samples. It was also inferred that it might be a cancer-promoting gene. It was concluded that high-expression results in a significantly poor prognosis. The high-expression group was significantly enriched in the tumor-related pathways, such as the PI3K-AKT signaling pathway. In addition, the results obtained by conducting immune infiltration analysis revealed a significant positive correlation between some immune scores and the gene PTP4A3. The drug KIN001−135 and gene PTP4A3 were also found to correlate positively with each other. CP466722, Pyrimethamine, AKT inhibitor VIII, Embelin, Cisplatin, QS11, Bexarotene, and Midostaurin negatively correlated with PTP4A3 associated with the three datasets. Moreover, the drugs Cisplatin, QS11, Midostaurin, and CP466722 were more sensitive toward the high-expression group than the low PTP4A3 expression group. Significant differences were observed in these cases.
PTP4A3/PRL-3 is potentially associated with the progression, metastasis, and invasion of LIHC. The prognosis of LIHC patients is negatively impacted by the high-expression levels of the gene. The results indicate that PTP4A3/PRL-3 is an important prognostic factor for LIHC and is a new potential prognostic detection target. The discovery of the 8 drugs that were negatively associated with PTP4A3 provided a new direction that can be developed in the future for the treatment of LIHC.
The most common type of primary liver cancer is liver hepatocellular carcinoma (LIHC). The incidence and mortality rate of LIHC hold on a high level especially in ages over than 40 [1] and are closely related to advanced liver disease [2–5]. This malignancy is considered the primary cause of death in patients with liver cirrhosis. Liver cirrhosis is also an important indicator that is used for monitoring and screening the occurrence of LIHC [6–8]. Although immense progress has been made in the field of surgery and medicine, LIHC is one of the most common causes of tumor-related deaths in the world. Most patients suffering from LIHC are diagnosed at an advanced stage of the disease. Patients at an advanced stage of LIHC cannot be treated following the process of surgical resection [5]. The survival rate recorded for most of the patients treated surgically was found to be poor [9–11]. It has been observed that there is a lack of useful prognostic markers for the prognosis prediction of LIHC. Patients who are at a similar tumor stage or are characterized by a similar pathological structure may have a significantly different prognosis, and this can be attributed to individual differences [12, 13]. Therefore, it is important to explore new and reliable biomarkers to predict the prognosis of LIHC. Apart from the phosphorylation-related enzyme protein tyrosine kinase [14], the phosphorylation-related enzyme protein tyrosine phosphatase (PTP) is a suitable therapeutic target for cancer [15]. It also significantly affects the processes of tumorigenesis and progression [15]. It has been widely reported that PTPs are potential therapeutic targets [16–18]. However, the amount of data available on the role of PTPs in LIHC is lesser than the amount of data available on the role of protein tyrosine kinases (PTKs). Various PTK inhibitors, such as sorafenib and regorafenib, are prescribed to patients in their advanced stages of LIHC [19]. However, high survival rates and satisfactory results have not been obtained using these drugs. PTPs also regulate the process of protein phosphorylation. An imbalance in the levels of PTKs (or PTPs) can result in the abnormal phosphorylation of various downstream proteins. Therefore, we focused on the therapeutic potential of PTPs for the treatment of LIHC. The protein tyrosine phosphatase 4A (PTP4A) family is commonly known as the phosphatases of regenerating liver (PRL). This family consists of three members of phosphatases and plays an important carcinogenic role in various human cancers. The analysis of literature reports reveals that multiple PRL inhibitors have been reported over the years [20]. Therefore, it is important to understand the role of PRLs in the incidence and progression of LIHC. Previous studies have shown that PRL-1 is overexpressed in LIHC and promotes LIHC cell migration and invasion through endothelial mesenchymal transformation (EMT) [21]. It has also been reported that the prognosis of patients is negatively affected by the upregulation of PRL-3 in LIHC [22, 23]. However, comprehensive information on the molecular mechanism associated with PRL-3 (also known as PTP4A3, hereinafter collectively referred to as PTP4A3) that promotes the development of LIHC is not yet available. We first analyzed the expression profile and prognosis based on the mRNA expression levels and clinical data corresponding to patients suffering from hepatocellular carcinoma. The relevant data were obtained from the public datasets. We studied the differential genes in the high- and low-expression groups of PTP4A3 and analyzed the function of the gene. In addition, we also compared and analyzed the immune microenvironment of different PTP4A3 expression levels in LIHC. The results revealed that some immune scores correlated positively with PTP4A3. Finally, we identified 8 drugs that negatively correlated with PTP4A3. The results confirm the carcinogenic effect of PRL-3 in LIHC and help identify new targets and treatment methods for LIHC.
The TCGA-LIHC dataset (hereinafter referred to as the TCGA dataset) was originally derived from the Cancer Genome Atlas (TCGA) database. It was downloaded from the UCSC Xena data portal. The database contained RNA sequencing (RNA-seq) data for LIHC and normal samples. It also contained clinical information and somatic mutation data. The TCGA-LIHC dataset (hereinafter referred to as TCGA dataset) was originally derived from The Cancer Genome Atlas (TCGA) database. It was downloaded from the University of California Santa Cruz (UCSC) Xena data portal (https://xenabrowser.net/). The dataset contained RNA sequencing (RNA-seq) data corresponding to LIHC and normal samples. It also contained clinical information and somatic mutation data. For RNA-seq data, the data in the fragments per kilobase of transcript per million mapped reads (FPKM) format were converted to the transcript per million (TPM) format. Following this, log2 conversion was realized. The downloaded somatic mutation data contained information on single nucleotide variations (SNVs) and copy number variations (CNVs). The SNV data were processed using MuTect tool, and the CNV data were processed using the Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm. Data on methylation was downloaded from the LinkedOmics data portal (https://www.linkedomics.org/login.php). Finally, 365 LIHC samples were identified from the TCGA dataset. The chip data (corresponding to LIHC) were obtained from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/). The GSE14520 dataset was considered, which contained data associated with the expression profile and survival rates. The chip probe was converted into gene symbols. The samples lacking clinical follow-up information, survival time, status, and expression profile data were removed, and 221 LIHC samples were finally included in the studies. The LIHC expression data and survival data for ICGC-LIRI-JP (also known as HCCDB18) were downloaded from the HCCDB website, which was accessed through https://lifeome.net/database/hccdb/download.html. Finally, 203 LIHC samples were included to conduct the studies.
The TCGA dataset was considered, and the differentially expressed genes (DEGs) in the high- and low-expression groups of PTP4A3 were identified using the limma package [24]. The genes were filtered based on the threshold false discovery rate (FDR) <0.05 and log2(fold change, FC) >1.5. We analyzed different datasets and used survminer (R-package; accessed through https://CRAN.R-project.org/package=survminer) to obtain the best cut-off values for the genes. The samples were divided into high- and low-expression groups based on the best cut-off values, and the Kaplan–Meier (KM) survival curve was generated.
We used “GSEA” [25] for pathway analysis to study the pathways associated with different molecular subtypes. We used the GSEA method using all candidate gene sets in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway provided by the MSigDB database to conduct the studies [26]. The input file for GSEA contains the data on the expression profile, and the sample label marks the sample as a high group or a low group. Further, we used the Gene Ontology (GO) function enrichment analysis and KEGG pathway analysis methods to study the differential genes in the LIHC groups using WebGestaltR (v0.4.2; R software) [27]. Subsequently, the results of the “GSEA” pathway analysis were filtered under conditions of P < 0.05 and FDR <0.25.
Convolution and deconvolution are common algorithms in the field of deep learning. Each sample is a mixture of multiple immune cells. The linear regression method is used to fit the relationship between the composition and expression of each immune cell and the final mixture. The expression characteristics of each immune cell are extracted using the deconvolution algorithm. Methods (based on the expression characteristics) to realize the deconvolution of the cell mixtures include the Tumor IMmune Estimation Resource (TIMER2) [28, 29]. TIMER2 is one of the most commonly used immune infiltration analysis methods in the field of bioinformatics analysis. The microenvironment cell populations-counter (MCP-counter; R package) [30] can be used to quantify the absolute abundance of 2 stromal cells and 8 immune cells present in heterogeneous tissues. The package is used to analyze the normalized transcriptome data to arrive at the results. The score presents the degree of infiltration in the immune microenvironment, and the abundance of cells cannot be compared with each other. The Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) [31] package cannot be used to score specific immune cell infiltration but can be used to only analyze the purity of the immune cells and tumor cells and the abundance of stromal cells. Estimating the Proportion of Immune and Cancer cells (EPIC) [32] package can be used to analyze the levels of infiltration of the 8 kinds of immune cells (cancer-associated fibroblasts (CAFs), B cells, CD8 + T cells, CD4 + T cells, natural killer (NK) cells, endothelial cells, and macrophages) based on the expression data. The algorithm associated with EPIC uses the constrained least square regression method to explicitly incorporate nonnegative constraints into the deconvolution problem. The algorithm is also used to meet the criterion that the sum of all cell fractions in each sample should be less than one. Under these conditions, based on the operation results, we can directly analyze the differences among various cell components of the sample. For example, a significant decrease in the proportion of B cells, CD8 + T cells, and NK cells indicates that the extent of immune response in the tissue gets inhibited, the recruitment process of immune cells gets hindered, and the tumor immunity gets inhibited. The increasing number of CAFs also contributes the immunosuppressive environment and the development tumors. Finally, we used EPIC [32], MCP-counter [30], TIMER2 [28, 29], ESTIMATE [31], and ssGSEA [25] to analyze the immune infiltration levels of LIHC and evaluate the tumor immune scores of the samples. In short, EPIC, MCP-counter, TIMER, and ssGSEA can be used to determine the composition of different immune cells. The ESTIMATE package can be used to evaluate tumor purity, stromal cell score, immune cell score, etc., for each sample. The expression of a single gene can be correlated with these immune invasion values. This method considers the marker genes corresponding to different immune cells as the gene set and uses an algorithm similar to GSEA to evaluate whether the highly expressed genes in the sample are enriched in the gene set of different immune cells.
The Tumor Immune Dysfunction and Exclusion (TIDE) [33] analysis method can be used to identify biomarkers for the prediction of the efficacy of immune checkpoint inhibitors or drugs by comprehensively analyzing hundreds of different tumor expression profiles. The sensitivity of immune checkpoints can be determined by obtaining the TIDE score following the process of TIDE analysis. In addition, to estimate the risk score of predicting the molecular drug response, we used the “pRRophetic” R software package [34] to evaluate half of the maximum inhibitory concentration (IC50) values of the drugs based on the expression profile obtained from different datasets. Following this, we determined the correlation between these drugs and the gene (PTP4A3) in different datasets.
All statistical analysis and visualization methods were performed using R software (4.1.0). Clinical features were expressed as mean ± standard deviation or n (%). The Benjamini–Hochberg method was used to control the FDR value. Adjusted P values below 0.05 were considered significant. The Pearson correlation analysis method was used to correlate the identified features and clinical parameters.
We first assessed the expression level of PTP4A3 in tumor and normal (tumor-adjacent) samples. A significantly high differential expression level was observed between the two groups. The PTP4A3 expression levels of the tumor samples in all three independent datasets (TCGA, HCCDB18, and GSE14520) were significantly high (Figures 1(a)–1(c)), indicating that PTP4A3 could potentially play an oncogenic role in LIHC. To understand whether the level of PTP4A3 expression was associated with overall survival, we classified LIHC samples into two groups based on the optimal cut-off value of the PTP4A3 expression level. The optimal cut-off value was determined following the KM survival analysis method. The results revealed that the two groups (in the three datasets) were characterized by different overall survival rates (Figures 1(d)–1(f)). A significant difference was observed for the TCGA and GSE14520 datasets (P = 0.016 and P = 0.0011, respectively), while a significant difference was not observed for the HCCDB18 dataset (P = 0.2). There were significant differences between the TCGA and GSE14520 datasets. The groups with high PTP4A3 expression levels exhibited poor prognoses. LIHC samples were divided into two groups based on the optimal cut-off for PTP4A3. The high-expression group of PTP4A3 was characterized by a higher risk than the low-expression group, indicating that PTP4A3 was a risk factor for LIHC.
We further analyzed the samples and found that the mutation frequency of PTP4A3 in LIHC was 1%. Following this, we mapped the 10 genes that were characterized by the highest mutation frequency in the low- and high-expression groups. The results revealed that the mutation frequencies corresponding to TTN, TP53, CTNNB1, MUC16, ALB, RYR2, and other genes in the high-expression group were higher than the mutation frequencies of the genes belonging to the low-expression group (Figure S1A). It was also observed that PTP4A3 mutated in the high-expression group but not in the low-expression group (Figure S1B). Subsequently, we analyzed the differences in the TMB associated with the low- and high-expression groups. A significant difference was not observed (Figure S1C). We also analyzed the amplification and deletion processes associated with PTP4A3 and compared the expression levels of PTP4A3 in the different groups. It was found that the group with amplified PTP4A3 (gain group) was characterized by the highest expression level, which was significantly higher than diploid group (Figure S1D). The correlation between the expression of PTP4A3 and the degree of methylation was determined and plotted. The results revealed that the expression of PTP4A3 negatively correlated with the methylation of PTP4A3 (Figure S1E), suggesting that the higher methylation level corresponded to lower expression level.
The significantly enriched pathways in the low- and high-expression groups were analyzed using the GSEA method. The results revealed that, in the TCGA dataset, angiogenesis, EMT, hypoxia, and other pathways that were associated with the invasion and metastasis processes were significantly enriched in the high-expression groups. This indicates that the high-expression level of PTP4A3 can be potentially associated with the processes of metastasis and invasion (Figure 2). For the TCGA dataset, we obtained 2212 DEGs for the high- and low-expression groups of PTP4A3. Of these, 1831 genes were upregulated, and 381 genes were downregulated. For the downregulated genes associated with LIHC, several significant GO function annotation entries were identified (FDR <0.05). Of these, 1093 items with a significant difference in biological process (BP) were annotated (Figure S2A), 158 items with significant differences in cellular component (CC) were annotated (Figure S2B), and 103 items with significant differences in molecular function (MF) were annotated (Figure S2C). For the KEGG pathways enriched by the downregulated expression genes (FDR <0.05), 59 were annotated (Figure S2D). Among them, the ECM−receptor interaction pathways, TNF signaling pathway, pathways associated with cancer, PI3K-AKT signaling pathway, and other tumor-related pathways were significantly enriched. For the upregulated genes associated with LIHC, several significant GO function annotation entries were identified (FDR <0.05), of which 417 entries with significant differences in BP were annotated (Figure S3A), 30 entries with significant differences in CC were annotated (Figure S3B), and 96 entries with significant differences in MF were annotated (Figure S3C). The upregulated genes associated with LIHC were enriched in the case of the KEGG pathways (FDR <0.05), and 37 entries were annotated (Figure S3D). The pathways associated with retinol metabolism, cholesterol metabolism, metabolism of xenobiotics (in the presence of cytochrome P450), tryptophan metabolism, and other metabolic events were significantly enriched.
We identified 5 types of genes from literature reports [35]. These are associated with chemokine, immunostimulator, immunoinhibitor, major histocompatibility complex (MHC), and receptor. The correlation between PTP4A3 and these genes was analyzed for different datasets. The results revealed that PTP4A3 showed a significant positive correlation with these 5 types of genes associated with the TCGA and HCCDB18 datasets. It was also observed that there was no significant correlation between PTP4A3 and most of these 5 types of genes associated with the GSE14520 dataset (Figure 3). The differential expression levels of the 5 types of immune-related genes were analyzed by taking into consideration the different expression groups of PTP4A3 (Figures S4A–S4E). Most of the 5 different types of genes exhibited significant differences, and most of them were highly expressed in the high-expression group. EPIC, MCP-counter, TIMER, ESTIMATE, and ssGSEA were used to analyze the LIHC immune infiltration levels in different datasets. Following this, the correlation between the PTP4A3 expression levels and their scores was determined. The results revealed that the PTP4A3 expression level positively correlated with the immune scores (corresponding to the TCGA and HCCDB18 datasets) determined using different software systems. Most immune scores were not related to PTP4A3 in the GSE14520 dataset, while some immune scores correlated positively with PTP4A3. TIMER was used for the evaluation of CD4 T cells and B cells, and EPIC was used for the evaluation of the CD4 T cells. Three immune scores were determined using ESTIMATE, the MCP-counter software was used for the evaluation of T cells, and the ssGSEA method was used for the evaluation of the activated CD4 T cells, regulatory T cells, NK T cells, activated B cells, etc. The differential expression of immune scores obtained using EPIC, MCP-counter, TIMER, ESTIMATE, and ssGSEA for the different expression groups of PTP4A3 was analyzed (Figures S5A–S5C). We observed that the immune cell enrichment score corresponding to the high-expression group was generally higher than that of the low-expression group. The results agreed well with the results obtained following the correlation analysis method. We continued to analyze the correlation between PTP4A3 and the 5 software-derived immune scores. Significant correlations between immune scores and PTP4A3 expression were shown in three datasets, among which is the HCCDB18 dataset (Figure 4).
The results reveal that the expression of PTP4A3 correlates significantly with disease prognosis and the tumor microenvironment. This indicated that PTP4A3 could potentially play an important role in the development of LIHC. Therefore, we believe that PTP4A3 can be used as a potential drug target. The sensitivity of the low- and high-expression groups toward chemotherapeutic drugs, targeted drugs, and immunotherapeutic drugs was evaluated to validate this hypothesis. The correlation between the 52 drugs and PTP4A3 for different datasets was determined. It was observed that the 9 drugs correlated significantly with the PTP4A3 expression levels recorded for the three datasets (Figure 5(a), |R| > 0.15, P < 0.05). However, only KIN001−135 positively correlated with PTP4A3 expression in all three datasets (P < 0.0001). The 8 drugs (CP466722, Pyrimethamine, AKT inhibitor VIII, Embelin, Cisplatin, QS11, Bexarotene, and Midostaurin) correlated negatively with PTP4A3 in the case of all the three datasets. Next, the differences in the IC50 values of the 9 drugs associated with different PTP4A3 expression groups in different datasets were compared (student t-test, Figures 5(b)–5(d)). The results revealed that the drug KIN001−135 was more sensitive toward the low-expression group of PTP4A3(P < 0.001). Cisplatin, QS11, midostaurin, and CP466722 were more sensitive toward the high-expression group of PTP4A3 associated with the three datasets (P < 0.01). The differences in the effects of immunotherapy among the different expression groups of PTP4A3 belonging to different datasets were analyzed. The potential clinical effects of immunotherapy on the defined groups were assessed using TIDE (https://tide.dfci.harvard.edu/). An increase in the TIDE prediction score resulted in an increase in the possibility of immune escape. This indicated that patients were less likely to benefit from immunotherapy under these conditions. We determined the correlation between PTP4A3 and TIDE, dysfunction, exclusion, myeloid-derived suppressor cells (MDSSs), CAFs, and tumor-associated macrophage (TAM).M2 scores obtained for different datasets (Figure 6). The results revealed that PTP4A3 exhibited a significant positive correlation with TIDE, exclusion, MDSC, and CAF when different datasets were studied. This indicates that an increase in the expression level of PTP4A3 can potentially reduce the positive effects of immunotherapy on patients. We compared the differences in the TIDE scores of different PTP4A3 expression groups belonging to different datasets (Figures 7(a)–7(c)). Different datasets were studied, and it was observed that the TIDE score corresponding to the high-expression group was significantly higher than the TIDE score recorded for the low-expression group. This indicated that the low-expression group was more responsive toward immunotherapy than the high-expression group. In addition, the exclusion and CAF scores corresponding to the low-expression group were lower than those of the high-expression group.
It has been previously reported that PTP4A3 plays a variety of roles in the process of cancer metastasis. Cell differentiation, invasion, proliferation, and metastasis are induced by PTP4A3 when a series of intracellular signaling pathways are activated [36–38]. Moreover, the upregulation of PTP4A3 in LIHC exerts a negative effect on the patients' prognosis [22, 23]. It also promotes the progress of LIHC [39]. Comprehensive studies on PTKs that function as biomarkers and PTPs that function as tumor markers have not been conducted to identify potential therapeutic targets or drugs that can be used to treat LIHC. Reports in the field are rare, and further studies should be conducted to gain in-depth knowledge. We used three different public datasets for comprehensive expression and drug sensitivity analysis. The results obtained by conducting a comprehensive analysis revealed that PTP4A3 was a new and reliable potential marker that could predict the prognosis of LIHC. The corresponding targets and drug candidates could also be identified. We analyzed the TCGA, GEO, and HCCDB18 datasets and observed that the expression levels of PTP4A3 in tumors were significantly higher than the expression levels recorded for the adjacent samples. This indicated that PTP4A3 might be a cancer-promoting gene in LIHC. The results agreed well with previously reported results [36]. It was also observed that poor prognosis was associated with high-expression levels of PTP4A3. The results revealed that PTP4A3 dictated patient survival and was associated with poor prognosis. It has been previously reported [22–40] that TGFB1 can be used as a downstream molecule of PTP4A3. In other words, the process of TGF-β signal transduction mediates the PTP4A3-induced FAK activation process. PI3K/AKT and p38 pathways mediate the PTP4A3-induced TGFB1 expression and subsequent FAK activation processes, which in turn stimulate the activation of the PI3K/AKT and p38 pathways. This results in the generation of a PRL-3-triggered AKT/p38/TGFB1/FAK positive feedback loop. The results agree well with the results reported herein. The downregulated gene set in the TCGA dataset was significantly enriched in pathways associated with cancer, PI3K-AKT signaling pathway, TNF signaling pathway, and other related pathways. The AKT inhibitor VIII negatively correlated with PTP4A3 in all three datasets. This was in line with the expectations. The results confirm and validate the reliability of the reported method. The results obtained by conducting GSEA analysis revealed that the high-expression group was significantly enriched in pathways associated with angiogenesis, epithelial mesenchymal transition, hypoxia, invasion, and metastasis, indicating that the high-expression levels of PTP4A3 could potentially be associated with the processes of metastasis and invasion. The combined results reveal that the influence of PTP4A3 may result in a poor prognosis, and this can be attributed to the promotion of metastasis and invasion. It has also been reported that PTP4A3 exhibits significant positive correlation genes associated with chemokine, immunostimulator, immunoinhibitor, MHC, and receptor [35]. The results from immune infiltration analysis revealed that the expression of PTP4A3 correlated positively with the software-derived immune scores of some of the immune cells. It has been reported by some researchers [38] that PTP4A3 can upregulate the expression of the chemokine ligand 26 (CCL26) and participate in cell migration. The results from immunohistochemistry (IHC) analysis revealed that the levels of PRL-3 and CCL26 correlated positively with each other, and the levels increased in stages III and IV of colorectal cancer. This could be attributed to the poor prognosis of patients suffering from colorectal cancer. PTP4A3 can potentially function as a potential prognostic marker in the case of LIHC (similar to the case of colorectal cancer). It promotes the processes of invasion and metastasis associated with LIHC by upregulating CCL26 and inducing the process of TAM infiltration. The results obtained by analyzing drug sensitivity revealed that CP466722, pyrimethamine, AKT inhibitor VIII, embelin, cisplatin, QS11, bexarotene, and midostaurin correlated negatively with PTP4A3 associated with the three datasets. AKT inhibition can be considered an attractive therapeutic intervention for LIHC. For example, AKT inhibitor VIII is identified as a drug, which can intervene in LIHC by inhibiting the upstream kinase of AKT signal transduction. The LIHC cell line responds to the AKT inhibitor via the process of apoptotic cell death. The process is independent of the AKT activation state [41]. Among all the drugs, Embelin is an active ingredient that is used in the preparation of traditional herbal medicine. It is used to treat a variety of diseases, such as cancer. It has been reported that Embelin, as a drug delivery system in the liver, is a new candidate drug that can be used for the clinical treatment of advanced hepatocellular carcinoma [42]. Cisplatin can also be used to treat LIHC [43]. These results confirm the reliability of the reported analytical method. CP466722 has been studied as an inhibitor of ataxia telangiectasia mutated (ATM) kinase [44, 45]. Following the inhibition of ATM, the processes of EMT and tumor metastasis in drug-resistant lung cancer cells are inhibited [44]. In addition, it has also been reported that the ATM inhibitor CP466722 strongly binds to ALK2. A new chemical type for the discovery of drugs for the treatment of progressive ossifying fiber dysplasia was also identified [45]. ALK2 is a serine–threonine kinase receptor (STKR), which belongs to the tyrosine-like kinase (TKL) family. The PI3K-AKT pathway associated with PTP4A3 is mediated by the processes of serine or threonine phosphorylation associated with a series of downstream substrates. CP466722 has not been previously reported in liver cancer. Therefore, the results reported herein can help provide a platform for the development of drugs that can be used to treat liver cancer. Further experiments should be conducted to validate the results reported herein. The results reveal whether PTP4A3 can function as a potential therapeutic target for liver cancer. The impact of the 8 drugs on the processes of tumor progression and the prognosis of patients with liver cancer have also been reported. The effect of immunotherapy on patients suffering from liver cancer needs to be further studied. The results revealed that when different datasets were considered, the TIDE score corresponding to the-high expression group of PTP4A3 was significantly higher than the TIDE score corresponding to the low-expression group. This indicates that the low-expression group may be more responsive toward immunotherapy. The results from a phase 1 trial underway in Singapore reveal that PRL3-zumab is well tolerated by animals suffering from cancer. The relevant data can be obtained from https://clinicaltrials.gov/ct2/show/NCT03191682?term=PRL-3&rank=1. The safety of using this drug and the preclinical efficacy of PRL3-zumab (studied using an orthotopic tumor model) make the PRL3-zumab-based therapeutic method a safe and effective targeted therapy method. PTP4A3/PRL-3 was identified as one of the molecules that were overexpressed in LIHC tissues. PTP4A3/PRL-3 can potentially affect the processes of invasion, progression, and metastasis associated with LIHC. It was observed that the high-expression levels negatively affected the prognosis of LIHC patients. The results indicated that PTP4A3 should be considered as an important prognostic factor in the case of LIHC. More attention should be paid to the abnormality of PTP4A3 phosphorylase to gauge the progress of LIHC. It should be considered a potential target for the treatment of LIHC to conduct further research. The results reported herein can potentially help in the development of clinical trials, exploration of treatment methods in preclassified patient groups, and improvement in the survival rate of patients suffering from this fatal disease.
Overall, the results reveal that the PTP enzyme significantly affects the progression of LIHC. The results from integrated differential expression and correlation analysis revealed that the high-expression levels of PTP4A3 indicate a poor prognosis. This suggests that the immune scores corresponding to some immune cells correlate positively with the expression of PTP4A3. The drug sensitivity analysis method was used to identify 9 potential liver cancer intervention methods and treatment drugs associated with PTP4A3. In conclusion, PTP4A3 should be considered as a potential LIHC prognostic detection target and treatment direction. | true | true | true |
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PMC9546798 | Leila Sabour Takanlou,Gulsah Cecener,Maryam Sabour Takanlou,Hulya Ozturk Nazlioglu,Havva Tezcan Unlu,Ozgen Isik,Unal Egeli,Berrin Tunca,Erdem Cubukcu,Sahsine Tolunay,Mustafa Sehsuvar Gokgoz | Correlation between Ubiquitin E3 Ligases (SIAHs) and Heat Shock Protein 90 in Breast Cancer Patients | 01-08-2022 | Breast cancer,Invasive ductal carcinoma,Ubiquitin-protein ligases | Background: Breast cancer is a heterogeneous disease and differences in the expression levels of the ER, PR, and HER2 the triplet of established biomarkers used for clinical decision-making have been reported among breast cancer patients. Furthermore, resistance to anti-estrogen and anti-HER2 therapies emerges in a considerable rate of breast cancer patients, and novel drug therapies are required. Several anomalous signaling pathways have been known in breast cancer have been known; heat shock protein 90 (HSP90) is one of the most plenty proteins in breast cells. The family of ubiquitin ligases such as SIAH1 and SIAH2 is known to specifically target misfolded proteins to the proteasome; also, they have been illustrated to play a role in RAS signaling and as an essential downstream signaling component required for EGFR/HER2 in breast cancer. Methods: The expression of SIAH2, HSP90, and HER2 was assessed by quantitative Real-Time PCR in 85 invasive ductal carcinoma breast tumor samples at Uludag University Hospital in Turkey during the years 2018–2019, and its association with the clinicopathologic variables of patients was evaluated. Results: HSP90, SIAH1, and SIAH2 were significantly (P=0.0271, P=0.022, and P=0.0311) upregulated tumor tissue of patients with breast cancer. Moreover, this study observed a significant association between the high expression of SIAH2/HSP90 with ER status, high expression of HSP90 with Recurrence/Metastasis, and high expression of SIAH2 with Ki-67 proliferation index. Conclusion: The HSP90 and SIAH2 expressions play a significant role in breast cancer development by combining the experimental and clinical data obtained from the literature. | Correlation between Ubiquitin E3 Ligases (SIAHs) and Heat Shock Protein 90 in Breast Cancer Patients
Breast cancer is a heterogeneous disease and differences in the expression levels of the ER, PR, and HER2 the triplet of established biomarkers used for clinical decision-making have been reported among breast cancer patients. Furthermore, resistance to anti-estrogen and anti-HER2 therapies emerges in a considerable rate of breast cancer patients, and novel drug therapies are required. Several anomalous signaling pathways have been known in breast cancer have been known; heat shock protein 90 (HSP90) is one of the most plenty proteins in breast cells. The family of ubiquitin ligases such as SIAH1 and SIAH2 is known to specifically target misfolded proteins to the proteasome; also, they have been illustrated to play a role in RAS signaling and as an essential downstream signaling component required for EGFR/HER2 in breast cancer.
The expression of SIAH2, HSP90, and HER2 was assessed by quantitative Real-Time PCR in 85 invasive ductal carcinoma breast tumor samples at Uludag University Hospital in Turkey during the years 2018–2019, and its association with the clinicopathologic variables of patients was evaluated.
HSP90, SIAH1, and SIAH2 were significantly (P=0.0271, P=0.022, and P=0.0311) upregulated tumor tissue of patients with breast cancer. Moreover, this study observed a significant association between the high expression of SIAH2/HSP90 with ER status, high expression of HSP90 with Recurrence/Metastasis, and high expression of SIAH2 with Ki-67 proliferation index.
The HSP90 and SIAH2 expressions play a significant role in breast cancer development by combining the experimental and clinical data obtained from the literature.
Breast cancer is a heterogeneous disease with morphologic and genetic alterations varied that pose a challenge to its diagnosis and treatment. Two classifications of breast carcinoma are ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC), in which IDCs with wide morphological variation are a heterogeneous group of breast cancers (1). In recent times, the detection of cancer biomarkers has become a focal point of cancer research, and biomarkers play a requisite role in the administration of invasive breast cancer patients (2, 3). IHC4 score (ER, PR, HER2, and Ki-67) is a rapid, economical breast cancer prognosis (4). HER2 (human epidermal growth factor receptor 2) is an important prognostic factor of breast cancer, and HER2 overexpression is correlated with aggressive tumors, lower prognosis, and response to chemotherapy (5–7). Trastuzumab is routinely used at the early stages of adjuvant and neoadjuvant therapy in HER2-positive breast cancer (8). There are various factors related to resistance to anti-HER2 therapies, such as loss of HER2 amplification, p95HER2 or mutations in the extracellular domain, crosstalk of HER2 with the PI3K/Akt/mTOR, and the estrogen receptor pathway (9, 10). Furthermore, high HSP90 expression may regulate the HER2 activation and offering the main mechanism of resistance to HER2 inhibitors (11). So far, more than 200 HSP90 clients have been recognized, inclusive of key regulators in signal transduction and cell cycle control, steroid hormone receptors, and tyrosine and serine/threonine kinases (12, 13). The HSP90 expression has been correlated with high ER levels, high HER2 levels, lymph node status, size of tumors, and reduced survival in breast cancer; HSP90 overexpression is a feature of IDC breast cancers (14–16). HSP90 inhibitors may enhance the effects of anticancer agents that target client proteins of HSP90 such as HER2 (11). HSP90 inhibitors such as tanespimycin reduced ER in ER-positive tamoxifen-sensitive and ER-positive tamoxifen-resistant breast cancer cells and repressed the growth of breast tumors. Moreover, the combining inhibitors of HSP90 (Tanespimycin and Ganetespib) and trastuzumab expanded ubiquitinylation and reduce the expression of HER2 in HER2-overexpressed breast cancer cell lines (17). Conclusively, the overexpression of HSP90 has been exhibited to be associated with opposite clinical outcomes, further validating HSP90 as a target in breast cancer (15). The first step in the activation of Ubiquitin occurs through a thioester bond catalyzed by an Ubiquitin-activating (E1) enzymes prior transfer to the Ubiquitin-conjugating (E2) enzymes. The final step in transmission of ubiquitin to the cellular targets, Ubiquitin-conjugating (E2) enzymes react with E3 ubiquitin ligases and become targets for the proteasome (18, 19). The Ubiquitylation–proteasome system is major intracellular misfolded protein degradation pathways, (20, 21) and it works with molecular chaperones in this process (22, 23). Moreover, the ubiquitin ligase functions have been demonstrated in the degradation of ErbB2/HER2 (HSP90 client protein kinases) following inhibition of HSP90 (24). Seven In Absentia Homolog (SIAH) proteins are E3 ubiquitin ligase, and SIAHs are involved in cancers such as prostate cancer, leukemia, and breast cancer. Furthermore, SIAH has been proposed as a beneficial prognostic biomarker that predicts DCIS progression to IDC breast cancer (25, 26). There are two homologs for SIAH in humans; SIAH1 and SIAH2 play roles in different pathways inclusive of the hypoxic response, inflammation, those involved in response to DNA damage, RAS signaling, estrogen signaling, and EGFR/HER2 signaling (26–29). As well as SIAHs are involved in cytokine signaling modulating the epithelial to mesenchymal transition (EMT) (30). Here we employed a quantitative PCR method to detect HER2, SIAH2, and HSP90 gene expressions in 85 formalin-fixed and paraffin-embedded (FFPE) breast cancer tissue samples from breast cancer patients.
We examined 85 formalin-fixed, paraffin-embedded (FFPE) cancer tissues with invasive ductal breast carcinoma and normal tissues at Uludag University Hospital in Turkey during the years 2018–2019. The usage of breast cancer tissues for molecular analysis was ratified under the number (BUU 2018-14/26) by the Ethics Committee of the Faculty of Medicine of the Bursa Uludag University.
Total RNA was extracted from the tissue samples including tumor and adjacent normal tissues of the same patient using OMEGA reagent (FFPE RNA Kit, Omega, Germany) according to the manufacturer’s instructions.
Reverse transcription were performed by the TaqMan High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems™, USA). The 20 μL reverse transcription reaction contained dNTPs, MultiScribe Reverse Transcriptase (50 U/μL), 10x Reverse Transcription Buffer, Random Primer, nuclease-free water, and 10 μL RNA. The reaction was carried out at 4 steps (Step 1: 25 °C, 10 min; Step 2: 37 °C, 120 min; Step 3: 85 °C, 5 min; Step 4: 4 °C, ∞) on Thermal Cycler (Bio-Rad, California, USA). In the present study, the reaction mix for each sample used of TaqMan, ®Gene Expression, in a volume of 20 μL including in 4 μL preamplified of cDNA (50 ng), 1 μL of TaqMan gene expression assay, 5 μL of dH2O, and 10 μL of the Universal Master Mix (2x). The qRT-PCR reactions were accommodated in 96-well plates in the Applied Biosystems RT- PCR instrument. The assays were started by denaturation for 2 min at 50 °C, 10 min at 95 °C and followed by 40 cycles of 95 °C for 15 sec and 60 °C for 1 min. In addition, all probes (Applied Biosystems, Foster City, CA, USA) in this study, based on the mRNA sequences of target HER2, HSP90AA1, SIAH2, and reference gene GAPDH (Glyceraldehyde-3-phosphate dehydrogenase) acquired from GenBank database (http://www.ncbi.nlm.nih.gov/genbank/) (Table 1).
Statistical analysis was performed using SPSS version 21.0 (IBM Corp., Armonk, NY, USA). Correlation of gene expression analyses was done using Pearson linear correlation. Survival analysis was performed using Kaplan-Meier analysis. All tests were 2- 2-sided, and the significance level was set at 0.05.
The clinical characteristics are shown in Table 2. Overall, 85 invasive ductal carcinoma breast cancer patients were investigated in this study. The mean age was 53,18±11,62 years (median, 52), and the median age at the time of breast cancer diagnosis was 47.
In this study, HSP90, SIAH2, and HER2 mRNA gene expressions comparison between tumors and normal tissues were calculated by Sabiosciences’ data analysis software (https://dataanalysis.qiagen.com). Comparison of HSP90, SIAH1, and SIAH2 mRNA mean expression levels in breast tumor and normal tissues indicate a significant increase in breast cancer patients with 1.93, 2.09, and 1.82 fold increase in tumor samples compared to the normal tissues (P= 0.0271, P= 0.0225, and P= 0.0311, respectively). Whereas, the analysis of HER2 gene expression in tumoral tissues with a 1.66 fold increase was not significantly higher than normal tissues (P= 0.3793) (Fig. 1). A Heatmap of gene expressions is demonstrated in Fig. 2. Based on the cutoff value of SIAH1, SIAH2 and HSP90 fold changes, tumor breast cancers were identified as upregulated (AUC= 0.848, P<0.001; AUC=0.848, P<0.001; AUC=0.724, P<0.001, respectively) (Table 3, Fig. 3).
The correlation of HSP90 and SIAH1/2 expression with clinicopathological parameters (Ki-67, ER, PR, and HER2 were assessed with immunohistochemistry (IHC)) are shown in Table 4.
HSP90 gene expression, significantly associated with ER-positive (P=0.0423), HER2-positive (P=0.0312), and recurrence/metastasis rates (P=0.0447) in histopathological tumoral tissues; but no significantly associated with histopathological tumor staging, in situ component, and ki-67 status of the breast cancer patients. We observed that HSP90 expression increased 4.295 fold change (P=0.0931) in breast cancer lymph node (N2: at least 4 nodes) compared with lymph node (N1: 1–3 nodes) patients. Moreover, tumor tissues with size >3 cm (1.89-fold change; P=0.0808) presented an increase in HSP90 expression compared with normal tissues.
SIAH1 overexpression was not related to age, PR, recurrence/metastasis rates, tumor staging, lymph node involvement, Ki-67 status, and in situ component status of the breast cancer patients. The SIAH1 overexpression was associated with the ER-positive (P= 0.0375), and SIAH1 expression in tumor tissues approximately significant was up-regulated (P= 0.0657) in recurrence/metastasis positive breast cancers.
SIAH2 overexpression was not related to age, PR, recurrence/metastasis rates, tumor staging, lymph node involvement, and in situ component status of the breast cancer patients. SIAH2 overexpression was associated with the ER-positive (P= 0.050) and ki-67 status (Ki-67 (15%–35%), P= 0.0154). Besides, the high expression of SIAH2 showed close to being significant in HER2-positive tumors (P= 0.070).
Furthermore, the correlation between HER2 and HSP90, SIAH2 were analyzed. Results of correlation were shown that HSP90 scores were higher in high-level HER2 mRNA expression cases (Fig. 4A; P=0.001, r=0.20). Additionally, analysis of gene expression data demonstrated that SIAH2 expression was significantly correlated with HER2 mRNA level (Fig. 4B; P<0.001, r=0.25). HSP90 mRNA expression was positively associated with the expression of SIAH2 (Fig. 4C; P<0.001, r=0.45). There was no relationship between the SIAH1 and HER2, SIAH1 and HSP90, or SIAH1 and SIAH2.
The Kaplan-Meier survival analysis showed no effect of the SIAH1, SIAH2, and HSP90 high expressions on the overall survival of breast cancer patients (5 years follow-up) (P= 0.090, P= 0.971, and P= 0.582, respectively).
The resistance to anti-estrogen and anti-HER2 therapies emerges in a considerable rate of breast cancer patients, and novel drug therapies are required. Recognition of other molecular factors, exclusively those related to aggressive features and poor prognosis, could improve the diagnosis and therapy of breast cancer patients (12). HSP90 modulates the stabilization of oncogenic and anti-oncogenic proteins such as ER, PR, essential components of HER2 signaling (HER2, AKT, RAF, and HIF1a), and EGFR in breast cancer (11, 31, 32). The prognostic significance of HSP proteins in breast cancer is better reflected in their impact on patient survival, and increased HSP90 expression was associated with increased death rates (33). DCIS does not exhibit marked HSP90-upregulated, while IDC presents with high HSP90 expression (34, 35). In previous studies, the negative impact of overexpression HSP90 on patient survival was illustrated; also, the overexpression of HSP90 was severely correlated with larger tumor size, histological grade, and lymph node (34, 35). The studies on HSP90 expression have been published from breast cancer cell lines xenografts and not from tumor biopsy samples, and the association of HSP90 expression with clinical features has not been broadly studied in the context of molecular subtypes of breast cancer. Our findings showed that HSP90 gene expression, significantly associated with ER-positive, HER2-positive, and recurrence/metastasis rates in histopathological tumoral tissues, whereas no significant correlation was observed between histopathological tumor sizes. This is in contrast with the results that demonstrated a significant difference between high-level HSP90 expression with larger tumor size; whereas in our studt, tumor tissues with size >3 cm presented an increase in HSP90 expression (1.89-fold change) compared with normal tissues (16). We observed that HSP90 expression increased 4.295-fold change in breast cancer lymph node with at least 4 nodes. Furthermore, significant difference were showed between high-level HSP90 expression with lymph node metastases. “HSP90 expression was different in patients’ tumors in comparison with cancer cell lines; whether overexpression of HSP90 is also different between primary and metastatic tumors is unclear at this time” (15). In studies of pre-clinical and clinical breast cancer models demonstrated that the potentially increased aggressiveness, related to overexpressing the Hsp90. HER-2 is the most sensitive HSP90 client, and HER2-amplified are potently inhibited by HSP90 inhibitors in breast cancer cells (36). In the present study, HSP90 expression in tumor tissues was up-regulated, and significantly mRNA expression of HSP90 and HER2 was linearly correlated. “SIAHs are the human homologs of Seven-In-Absentia (SINA), an evolutionarily conserved RING finger E3 ubiquitin ligase, and two SINA homologs have been identified in the human genome, SIAH1 and SIAH2” (37). SIAHs have been shown to play a role in different pathways including estrogen signaling, RAS signaling, and as an essential downstream signaling component required for suitable EGFR/HER2, and also in pathways those involved in response to DNA damage, the hypoxic response (26). Some studies reported pro-tumorigenic roles of SIAH1 and SIAH2, whereas studies often identify SIAH1 as a tumor suppressor in breast cancer (38). SIAH2 as an E3 ubiquitin ligase involved in proteasome-mediated degradation and ubiquitination of proteins (25, 39). SIAH may represent as a beneficial prognostic biomarker that predicts ductal carcinoma in situ progression to invasive ductal breast cancer (26). In our study, there was a significant increase in the expression of SIAH2 levels in invasive ductal carcinoma (IDC) tissues. A significant increase was found in SIAH2 expression in DCIS progression to invasive cancers (40). A significant positive association was revealed between SIAH and HER2, which is in line with our study. In the present study, SIAH2 overexpression was associated with the ER-positive, which was similar to that of Chan et al (40), and also our findings showed that SIAH2 gene expression, significantly associated with Ki-67 (15%–35%) proliferation index. The high expression of SIAH2 showed close to being significant in patients with HER2-positive breast cancer. Notably, in this study correlation analysis showed that the mRNA expression of HSP90 and HER2 was linearly and mRNA expression of HSP90 and SIAH2 was correlated. The heat shock protein 90 (HSP90) activates/stabilizes its target proteins such as HER2. The repression of HSP90 causes the deterioration of oncogenic protein kinase activated or mutated; the ubiquitination of client proteins takes place by means of the action of E3 ubiquitin ligases. CUL5 (Cullin-RING ligase Cullin-5) is an E3 ubiquitin ligase, which the overexpression of CUL5 has been shown in breast cancer patients (41). The silencing of CUL5 (Cullin-RING ligase Cullin-5; an E3 ubiquitin ligase) was decreased cellular susceptibility to HSP90 inhibitors in HER2-positive breast cancers (24).
The mRNA expression of HSP90 and HER2 was related, and also mRNA expression of HSP90 and SIAH2 was correlated. In terms of the correlation between SIAH2 expression and HER2, there was a linear correlation in our study. Therefore, SIAH2 can contribute as a cellular and molecular response to HSP90 inhibitors in the treatment of HER2-positive breast cancer.
Ethical issues (Including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, etc.) have been completely observed by the authors.
The present study was supported by a grant from the Scientific Research Projects Foundation (BAP; ÖAP(T)-2019/1) of the Bursa Uludag University of Turkey. | true | true | true |
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PMC9547094 | Hui Wang,Danrong Shi,Penglei Jiang,Zebin Yu,Yingli Han,Zhaoru Zhang,Peihui Wang,He Huang,Hangping Yao,Pengxu Qian | SARS-CoV-2 N protein potentiates host NPM1-snoRNA translation machinery to enhance viral replication | 08-10-2022 | Non-coding RNAs,Infectious diseases,Epigenetics | SARS-CoV-2 N protein potentiates host NPM1-snoRNA translation machinery to enhance viral replication
Dear Editor, COVID-19 (Coronavirus Disease 2019) is causing an unprecedented public health crisis. Protein translation is crucial for virus lifecycle. Nucleocapsid (N) protein is among the most abundant SARS-CoV-2 proteins and highly conserved across coronavirus genus. However, its function in subverting host translation machinery is still elusive. To explore crucial signaling pathways for SARS-CoV-2 lifecycle, we initially analyzed expression profiles of ACE2, CTSL and TMPRSS2 in susceptible organs (Supplementary Fig. S1a–f). Meanwhile, GSEA and GO term analysis revealed that translation related pathways were significantly enriched among SARS-CoV-2 infection-related genes in these organs (Supplementary Figs. S1g–1I, S2a). These results suggested that host cell translation machinery was crucial during SARS-CoV-2 invasion. Besides, host proteins interacting with N protein were enriched in “translation” and “ribosome” related pathways (Fig. 1a). Therefore, we next focused on N protein and its impact on host translation machinery. Post-transcriptional modifications of rRNAs are involved in ribosome biogenesis and fine-tuning of translation, with the 2′-O-Methylation being the most abundant (Supplementary Fig. S2b). We first examined how N protein affects 2′-O-Me modification on host rRNAs by RiboMethSeq in HEK293T cells. We detected 12 sites on rRNA as differentially modified sites (DMS), all of which presented elevated modification upon N protein expression (Fig. 1b, c). Ectopic N protein enhanced global protein synthesis in 293T cells (Fig. 1d). and similarly, polysome fractions significantly increased, indicating mRNAs were translated at higher efficiency (Supplementary Fig. S2c). Using a hybrid in vitro translation (IVT) system (Supplementary Fig. S2d), we found that ribosomes from 293T cells with ectopic N protein showed enhanced translation efficiency (Fig. 1e). These results demonstrate that ectopic expression of N protein promoted host translation, with direct impact on rRNA modification. We re-analyzed the interactome data between SARS-CoV-2 proteins and host proteins and discovered extensive interactions between SARS-CoV-2 proteins and host rRNA modification related complexes (Supplementary Fig. S3a). We then experimentally verified these interactions (Supplementary Fig. S3b), and found that NPM1 interacted with multiple SARS-CoV-2 proteins, which was verified by Co-IP and immunofluorescence staining (Fig. 1f and Supplementary Fig. S3b–d). We also performed ELISA assays and found that N protein bound to pre-coated NPM1 in a dose-dependent manner (Supplementary Fig. S3e, f). Biolayer interferometry assays (BLI), and Surface Plasmon Resonance (SPR) also revealed the interaction between N and NPM1 (Kd = 0.293 μM) (Supplementary Fig. S3g, h). The association between N and NPM1 was significantly attenuated by RNase A treatment, suggesting that their interaction was at least partially RNA-dependent (Supplementary Fig. S3i). We next constructed series of truncations of N protein. Only the long isoform of T3 was co-immunoprecipitated with NPM1 (Supplementary Fig. S4a) and co-localized with NPM1 (Supplementary Fig. S4b). None of the truncations were able to enhance translation efficiency comparably to full-length N protein, suggesting the importance of structural integrity to its function (Supplementary Fig. S4c). Besides, we found that other structural proteins, such as M, were neither able to enhance translation efficiency nor interacting with NPM1 (Supplementary Fig. S4d, e). These results provide strong evidence for the specific interaction between N and NPM1, and the SR motif plays an essential role in the interaction. NPM1 is a multifunctional protein which shuttles between nucleus and cytoplasm. It is involved in many physio/pathological processes and has been reported to regulate rRNA modification and ribosome biogenesis via interacting with snoRNAs. Knockdown of NPM1 significantly suppressed translation efficiency that was boosted by N protein (Fig. 1g, Supplementary Fig. S5a, b). Besides, treatment with NPM1 inhibitor, NSC348884, also partially rescued the effect of N protein (Supplementary Fig. S5c–i). We next quantified translation efficiency of specific genes using total RNAs extracted from separate sucrose gradients in the polysome profiling assay. Most N mRNA was presented in polysome fractions, indicating highly efficient translation, and knockdown of NPM1 led to a drastic shift of N mRNA distribution toward the monosome fractions (gradients 2–5), indicating that N mRNAs were much less efficiently translated after NPM1 depletion (Fig. 1h). Similar results were observed after NSC treatment (Supplementary Fig. S5j). Moreover, N protein also led to a much milder increase in the amount of host mRNA (actin) in polysome fractions, which decreased after NPM1 knockdown or NSC treatment (Supplementary Fig. S5k, l). In IVT assays, ribosomes from 293T cells with exogenous N showed enhanced translation efficiency when translating N mRNAs, which was suppressed upon NPM1 knockdown (Fig. 1i, top row) or NSC treatment (Supplementary Fig. S5m, top row). However, translation of host actin mRNAs was not affected by N protein (Fig. 1i and Supplementary S5m, 2nd row). When both N and actin mRNAs were presented in one IVT reaction, partially mimicking competition between viral and host mRNAs, ribosomes still showed higher translation efficiency for N mRNAs, but not for actin, and NPM1 inhibition suppressed this effect (Fig. 1i and Supplementary S5m, bottom rows). When using exogenous mRNA (Luciferase mRNA), similar results were observed (Fig. 1j and Supplementary S5n). These results demonstrated that ectopic N protein potentiated host translation machinery via interacting with NPM1, which might predominantly enhance translation efficiency of virus transcripts. NPM1 has been shown to function as RNA/DNA binding protein regulating 2′-O-methylation of rRNA via direct binding of snoRNAs. We therefore hypothesized that N protein functions via NPM1-binding snoRNAs. We first re-analyzed snoRNA expression in different tissues using public data from ENCODE, and found significant overlap of expression profile among lung, liver, and intestine (16/top 20, Supplementary Fig. S6a–c), of which 4 snoRNAs were reported to bind to NPM1 and their expression was highly correlated with ACE2, TMPRSS2, FURIN (Fig. 1k, l, Supplementary Fig. S6d). Exploiting published data, we also found that SNORD93 was the most highly enriched, among snoRNAs bound to N protein (Fig. 1m). This was verified by RNA immunoprecipitation (Fig. 1n and Supplementary S6e). Besides, we found that N protein significantly promoted binding of snoRNAs to NPM1 (Fig. 1o and Supplementary S6f). Knockdown 3 of the 4 snoRNAs fully restored translation to normal levels (Fig. 1p, Supplementary Fig. S6g, h). Besides, another snoRNA, SNORD61, albeit not highly correlated with ACE2, also showed similar rescuing effects (Supplementary Fig. S6i–k). SNORD93 was predicted to target A576 on 18S rRNA for 2′-O-Me modification (Fig. 1l), which increased most after ectopic expression of N (Fig. 1b), and bound to N protein with highest abundance (Fig. 1m). These data suggested that SNORD93 was a crucial downstream factor. In IVT assay, Knockdown SNORD93 significantly rescued ribosome translation activity in IVT assay (Fig. 1q, r) and recovered polysome fraction amount and mRNA distribution across the sucrose gradients (Fig. 1s, Supplementary Fig. S6l–m). Distribution of actin mRNA was affected but to much less extent (Supplementary Fig. S6o). Besides, another SARS-CoV-2 protein nsp16, the methyl-transferase, was also affected to similar extent as N protein (Supplementary Fig. S6p). Together, these results show that SNORD93 plays a crucial role in regulating the function of N protein. We next explored strategy for SARS-CoV-2 prevention via targeting N protein-related translation machinery components. SARS-CoV-2 infection also enhanced 2′-O-Me modification, as was detected by RTL-P assay (Supplementary Fig. S7a). In Huh-7 and Calu-3 cells, exogenous N protein enhanced translation via interaction with NPM1 (Supplementary Fig. S7b–g). In SARS-CoV-2 infected Huh-7 cells, co-localization was also observed by IF staining (Supplementary Fig. S7d). NSC dose-dependently suppressed SARS-CoV-2 proliferation, although not as effective as remdesivir and cycloheximide in Huh-7 and Calu-3 cells (Fig. 1t, and Supplementary S7h–j). Besides, depletion of SNORD93 or SNORD104 significantly reduced virus proliferation in Huh-7 other than Calu-3 (Fig. 1u–w, Supplementary Fig. S7k–m). Moreover, knockdown of NPM1 in Huh-7 cells also significantly inhibited virus proliferation (Supplementary Fig. S7n–q). These results support our hypothesis that SARS-CoV-2 proliferation could be effectively attenuated by NPM1 inhibition or snoRNA ASO, nominating promising potential therapeutic strategies for clinical use. In summary, we found that SARS-CoV-2 N protein enhances host translation efficiency by potentiating the host NPM1-snoRNA translation machinery. By interacting with NPM1 and snoRNAs, N protein significantly promotes ribosome translation efficiency, particularly for viral mRNAs, via enhancement of snoRNA-mediated 2′-O-methylation on rRNAs (Supplementary Fig. S8). Finally, targeting NPM1 or N-related snoRNAs efficiently ameliorated SARS-CoV-2 proliferation. Our work provides preliminary data in understanding the SARS-CoV-2 viral lifecycle and offers novel potential strategies for COVID-19 prevention and therapy.
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PMC9547152 | Eva van Ingen,Pleun A.M. Engbers,Tamar Woudenberg,M. Leontien van der Bent,Hailiang Mei,Johann Wojta,Paul H.A. Quax,A. Yaël Nossent | C/D box snoRNA SNORD113-6 guides 2′-O-methylation and protects against site-specific fragmentation of tRNALeu(TAA) in vascular remodeling | 17-09-2022 | MT: RNA/DNA Editing,tRNA-derived fragments,tRF,C/D box small nucleolar RNAs,orphan,14q32 locus,DLK1-DIO3 locus,cardiovascular disease,vascular remodeling | C/D box small nucleolar RNAs (snoRNAs) of the DLK1-DIO3 locus are associated with vascular remodeling and cardiovascular disease. None of these snoRNAs has any known targets yet except for one, AF357425/SNORD113-6. We previously showed that this snoRNA targets mRNAs of the integrin signaling pathway and affects arterial fibroblast function. Here, we aimed to identify whether AF357425/SNORD113-6 can also target small RNAs. We overexpressed or inhibited AF357425 in murine fibroblasts and performed small RNA sequencing. Expression of transfer (t)RNA fragments (tRFs) was predominantly regulated. Compared with overexpression, AF357425 knockdown led to an overall decrease in tRFs but with an enrichment in smaller tRFs (<30 nucleotides). We focused on tRNA leucine anti-codon TAA (tRNALeu(TAA)), which has a conserved predicted binding site for AF357425/SNORD113-6. Adjacent to this site, the tRNA is cleaved to form tRFLeu 47–64 in both primary murine and human fibroblasts and in intact human arteries. We show that AF357425/SNORD113-6 methylates tRNALeu(TAA) and thereby prevents the formation of tRFLeu 47–64. Exposing fibroblasts to oxidative or hypoxic stress increased AF357425/SNORD113-6 and tRNALeu(TAA) expression, but AF357425/SNORD113-6 knockdown did not increase tRFLeu 47–64 formation under stress even further. Thus, independent of cellular stress, AF357425/SNORD113-6 protects against site-specific fragmentation of tRNALeu(TAA) via 2′O-ribose-methylation. | C/D box snoRNA SNORD113-6 guides 2′-O-methylation and protects against site-specific fragmentation of tRNALeu(TAA) in vascular remodeling
C/D box small nucleolar RNAs (snoRNAs) of the DLK1-DIO3 locus are associated with vascular remodeling and cardiovascular disease. None of these snoRNAs has any known targets yet except for one, AF357425/SNORD113-6. We previously showed that this snoRNA targets mRNAs of the integrin signaling pathway and affects arterial fibroblast function. Here, we aimed to identify whether AF357425/SNORD113-6 can also target small RNAs. We overexpressed or inhibited AF357425 in murine fibroblasts and performed small RNA sequencing. Expression of transfer (t)RNA fragments (tRFs) was predominantly regulated. Compared with overexpression, AF357425 knockdown led to an overall decrease in tRFs but with an enrichment in smaller tRFs (<30 nucleotides). We focused on tRNA leucine anti-codon TAA (tRNALeu(TAA)), which has a conserved predicted binding site for AF357425/SNORD113-6. Adjacent to this site, the tRNA is cleaved to form tRFLeu 47–64 in both primary murine and human fibroblasts and in intact human arteries. We show that AF357425/SNORD113-6 methylates tRNALeu(TAA) and thereby prevents the formation of tRFLeu 47–64. Exposing fibroblasts to oxidative or hypoxic stress increased AF357425/SNORD113-6 and tRNALeu(TAA) expression, but AF357425/SNORD113-6 knockdown did not increase tRFLeu 47–64 formation under stress even further. Thus, independent of cellular stress, AF357425/SNORD113-6 protects against site-specific fragmentation of tRNALeu(TAA) via 2′O-ribose-methylation.
Vascular remodeling is the collective name for both adaptive and maladaptive changes to the vessel wall. This includes processes like angiogenesis and arteriogenesis on the one hand and atherosclerosis and aneurysm formation on the other. Vascular remodeling is the predominant underlying cause of most cardiovascular disease. All layers of the arterial wall, i.e., the tunica intima made up of endothelial cells, the tunica media made up of smooth muscle cells, and the tunica adventitia made up of predominantly fibroblasts, play their own role in vascular remodeling, but the role of the adventitial fibroblasts is often underestimated. Although cardiovascular disease has a complex pathology, ischemia plays an intricate part in both the development and manifestation of cardiovascular disease. Ischemia induces several forms of cellular stress, including nutrient deprivation and hypoxia, that have all been linked to increases in posttranscriptional modifications of RNA.3, 4, 5, 6, 7 Small nucleolar RNAs (snoRNAs) are a type of small noncoding RNA that mediate RNA modifications at the post-transcriptional level. There are two types of snoRNAs, C/D box and H/ACA box snoRNAs, named after their conserved sequence motifs. C/D box snoRNAs guide 2′-O-ribose methylation (2′Ome) of their target RNAs. The DLK1-DIO3 locus on the long arm of human chromosome 14 encodes a cluster of 41 C/D box snoRNAs (14q32; 12F1 in mice). We have demonstrated that this cluster of 14q32 C/D box snoRNAs is strongly associated with vascular remodeling and human cardiovascular disease.8, 9, 10 The association with cardiovascular disease is both independent of and stronger than the 14q32 long noncoding RNAs (lncRNAs) and the cluster of 14q32 microRNAs that lie adjacent to the snoRNA genes. Furthermore, plasma levels of 14q32 snoRNAs were associated with disease outcome in patients with peripheral arterial disease (PAD)., However, all 14q32 C/D box snoRNAs, except for one, are orphan snoRNAs, meaning that they have no known RNA targets. We recently demonstrated that one of the most abundantly expressed snoRNAs of the 14q32 cluster, human SNORD113-6, and its murine equivalent, AF357425, target mRNAs of the integrin signaling pathway, influencing both pre-mRNA processing and 2′Ome. The D’ antisense box of AF357425/SNORD113-6 is fully conserved between humans and mice. Fibroblast integrin signaling is important for cell-cell and cell-matrix interactions and acts in various forms of cardiovascular remodeling that can lead to cardiovascular disease. Indeed, knockdown of SNORD113-6 altered human arterial fibroblast function. C/D box snoRNAs associate with four conserved ribonucleoproteins NHP2L1, NOP56, NOP58, and Fibrillarin (FBL). FBL is the methyltransferase that catalyzes 2′Ome. C/D box snoRNAs have two antisense boxes, located directly upstream of the D and D’ boxes, which are not covered by ribonucleoproteins and are thus free to interact with target RNA sequences. C/D box snoRNAs hybridize to their target RNAs via Watson-Crick base-pairing. Once bound to the target RNA, the 5th nucleotide upstream of the D or D’ box is positioned for 2′Ome.13, 14, 15 Many expressed C/D box snoRNAs, however, lack antisense elements of known rRNA 2′Ome sites and are considered orphan snoRNAs. Likely, these orphan C/D box snoRNAs target other types of RNA molecules than rRNA.17, 18, 19 Besides rRNAs, transfer (t)RNAs are the most heavily modified cellular RNAs. Their canonical function lies in protein translation, where they deliver amino acids to the translating peptide chain. However, recent reports show that tRNAs can be processed into tRNA-derived fragments (tRFs), which can perform other, noncanonical, functions. tRFs can derive from different regions of their parental tRNA, located anywhere from the 5′ to 3′ end, and have variable sizes up to ∼50 nucleotides., Fragmentation of tRNAs can be induced under cellular stress, such as oxidative stress and hypoxia, which are important triggers of vascular remodeling processes.23, 24, 25 Among others, angiogenin (ANG) is a tRNA-processing endonuclease that is activated during cellular stress. Recent findings show that RNA modifications guided by snoRNAs can prevent tRNA cleavage and thereby regulate tRF formation.,26, 27, 28, 29 For instance, SNORD97 induces 2′Ome on the wobble cytidine C34 of tRNAMet(CAT), which protects against ANG-induced cleavage. Whether AF357425/SNORD113-6 also guides 2′Ome on small RNA molecules like tRNAs, however, is still unknown. Here, we aimed to determine whether AF357425/SNORD113-6 can target small RNAs in the vasculature, using primary murine fibroblasts (PMFs) and primary human umbilical arterial fibroblasts (HUAFs). Fibroblasts were chosen for their relevance in vascular remodeling and because the 14q32 snoRNAs are expressed most abundantly in fibroblasts. We used both murine and human fibroblasts to be able to look only at putative target RNAs that were conserved between the two species. We confirmed our key findings using an ex vivo model for ischemia in intact human arteries. We performed small RNA sequencing (sRNA-seq) on primary PMFs in which we either inhibited or overexpressed AF357425. We found that tRFs were the predominant group of small RNAs that changed in expression. Knockdown of AF357425 resulted in an apparent reduction of total tRFs but an enrichment of smaller sized tRFs (18–30 nucleotides). We focused on one of these tRNAs, tRNA leucine anti-codon TAA (tRNALeu(TAA)), which has a predicted binding site for AF357425 in mice and SNORD113-6 in human. sRNA-seq data showed that its dominant tRF, tRFLeu 47–64, is formed just upstream of this site. Formation of tRFLeu 47-–64 was conserved in both PMFs and HUAFs and was investigated under oxidative, hypoxic, and starvation stress. We show that AF357425/SNORD113-6 indeed methylates this tRNA and protects against site-specific tRNALeu(TAA) fragmentation.
In order to identify small RNA targets of AF357425/SNORD113-6, we performed sRNA-seq on PMFs in which we either inhibited or overexpressed AF357425. With this strategy, we aimed to obtain the largest possible difference in small RNA target expression. Gapmers were used to inhibit AF357425 expression (GM-AF25) and 3rd generation antisense oligonucleotides (3GAs) to overexpress AF357425 (3GA-AF25). We showed previously that 3GAs directed against the 3′ end of AF357425 (3GA-AF25) induced snoRNA overexpression, likely through protection from degradation by endonucleases. Expression of AF357425 was increased (>5-fold) in PMFs treated with 3GA-AF compared with GM-AF25 (Figure S1). By far, most reads from the sRNA-seq in both samples were mapped to microRNAs. Read counts mapped to microRNAs, as well as those that mapped to the much lower expressed snoRNA and rRNA genes, were similar between AF25-high and AF25-low cells. However, reads that mapped to tRNA genes, which are all tRFs of <45 nucleotides in length, appeared to be reduced in number in AF25-low cells (Figure 1A; Tables S2 and S3). Where the longer tRFs (30–45 nucleotides) appeared enriched in AF25-high cells, smaller-sized tRFs (18–29 nucleotides) were enriched in AF25-low cells, particularly the 18-nucleotide tRFs (Figure 1B). These data indicate that AF357425 may protect against tRNA fragmentation.
In order to investigate the mechanisms through which AF357425/SNORD113-6 may influence tRNA fragmentation, we focused on a single tRNA. Among others, tRNALeu(TAA) had a predicted D’ box antisense sequence for AF357425. This site was conserved in human tRNALeu(TAA) for the D’ box antisense sequence of SNORD113-6. Except for the outer 2 nucleotides, a perfect reverse complementary sequence for the middle 7 nucleotides is present in both mouse and human tRNALeu(TAA) (AACCCCA; Figure 2B). A tRF cleaved just upstream of this predicted 2′Ome site (18–20 nucleotides; Figure 2A), tRFLeu 47–64, was abundantly expressed in both AF25-high and AF25-low cells (Figure 2B). However, the total tRFs generated from tRNALeu(TAA) were decreased in AF25-low cells. In contrast, tRFLeu 47–64 was more abundant relative to the total tRFs in AF25-low (50%) compared with AF25-high cells (35%; Figures 2B and 2C). We confirmed expression of tRFLeu 47–64 by northern blot in both PMFs and in HUAFs. Expression of tRFLeu 47–64 appeared enhanced under oxidative stress (Figures 2D and 2E).
Next, we performed reverse transcription at low dNTP concentration followed by quantitative PCR (RTL-Q) to calculate the estimated methylated fraction (EMF), using site-specific primers for detection of 2′Ome. We confirmed 2′Ome of the mature full-length tRNALeu(TAA), located on the 5th nucleotide upstream of the D’ antisense box, in both PMFs and HUAFs. Inhibition of AF357425/SNORD113-6 partly reduced 2′Ome at this site compared with a gapmer control (GM-ctrl; p for trend = 0.0725 in PMFs and 0.0968 in HUAFs; Figure 3). 2′Ome also appeared present on the precursor-(pre)tRNALeu(TAA) in HUAFs, but we could not confirm snoRNA-induced regulation of 2′Ome in the pre-tRNALeu(TAA) due to high Ct values above the detection threshold (>45 Ct; Figure S2). The validation of 2′Ome in both mouse and human cells suggests that both are evolutionarily conserved features of tRNALeu(TAA).
As fragmentation of tRNAs can be induced during cellular stress,23, 24, 25 we cultured PMFs and HUAFs under different cellular stress conditions and measured expression levels of AF357425/SNORD113-6, mature tRNALeu(TAA), and tRFLeu 47–64 by qPCR. Endogenous expression of AF357425/SNORD113-6 and mature tRNALeu(TAA) showed similar expression patterns in PMFs and HUAFs, with increased expression under both hypoxia and oxidative stress, compared with the normal culture condition control. Serum starvation, on the other hand, did not induce changes in either AF357425/SNORD113-6 or tRNALeu(TAA) expression compared with normal culture conditions. Expression of tRFLeu 47–64 was only increased significantly under hypoxia in both PMFs and HUAFs but appeared slightly elevated under oxidative stress as well (Figure 4). Subsequently, PMFs and HUAFs were transfected with either GM-AF25/113 or a GM-ctrl and were cultured under the different cell stress conditions. The absolute Ct value of mature tRNALeu(TAA) was divided by the Ct value of tRFLeu 47–64 in order to quantify the expression of tRFLeu 47–64 relative to mature tRNALeu(TAA), which it was generated from. The ratio was increased under AF357425/SNORD113-6 inhibition under control conditions in both PMFs and HUAFs (Figure 5). In PMFs, the ratio was also increased under hypoxia and showed a trend toward an increased ratio under serum starvation (Figure 5A). This increased ratio demonstrates that more tRFLeu 47–64 is formed relative to its mature tRNA, when AF357425/SNORD113-6 is inhibited. When we quantified expression of ANG, we did not observe a difference between GM-AF25/113 and GM-ctrl (Figure S3). However, ANG did increase under cellular stress, similar to the snoRNA, both in PMFs and HUAFs. We can neither confirm nor exclude that ANG is responsible for cleavage of tRNALeu(TAA), but we can conclude that ANG is not influenced by the snoRNA directly and that changes in fragmentation are likely caused by changes in snoRNA-guided 2′Ome of the tRNA.
In many vascular pathologies, adventitial fibroblasts are activated and become myofibroblasts. We therefore examined whether inhibition of SNORD113-6 affects this phenotype transition (Figure S4). There was a trend toward reduced collagen type 1 alpha 1 chain (COL1A1) expression in GM-113-treated fibroblasts (p = 0.07); however, protein expression was affected by snoRNA inhibition. Although α-smooth muscle actin (αSMA) was expressed, as is common for fibroblasts in culture, we did not observe differences between GM-113- and GM-ctrl-treated cells. To examine whether tRNALeu(TAA) fragmentation increases under stress conditions in human vascular tissues, we used internal mammary arteries (IMAs), which were harvested during elective coronary bypass surgery on patients with coronary artery disease. After culturing the vessels ex vivo under control or ischemic (= hypoxia + starvation) conditions for 24 h, expressions of SNORD113-6, tRNALeu(TAA), and tRFLeu 47–64 were measured. Consistent with our in vitro models, expression of SNORD113-6 was significantly upregulated (p = 0.0432) under ischemic conditions (Figure 6A). tRNALeu(TAA) also appeared somewhat upregulated, but not significantly (Figure 6B). tRFLeu 47–64 expression, however, was not altered (Figure 6C). When we calculated the Ct tRNALeu(TAA)/tRFLeu 47–64, there was a trend toward a decrease in the ratio, indicating that less tRNALeu(TAA) was cleaved into tRFLeu 47–64 (Figure 6D).
Ribonucleotide modifications in the structural core of the tRNA may stabilize the tRNA and reduce tRNA degradation rates. After transfection with either GM-AF25/113 or GM-ctrl, cells were treated with a high concentration of actinomycin D (5 μg/μL) for 1 h to inhibit novel tRNA transcription. In both PMFs and HUAFs, mature tRNALeu(TAA) was rapidly degraded, but no differences were observed between GM-AF25/113 and GM-ctrl (Figures 7A and 7C). In PMFs, the relative expression of mature tRNALeu(TAA) was lower to begin with in AF25-low cells and remained lower after 1 h, compared with GM-ctrl (Figure 7A). To rule out differences in degradation rates of housekeeping genes used (RPLP0 and U6) between the two groups, we also normalized the expression levels at 1 to 0 h (T0; Figures 7B and 7D). Indeed, no differences in degradation rates between GM-AF25/113 or GM-ctrl were observed, indicating that a reduction of this single 2′Ome modification did not affect overall mature tRNALeu(TAA) stability but only the site-specific fragmentation.
Here, we aimed to further elucidate the role of the vasoactive 14q32 snoRNA AF357425/SNORD113-6 in vascular remodeling. We investigated whether AF357425/SNORD113-6 could also target small RNAs besides the previously identified integrin signaling mRNA targets. We found that tRNAs are the predominant small RNA target of AF357425 in primary fibroblasts. Inhibition of AF357425/SNORD113-6 led to an overall decrease in tRFs, and, compared with overexpression of the snoRNA, less larger (>30 nucleotides) and more smaller (<30 nucleotides) tRFs were formed. In order to investigate the underlying mechanisms of action, we focused on tRNALeu(TAA), which has a conserved binding site for the D’ box seed sequence of AF357425/SNORD113-6. We showed that tRNALeu(TAA) is a 2′Ome target of AF357425/SNORD113-6 and that snoRNA inhibition led to an apparent reduction of 2′Ome at this site, both in murine and in human primary fibroblasts. Endogenous expression of AF357425/SNORD113-6 and mature tRNALeu(TAA) both increased under hypoxia and oxidative stress. Endogenous tRFLeu 47–64 expression was also elevated under hypoxia in vitro. In intact human arteries however, ischemia-induced upregulation of SNORD113-6 appeared to reduce tRNALeu(TAA) fragmentation into tRFLeu 47–64. Knockdown of AF357425/SNORD113-6 resulted in an increased ratio of tRFLeu 47–64 relative to its mature tRNALeu(TAA). 2′Ome by AF357425/SNORD113-6 was not important for the overall stability of the tRNA, and therefore, we conclude that it acts via protecting against site-specific fragmentation of tRNALeu(TAA) into tRFLeu 47–64. Regarding the biological role of tRFLeu 47–64 in vascular remodeling and cardiovascular disease, much remains unclear. Just like we show here, several other recent studies have shown that fragmentation of tRNAs increases under cellular stress.23, 24, 25, Similar cellular stress conditions also trigger vascular remodeling. This implicates that the formation of tRFs play a regulatory role in vascular remodeling. Indeed, oxygen-glucose deprivation, which is an in vitro model for ischemic reperfusion injury, induced tRNA cleavage in neuronal cells. Also in vivo, in models for acute ischemic stroke and PAD, the formation of tRFs was strongly increased. Similarly, we have previously shown that the 14q32 snoRNAs are regulated under ischemic conditions in patients with PAD and during vascular remodeling. In the current study, we show that expression of AF357425/SNORD113-6 indeed increased during hypoxia and oxidative stress in cells, as well as under ischemia in whole human inner mammary arteries cultured ex vivo. In whole artery tissue, ischemia appear to reduce the cleavage of tRNALeu(TAA) into tRFLeu 47–64 when looking at their Ct ratio. In cells, we did not observe this decrease; however, exposing cells to cellular stress did not result in an additional increase of tRFLeu 47–64 to mature tRNALeu(TAA) ratio in AF357425/SNORD113-6 knockdown cells, whereas expression of mature tRNALeu(TAA) and ANG both increased under both hypoxia and oxidative stress. Even though our findings implicate a role for site-specific fragmentation of tRNAs in vascular remodeling, the question remains what the molecular and biological function of the formed tRNA fragment tRFLeu 47–64 could be. Assumingly, tRFLeu 47–64 has an important role in vascular biology, as tRFLeu 47–64 is also generated under physiological conditions and not exclusively during cellular stress. Our group, as well as others, have shown that tRFs have potential as circulating biomarkers in, for example, acute stroke.35, 36, 37 It has also been demonstrated that tRFs can perform all sorts of regulatory functions, including regulation of protein translation, microRNA-like functions by base-pairing with mRNAs, and interaction with RNA-binding proteins., Furthermore, tRFs have been shown to be functionally active in modulating cardiac and skeletal muscle function and endothelial function but also in inhibition of angiogenesis., Which exact regulatory function(s) tRFLeu 47–64 may have and how it impacts vascular function, as well as vascular remodeling, remains to be determined. Regarding the molecular role of snoRNA-induced 2′Ome of tRNALeu(TAA), the same post-transcriptional modifications on tRNAs have been shown to both protect from and promote fragmentation., Our data suggest that AF357425/SNORD113-6 2′Ome protects the tRNA from cleavage into small fragments (∼18 nucleotides in length) rather than promoting it. However, we found more tRFs in total, including all tRFs formed of tRNALeu(TAA), and longer fragments (>30 nucleotides) in AF357425-high cells than in AF357425-low cells. Perhaps the presence or absence of modifications attracts different tRNA endonucleases, which produce different tRF species. The role of AF357425/SNORD113-6 2′Ome in cleavage of other tRNAs remains to be determined, but likely, its function is to prevent fragmentation of shorter tRFs (∼18 nucleotides in length). Besides the stabilizing tertiary structure, little is known about other functions of post-transcriptional modifications in the structural core of tRNAs. AF357425/SNORD113-6 targets and guides 2′Ome in the T-arm, the structural core, of tRNALeu(TAA). 2′Ome and the formation of tRFLeu 47–64 were found in both mice and humans, suggesting that both are evolutionarily conserved features of tRNALeu(TAA). Degradation rates of tRNALeu(TAA) were similar between GM-ctrl and GM-AF25/113 transfected cells, indicating that 2′Ome by AF357425/SNORD113-6 is not important for the overall tRNALeu(TAA) stability. Of course, tRNAs are heavily modified, and reduction of a single 2′Ome modification may not have direct consequences for their stability. This could however pose a threat to the reliability of our measurements. Modifications on tRNAs may impede reverse transcription and limit detection of tRFs and tRNAs by qRT-PCR. However, 2′Ome by AF357425/SNORD113-6 is located toward the 3′ end of the tRNA. We designed qPCR primers for mature tRNALeu(TAA) upstream of that site in order to limit confounding effects by the presence or absence of 2′Ome. Furthermore, expression of tRFLeu 47–64, which we initially found in the sRNA-seq, was confirmed by northern blot, and our qPCR results showed that tRFLeu 47–64 and mature tRNALeu(TAA) were both abundantly expressed. We cannot control for effects of other modifications in our qPCRs; however, if reversed transcription was hampered by other modifications, these were likely similar between GM-AF25/113 and GM-ctrl. Taken together, we show that AF357425/SNORD113-6 targets predominantly tRNAs, protecting the tRNA from cleavage into small fragments. When zooming in on one specific tRNA, tRNALeu(TAA), we show that AF357425/SNORD113-6 induces 2′Ome of the mature tRNA, thereby protecting against site-specific tRNA fragmentation. The function of tRFLeu 47–64 in vascular remodeling and whether this tRF forms a potential future therapeutic target for treatment and/or prevention of cardiovascular disease, however, remain to be elucidated.
Cells were cultured in a humidified incubator at 37°C under 5% CO2. Cells were passaged at 70%–90% confluency and used up to passage 6. DMEM, supplemented with 10% heat-inactivated fetal calf serum (FCSi) and 1% Pen/Strep, was used as culture media and was refreshed every 2–3 days.
Ear tissues from C57BL/6-J mice, about 3 weeks of age, were clipped into smaller pieces and embedded in 0.2% gelatine in 6-well plates. DMEM supplemented with 20% FCSi and 1% nonessential amino acids (NEAAs; Thermo Fisher Scientific, Waltham, MA, USA, cat. no. 11140050) was added to the embedded ear clippings. After 7 days, skin fibroblasts were grown out of the tissues onto the bottom of the culture plates. PMFs were expanded in culture media up to passage 3. PMFs were then used for further analysis or frozen down and stored in liquid nitrogen for later use.
Umbilical cords from full-term pregnancies were collected, stored in sterile PBS at 4°C, and, within 7 days, used for HUAF isolation. The two arteries were isolated from the umbilical cord. Endothelial cells were removed by gently rolling the artery over a blunted needle. After that, the tunica adventitia and tunica media were separated using surgical tools. The tunica adventitia was incubated overnight in culture media supplemented with 10% heat inactivated human serum (PAA, Pasching, Austria) and 1% NEAA. The next day, the tunica adventitia was treated with 2 mg/mL collagenase type II solution (Worthington, OH, USA, cat. no. NC9693955) at 37°C. The resulting cell suspension was filtered over a 70 μm cell strainer and centrifuged at 400 × g for 10 min. Cells were plated in 6-well plates, and media were refreshed after 90 min to remove slow adhering nonfibroblast cells. HUAFs were expanded up to passage 3 and used for further analysis or frozen down and stored in liquid nitrogen for later use.
Oxidative stress in both PMFs and HUAFs was induced by adding 10 μM reactive oxygen species (ROS) mimic tert-butyl hydroperoxide (tBHT; Luperox, 458139, Sigma Aldrich, St. Louis, MO, USA) to the culture media for 24 h. To serum starve the cells, DMEM with 1% PenStrep, supplemented with 1% FCSi for PMFs or 3% FCSi for HUAFs, was added to the cells. Different incubation times were tested for serum starvation (Figure S5). An incubation time of 24 h was determined as the most optimal time point. To induce hypoxia, cells in normal culture media were kept in a humidified incubator at 37°C under 1% O2 for 24 h. Absolute Ct values of AF357425 and U6 expression are shown in Figure S6.
RNA was isolated by standard TRIzol (Thermo Fisher Scientific, cat. no. 15596026) chloroform extractions. RNA concentration and purity were measured using Nanodrop (Nanodrop Technologies, Wilmington, DE, USA) or the Bioanalyzer (2100 Bioanalyzer Instrument, Agilent, Santa Clara, CA, USA). Reversed transcription of total RNA was performed with the high-capacity RNA-to-cDNA reverse transcription kit (Applied Biosystems, Thermo Fisher Scientific, cat. no. 4388950). Quantitect SybrGreen reagents (Qiagen Benelux, Venlo, the Netherlands, cat. no. 204145) were used for quantifications. Custom designed TaqMan small RNA assays (Thermo Fisher Scientific, cat. no. 4398987) were used for reversed transcription and quantifications of tRFs. Expression levels were normalized to U6 using the 2−ΔCt method. All primers used are provided in Table S1.
3GAs were kindly provided by Idera Pharmaceuticals (Cambridge, MA, USA). 3GAs directed to AF357425 consisted of two identical strands of DNA nucleotides with a full phosphorothioate backbone, connected by a 5′ phosphorothioate linker. GMs were custom designed against AF357425 (GM-AF25) or SNORD113-6 (GM-113; Sigma Aldrich). GMs were made up out of five 2′Ome RNA nucleotides, 10 DNA nucleotides, and five more 2′Ome RNA nucleotides with full phosphorothioate backbone. Sequences of 3GAs and GMs are provided in Table S1.
Prior to transfections, G1 cell-cycle arrest was induced by treating cells with KN-93 (Sigma Aldrich, cat. no. K1385), an inhibitor of CaMK-II (the multifunctional Ca2+/CaM kinase). KN-93 was added to the culture media at a concentration of 10 μM for 48 h. After cell synchronization, cells were washed with PBS, and basal DMEM was added. Meanwhile, lipofectamine RNAiMAX Reagent (Thermo Fisher Scientific, cat. no. 13778030) was used to create micelles loaded with 3GAs or GMs against snoRNA AF357425 or SNORD113-6 for transfection. Micelles were added to the cells, and after 1 h of transfection, 10% FCSi was supplemented to the transfected cells. Two concentrations of GM transfection were tested for optimal snoRNA inhibition (Figure S7). The optimal inhibition, without visible cytotoxic effects, was at 500 nM. A timeline of AF357425 and SNORD113-6 inhibition showed efficient snoRNA knockdown at 24 h. Therefore, for all experiments a concentration of GMs (500 nM) or 3GAs (200 nM; as established in a previous study) and a total transfection time of 24 h were used. After 24 h of transfection, cells were washed with PBS and used for further experiments or analyses.
RNA was isolated from PMFs transfected with 3GAs or GMs against AF357425. Absolute Ct values of AF357425 and U6 expression are shown in Table S4 and Figure S6. Isolated RNA was shipped to BGI for DNBseq sRNA-seq (GEO: GSE190537). Generated sRNA-seq files in FASTQ format are processed using the sRNAbench tool. Bowtie aligner was used to align reads to various reference genome and databases, such as GRCm38, mirbase small database, and RNAcentral. The expression of multiple classes of small RNA are quantified in the single assignment-based approach where reads mapping to multiple loci are assigned to the locus that has the highest expression. Reads per million (RPM) normalized counts are further generated that are used for downstream analysis.
Total RNA samples were diluted in Novex Tris-borate-EDTA (TBE)-urea sample buffer (Thermo Fisher Scientific, cat. no. LC6876), denatured at 95°C for 5 min, and put on ice. 15% Mini-PROTEAN TBE-urea gels (BioRad, cat. no. 4566053) in TBE buffer were pre-run at 200 V for 20 min. After that, RNA samples and a digoxigenin (DIG)-labeled Blue Color Marker for small RNA (DynaMarker, BioDynamics, cat. no. DM270-125uL) were loaded on the gel. Gels were electrophoresed at 200 V for ∼1 h. Next, RNA was transferred from the gel to a Hybond N+ membrane (GE Healthcare, cat. no. RPN203B) at 200 mA for 1 h. A Mini Trans-Blot Electrophoretic Transfer Cell (BioRad) system with an ice element and stirrer were used for RNA transfer. Next, RNA was crosslinked to the membrane with freshly prepared 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC; Sigma, cat. no. E1769) 1-methylimidazole (Sigma, cat. no. 336092) crosslinking solution (pH 8) for 1 h at 60°C. Membranes were pre-hybridized in ULTRAhyb Oligo Hybridization Buffer (Invitrogen, cat. no. AM8663) at 37°C for 30 min while gently shaking. Dual DIG-labelled DNA probes (designed and ordered at Integrated DNA Technologies, Coralville, IA, USA) were denatured at 95°C for 1 min, added to the hybridization buffer (final concentration 5 nM), and left overnight at 37°C. The next day, membranes were washed with low stringency wash buffer (2× SSC, 0.1% SDS) and high stringency wash buffer (0.1× SSC, 0.1% SDS) at 37°C and then washed with 2× SSC buffer at room temperature. Then, membranes were washed and blocked with the DIG Wash and Block Buffer Set (Roche, cat. no. 11585762001) according to the manufacture’s protocol. After blocking for 3 h at room temperature while shaking, anti-DIG-AP, Fab fragments (Roche, cat. no. 11093274910) in blocking buffer (1:15.000) were added to the membranes. CDP-star Development Reagent (Roche, cat. no. CDP-RO) was added to the membranes, and images were acquired using ChemiDoc-IT imaging system. Dual DIG-labelled DNA probes are listed in Table S1.
For detection of 2′Ome nucleotides, we used an adaptation of the RTL-Q method that was described by Dong et al. To accurately determine the exact location of the 2′Ome site on mature tRNA, a reversed primer downstream of the 2′Ome site (RD) and a reversed primer on the 2′Ome site (RU) were designed to the +1 and 0 nt downstream of the predicted 2′Ome nucleotide, respectively. The RT reaction was performed in two consecutive steps. First, a mixture of 20 ng RNA and 10 μM RD or RU primers was denatured at 70°C for 5 min and incubated at 42°C for 10 min as an initial annealing step. Then, a high (200 μM) or low (0.5 μM) concentration of dNTPs (Promega, cat. no. U1511), 200 U M-MLV reverse transcriptase (Promega, cat. no. M1705), and 20 U recombinant RNasin ribonuclease inhibitor (Promega, cat. no. N2515) was added to the RT reaction. The RT reaction was incubated at 42°C for 90 min, followed by incubation at 75°C for 15 min. When a 2′Ome site is present, the extension of the RD primer pauses at this site when low dNTP concentrations are used, whereas the RU primer does not. Primer extensions are not affected by 2′Ome sites when performing RT at high dNTP concentrations. The differences in RT products were quantified by SYBR green-based qPCR. The EMF was calculated using the following formula. EMF = (Ct Low dNTP RD – Ct High dNTP RD) – (Ct Low dNTP RU – Ct High dNTP RU) EMF >0 means that methylation is present. EMF ≤ 0 means that no methylation is present. The sequence of the human precursor tRNA (pre-tRNA) was obtained from publicly available RNA-seq data performed by Gogakos et al. RT primers were designed around the predicted 2′Ome site. One reverse primer was designed upstream of the possible 2′Ome site (RU) and one downstream of the 2′Ome site (RD). One forward primer (FW) was used for both RU and RD. The same RTL-Q conditions were used as for mature tRNA. All primer sequences are provided in Table S1.
HUAFs were cultured on coverslips and transfected with GM-ctrl or GM-113-6 for 24 h. For collagen staining, cells were fixed in Zinc Formal-Fixx (Thermo Fisher Scientific, cat. no. 6764255) for 30 min and washed with PBS. Collagen was visualized with a picrosirius red staining. For αSMA staining, cells were fixed in 4% PFA for 15 min and washed in PBS. An antibody against αSMA, 1A4 (Dako M0851, 1:1000), and a secondary antibody Alexa Fluor 555 DαMouse (Invitrogen A31570, 1:1000) were used to visualize αSMA. Hoechst (34580, 1:1,000) was used to stain the nuclei. Fiji was used to perform immunohistochemistry and immunofluorescence analysis. The area was divided by the total amount of nuclei. The integrated density, which is the sum of values of the pixels, was calculated and divided by the total amount of nuclei (intensity). Primer sequences for COL1A1 and αSMA (smooth muscle α-2 actin [ACTA2]) are provided in Table S1.
Human artery samples were collected at the Leiden University Medical Center. Collection, storage, and processing of the samples were performed in compliance with the Medical Treatment Contracts Act (WGBO, 1995) and the Code of Conduct for Health Research using Body Material (Good Practice Code, Dutch Federation of Biomedical Scientific Societies, 2002) and the Dutch Personal Data Protection Act (WBP, 2001). Human IMAs were harvested during elective coronary bypass surgery from seven patients with coronary artery disease. Only surplus tissue was collected. These samples were anonymized, and no data were recorded that could potentially trace back to an individual’s identity. Vessels were left to rest overnight in culture medium (DMEM Glutamax with 10% heat FCSi and 100 U penicillin and 100 μg streptomycin per mL) at 37°C and 20% oxygen and subsequently cultured for 24 h, either at control conditions (20% oxygen and culture medium) or at hypoxia + starvation conditions (1% oxygen and FCS reduced to 0.5%). Samples were snap frozen and stored at −80°C. Frozen tissues were crushed in liquid nitrogen, and total RNA was isolated from tissue powder by standard TRIzol-chloroform extraction as described above.
HUAFs and PMFs were treated with KN-93 for 48 h and then transfected with GM-113 or GM-AF25, respectively, or a negative GM-ctrl, as described above. After 24 h of transfection, cells were treated with 5 μg/μL actinomycin D (Sigma Aldrich, cat. no. A9415) to inhibit novel RNA transcription for 1 h. The decline of mature tRNA and the tRF levels over time were quantified by qPCR. Relative AF357425 and SNORD113-6 expression before and after 1 h actinomycin D treatment is shown Figure S8.
Results are expressed as mean ± standard error of the mean (SEM). An unpaired t test was performed to compare single treatment with the control. As knockdown efficiency varied per experiment, for these experiments a paired t test was performed to compare each treatment with its own control, within each individual experiment. Graphpad (v.9.0.1) was used to perform all statistical analysis. p <0.05 was considered significant, and p < 0.1 was considered a trend. | true | true | true |
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PMC9547160 | Giancarlo Marra,Marco Oderda,Giorgio Calleris,Alessandro Marquis,Federica Peretti,Andrea Zitella,Marco Moschini,Rafael Sanchez-Salas,Robert Jeffrey Karnes,Burkhard Kneitz,Martin Spahn,Donatella Pacchioni,Paolo Gontero | Ki-67, topoisomerase IIα and miR-221 have a limited prostate cancer risk stratification ability on a medium-term follow-up: results of a high-risk radical prostatectomy cohort | 01-09-2022 | Risk stratification,radical prostatectomy (RP),miR-221,Ki-67,topoisomerase IIα | Background Currently, no biomarkers are able to differentiate lethal from relatively indolent prostate cancer (PCa) within high-risk diseases. Nonetheless, several molecules are under investigation. Amongst them, topoisomerase-II-alpha (TOPIIA), Ki67 and miR-221 showed promising results. Our aim was to investigate their prognostic role in the context of biochemical recurrence (BCR), clinical recurrence (CR) and PCa-related death (PcD). Methods We included 64 consecutive cM0 high-risk PCa [prostate specific antigen (PSA) >20 ng/mL or Gleason Score (GS) >7 or cT >2] undergoing radical prostatectomy (RP). Changes in miR-221 expression and alternative splicing were determined using microarrays. Immunohistochemical determination of Ki67 and TOPIIa were performed using monoclonal antibody MIB-1 and 3F6 respectively. Cox proportional-hazards regression models were used to predict BCR and CR as multivariate analysis. BCR and CR were defined as three consecutive rises in PSA and PSA >0.2 ng/mL and histologically-proven local recurrence or imaging positive for distant metastasis respectively. Results We included 64 men. Mean pre-operative PSA was 26.53 (range, 1.3–135); all GSs were ≥7 and pT was ≥ T3 in 78.13%. Positive margins and lymph-nodes were present in 42.19% and 32.81% respectively. At a mean follow-up of 5.7 years (range, 1.8–12.5), 42.18% experienced BCR (n=27), 29.68% CR (n=19) and 7.81% PcD (n=5). On univariate analysis positive nodes (<0.01), seminal vesicle invasion (0.02) and miR-221 downregulation (P=0.03), but not Ki67 and TOPIIA (both P>0.5) were associated with BCR whereas only PSA (P<0.01), seminal vesicle invasion (P<0.01) and positive nodes (both P<0.01) were linked to CR. No parameters predicted PcD (all P>0.05) or BCR and CR on multivariate analysis (all P>0.05 - miR-221 HR 0.776; 95% CI: 0.503–1.196 for BCR and HR 0.673; 95% CI: 0.412–1.099 for CR). Limitation of the study include its small sample size and limited follow-up. Conclusions TOPIIA, Ki-67 and miR-221 may not predict BCR, CR or PcD in high-risk PCa patients who underwent RP at a medium-term follow-up. Longer follow-up and larger cohorts are needed to confirm our findings. | Ki-67, topoisomerase IIα and miR-221 have a limited prostate cancer risk stratification ability on a medium-term follow-up: results of a high-risk radical prostatectomy cohort
Currently, no biomarkers are able to differentiate lethal from relatively indolent prostate cancer (PCa) within high-risk diseases. Nonetheless, several molecules are under investigation. Amongst them, topoisomerase-II-alpha (TOPIIA), Ki67 and miR-221 showed promising results. Our aim was to investigate their prognostic role in the context of biochemical recurrence (BCR), clinical recurrence (CR) and PCa-related death (PcD).
We included 64 consecutive cM0 high-risk PCa [prostate specific antigen (PSA) >20 ng/mL or Gleason Score (GS) >7 or cT >2] undergoing radical prostatectomy (RP). Changes in miR-221 expression and alternative splicing were determined using microarrays. Immunohistochemical determination of Ki67 and TOPIIa were performed using monoclonal antibody MIB-1 and 3F6 respectively. Cox proportional-hazards regression models were used to predict BCR and CR as multivariate analysis. BCR and CR were defined as three consecutive rises in PSA and PSA >0.2 ng/mL and histologically-proven local recurrence or imaging positive for distant metastasis respectively.
We included 64 men. Mean pre-operative PSA was 26.53 (range, 1.3–135); all GSs were ≥7 and pT was ≥ T3 in 78.13%. Positive margins and lymph-nodes were present in 42.19% and 32.81% respectively. At a mean follow-up of 5.7 years (range, 1.8–12.5), 42.18% experienced BCR (n=27), 29.68% CR (n=19) and 7.81% PcD (n=5). On univariate analysis positive nodes (<0.01), seminal vesicle invasion (0.02) and miR-221 downregulation (P=0.03), but not Ki67 and TOPIIA (both P>0.5) were associated with BCR whereas only PSA (P<0.01), seminal vesicle invasion (P<0.01) and positive nodes (both P<0.01) were linked to CR. No parameters predicted PcD (all P>0.05) or BCR and CR on multivariate analysis (all P>0.05 - miR-221 HR 0.776; 95% CI: 0.503–1.196 for BCR and HR 0.673; 95% CI: 0.412–1.099 for CR). Limitation of the study include its small sample size and limited follow-up.
TOPIIA, Ki-67 and miR-221 may not predict BCR, CR or PcD in high-risk PCa patients who underwent RP at a medium-term follow-up. Longer follow-up and larger cohorts are needed to confirm our findings.
Prostate cancer (PCa) remains the commonest non-skin cancer solid neoplasm amongst men, with the majority of diseases being discovered at an early indolent stage (1,2). However, due to its high incidence, it represents the second cause of male cancer-related deaths, claiming the need of a prognostic marker able to better identify aggressive diseases, potentially lethal, especially if undertreated (1). Currently amongst the top four causes of cancer related deaths, PCa is the only neoplasm lacking such a tool, unlike breast, colorectal and non-small cell lung cancer, for which targeted therapies in selected subgroups of patients led to significant survival improvements (1,3-5). In the intrinsic heterogeneity of PCa, high risk cancers are indeed the most relevant subgroup in which a potential biomarker may be tested to verify its predicting ability. To date, PSA, tumour stage and GS remain the major instruments to predict the risk of recurrence after radical prostatectomy (RP). Despite their proved ability to differentiate low-, intermediate- and high-risk diseases, no tools exist to further define aggressive diseases. Risk stratification is currently based on clinical parameters only, leading to a clinically defined uniform risk class in which, however, risk of dying for PCa competing causes after radical treatment can significantly differ from one case to another, with reported 10-year rates ranging from 9% up to 61% (6,7): this claims an absolute need of accounting for inter-individual outcomes to enhance disease-free and cancer-specific survival. With this aim, several biomarkers are currently under investigation. Hence, prognostic markers able to predict either the risk of biochemical recurrence (BCR) and clinical recurrence (CR) or the risk of PCa-related death (PcD) would revolutionize the treatment allocation pathway, allowing more precise risk-based discrimination. MicroRNAs (miRNA) are non-coding RNA molecules able to regulate gene expression by hybridizing with target mRNA complementary sequences. Their alteration has been shown to occur in both in vivo and in vitro cancerous cells, making them ideal cancer biomarkers and/or therapeutic targets (8,9). Above all, miR-221 has been suggested as a potential PCa biomarker, being inversely associated with the risk of PCa recurrence (8,9). Many microRNAs have been studied concerning PCa, including miR-21 (8,10), miR-141 (8), miR-205 (11), miR-214 (11), miR-222 (10,12,13) and others. Nonetheless, bioavailability is not always promising for their introduction in clinical practice and evidence is sometimes contrasting. Amongst them, miR-221 shows the most promising evidence, based on PCa cells in vitro studies which suggest its involvement in several molecular pathways such as androgen-dependent cell growth and development of CRPC phenotype (12,14,15), PCa migration and invasion (16,17), and inhibition of several cyclin-dependent kinases complexes, including those inducing apoptosis (13,18). Furthermore, miR-221 levels can be obtained from blood, prostatic tissue and prostatic secretion, thus providing easily available samples (19). Disagreement characterises the early clinical evidence. Three studies found no association amongst miR-221 downregulation and either BCR or CR (10,20), whilst four demonstrated significant correlations (8,9,16,17). Amongst molecules that have been incorporated in models predicting the risk of PcD, nuclear-based protein Ki-67, expressed in cells undergoing proliferation as an expression of DNA synthesis, and DNA binding enzyme topoisomerase-2α (TOPIIA) also appear as promising tools (21,22). The former yielded good correlation with BCR and enhanced D’Amico risk stratification predicting ability of post-RP outcomes (21) and the latter correlated with risk of systemic PCa progression (22). In the present study we report the results concerning the analysis of miR-221, and, given previous studies from others and our group reporting promising results, Ki-67 and TOPIIA prognostic role in men with high risk PCa who underwent RP. We present the following article in accordance with the REMARK reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-21-628/rc) (23).
After receiving institutional review and ethics board approval, we retrospectively collected data of 64 consecutive patients who underwent RP with extended lymph node dissection for high risk PCa at San Giovanni Battista Hospital, Turin, Italy, between 2003 and 2011. Patients were followed up with PSA measurements every three months for the first year, every six months in the following four years and yearly thereafter. Clinical visits were performed every six months for the first two years and then yearly. In case of PSA rise and/or suspicion of recurrence cases were discussed at a multidisciplinary meeting including Urologists, Oncologists, Radiologists, Radiotherapists and Nuclear Medicine Specialists and subsequently managed (imaging/staging) and/or treated (surveillance/adjuvant/salvage treatments) depending on the panel’s recommendation, in line with the EAU guidelines for prostate cancer.
Inclusion criteria were presence of high risk PCa, confirmed by the RP specimen and defined according to D’Amico Criteria [Gleason Score (GS) ≥8 and/or prostate specific antigen (PSA) >20 ng/mL and/or cT ≥3a]. Neo-adjuvant and adjuvant hormonal therapy as well as adjuvant radiotherapy were not considered as exclusion criteria. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the institutional ethics board of San Giovanni Battista Hospital (No. 112/106/70/2017) and individual consent for this retrospective analysis was waived.
All men received a negative pre-operative clinical staging including PSA, digital rectal examination, abdominal computed tomography (CT) and bone scans. Other recorded clinical variables included age, height, weight, BMI, follow-up PSA measurements, number and percentage of positive nodes (confirmed by histological analysis), cTNM, Charlson Comorbidity Index and American Society of Anaesthesiologists (ASA) score.
BCR and CR were defined as three consecutive rises in PSA and PSA being >0.2 ng/mL after RP and histologically proven local recurrence or bone or CT scan distant metastasis respectively. PcDs were verified by phone interviews. Our primary endpoint was to evaluate miR-221, Ki-67 and TOPIIA their prognostic role in the context of BCR, CR and PcD by comparing the expression of each marker in those experiencing BCR and/or CR and/or PcD versus those who did not.
Pathological macro-dissection was performed according to the Stanford protocol. After initial diagnostic evaluation all RP specimens were reviewed by a senior uro-pathologist and index lesions (defined as the largest cancer focus and/or focus with the highest GS) were contoured. No immunostaining was performed at this stage. After pathological examination, paraffin-embedded tissue was analysed for miR-221, Ki-67 and TOPIIA levels.
Changes in miRNA expression levels, alternative splicing, or expression of mRNAs were determined using microarrays (e.g., GeneChip® Exon Arrays, Affymetrix) and quantitative RT-PCR methods. Total RNA Extraction Kit (Applied Biosystems) was used to extract totalRNA as described previously (9). Quality and concentration of extracted RNA was determined with a BioAnalyzer (Agilent). cDNA was synthesized from total RNA with stem-loop reverse transcription primers for miR-221 according to the TaqMan MicroRNA Assay protocol. TaqMan microRNA assay kits and an Applied Biosystems 7900HT system were used for quantification of microRNA in tissue samples according to the manifacturer’s protocol (Applied Biosystems). For normalization and subsequent calculation of relative miR expression we used miR-151-3p expression and the comparative DCt-method. Mean Ct was determined from triplicate PCRs.
Immunostaining was performed as previously described (21,22). The monoclonal antibody MIB-1 (Immunotech, Marseilles, France; 1:400 dilution) using a standard avidin-biotin complex method to determine cells positivity was used for Ki-67 staining. An automatic stainer (BioTek, Ventana Medical Systems, Tucson, AZ, USA) was used for slides processing. Hematoxylin dilution was used as nuclear counterstain. MIB-1 percentage of positive nuclear area (MIB-1 index) was obtained with the Quantitative Proliferation Index program of the CAS 200 image analyser. Total optical density of nuclei expressing the antigen that reacts with MIB-1 (the brown chromogen diaminobenzidine) was divided by the total optical density of all measured nuclear images. Monoclonal antibodies 3F6 (Novacastra, Benton Lane, UK, 1:100 dilution) was used for TOPIIA immunostaining. Dako Advance polymer-based detection system (Dako, Carpenteria, CA, USA) was used for stain performance. Slide Scanner and Immunostaining Score Software (Bacus Laboratories, Inc., Lombard, IL, USA) were used for slides scanning and to obtain measurements of the 3F6 (total and immune-reactive nuclear area of the invasive tumour component within the index lesions). MIB-1 and 3F6 immunostaining were expressed as the percentage of invasive tumour total nuclear area that stained positively [labeling index (LI)]. After digital imaging analysis all slides were visually reassessed by dedicated cytotechnologists in relation to the MIB-1 and 3F6 LIs to guarantee correct quantification. Ki-67 and TOPIIA were defined as the percentage of PCa cells nuclear area displaying MIB-1 36F staining, irrespectively of their intensity.
Different distributions of all independent prognostic variables recorded were compared according to presence or absence of BCR, CR and PcD using Wilcoxon non-parametric test for dichotomic and Mann Whitney U-test for continuous variables. For univariate analysis Kaplan-Meyer curves were plotted for each independent variable (age, PSA, GS, positive and percentage of positive nodes, surgical margins status, height, weight, BMI, Charlson Score, Ki-67, topoisomerase II and miR-221) according to BCR, CR and PcD respectively. Cox proportional-hazards regression models to predict Biochemical and clinical recurrence (CR) as multivariate analysis. Statistics were conducted using SAS ver. 9.4 for Windows (SAS Institute, Cary, NC, USA) software package. P values of ≤0.05 were considered significant.
Baseline clinical characteristics are shown in Table 1, whereas Table 2 reports baseline pathological features. Mean pre-operative PSA and age were 26.5 (range, 1.3–135) and 68 (range, 53–79), with clinical stage being organ confined in 82.3% (n=51) and biopsy Gleason Score (bGS) being ≥7 in 92.1% (n=58). RP specimen pathological features were extracapsular extension (≥ pT3) in 78.1% (n=50) (pT4=3.1%, n=2 and SVI =39.1%, n=25), all being GS ≥7. Rates of positive surgical margins and lymph-nodes were 42.2% (n=27) and 32.8% (n=21) respectively. Additional PCa treatments including adjuvant and neo-adjuvant ADT and radiotherapy are displayed in Table 3. At a mean follow-up of 5.7 years (range, 1.8–12.5), 42.2% of the cohort (n=27) experienced BCR, and 29.7% had CR (n=19), of whom 7 locally and 12 in distant sites; overall death was 9.4% (n=6), 5 men died because of PCa (PcD =7.8%) and 1 for other causes. Kaplan-Meyer curves for BCR and CF are shown in Figure 1. On univariate analysis (Table 4) number of positive nodes (<0.01), positive nodes status (P<0.01), seminal vesicle invasion (0.02) and miR-221 downregulation (P=0.03) were significant predictors of BCR. However, only PSA (P<0.01), seminal vesicle invasion (P<0.01) and positive nodes number and status (both P<0.01) were able to predict CR. Ki-67 and TOPIIA levels were not associated with enhanced risk of BCR and/or CR (all P>0.5). Amongst investigated parameters, none was able to predict PcD (all P>0.05). On multivariate analysis for BCR and CR (Table S1), none of the investigated variables was able to independently predict PCa outcomes (all P>0.05).
In the current study we evaluated miR-221, Ki-67 and TOPIIA prognostic ability in a high risk PCa cohort with a mean follow-up of 5.7 years. miR-221 was able to predict BCR but not CR and PcD, whereas no correlation of the latter three with Ki-67 and TOPIIA levels were found. To date, PSA, tumour stage and GS remain the major instruments to predict the risk of recurrence after RP. Despite their proved ability to differentiate low, intermediate and high-risk diseases, no tools exist to further define aggressive PCa. Amongst those with the greatest malignant potential, we are not able to predict which patients will remain PCa-free and which patients will develop recurrence after primary curative treatment, possibly benefitting from adjuvant or more aggressive first line approaches. As shown in our cohort, with 42.18% BCR, 29.68% CR and 7.81% PcD, high risk PCa yields significant progression rates. Reported 5 years BCR and PcD range from 37 up to 65% and from 1 up to 7% respectively (24): this claims an absolute need of accounting for inter-individual outcomes to enhance disease-free and cancer specific survival. With this aim, several biomarkers are currently under investigation. Ki-67 and TOPIIA have been assessed in several malignancies, including breast (25-27), lung (28,29) and other major neoplasms (30-33). TOPIIA is involved with cell proliferation, with a well-characterized role in the DNA repair. Increased TOPIIA expression has been associated with enhanced risk of PCa progression through an increase in androgen-related signalling (34). Conversely, whilst being associated with cell proliferation, the biological function of Ki-67 remains unknown. Many series highlighted TOPIIA high levels correlate with GS (35-40), preoperative PSA (37,40) and surgical stage (36); a few of these works also proved its independent ability in predicting BCR (22,35,37), and, in two cases, its association with a decreased survival after PCa radical treatment (22,35). Ki-67 was recently validated as an independent predictor of BCR in a large multi-centre cohort of 3,123 men (HR =1.19; P=0.019) (41). Smaller studies proved its ability in predicting PcD as well (21,42). A work from the Mayo Clinic found Ki-67 as an independent predictor of PcD; each 1% increase in Ki-67 expression related to a 12% growth in cancer-specific death (P<0.001) (21). As in the current study, Karnes and colleagues tested both TOPIIA and Ki-67 in prognostic models (22). However, in their work, the staining of TOPIIA and Ki-67 were significantly different for PCa experiencing systemic progression after RP compared to those who did not (P<0.001). Further sub-analysis assessed prognostic ability in relation to ERG, an oncogenic protein which binds other proteins to modulate cytoskeleton organization, cell migration and protein degradation. ERG gene rearrangement with common recurrent transmembrane protease serine 2 (TMPRSS2) causes its overexpression. This seems to be an early step of PCa genesis and, although its role remains unclear, it has been associated with higher GS, stage and PCa aggressiveness (22,43). In men without ERG translocation, TOPIIA had a significantly better prognostic ability than Ki-67. On the contrary, when ERG translocation was present, TOPIIA and Ki-67 had no predictive value, suggesting their prognostic role may vary depending on ERG status (22). This has been recently confirmed in a large RP cohort (43). Although GS, pre-op PSA and positive lymph nodes were associated with a higher risk of biochemical and/or CR, in our study, no significant correlations with BCR, CF and PcD were found for either Ki-67 or TOPIIA. Indeed, the ERG status may account as an important influencing factor. In this sense the relatively small number of our validation cohort may even have been reduced by the presence of ERG(+) men, on whom Ki-67 and TOPIIA do not show any significant predictive ability. Unfortunately, we did not assess ERG translocation and no concrete statements can be made regarding this hypothesis. It is our opinion that future studies on Ki-67 and TOPIIA need to consider ERG status to account for possible biases deriving from its role, and to further clarify its mechanism of action. Low cost and rapid assessment, especially for Ki-67, are certainly considerable advantages that may derive from their large-scale use if prognostic ability is confirmed by future research. A retrospective analysis of ERG translocation has been planned in our cohort and will likely shed light on our current results. Differently from Ki-67 and TOPIIA, miRNA are relatively younger molecules, whose association with cancer was first suggested in 2002 for chronic lymphocytic leukemia (44). Many microRNAs have been studied concerning PCa, including miR-21 (8,10), miR-141 (8), miR-205 (11), miR-214 (11), miR-222 (10,12,13) and others. Amongst them, miR-221 shows the most promising evidence, based on PCa cells in vitro studies which suggest its involvement in several molecular pathways such as androgen-dependent cell growth and development of CRPC phenotype (12,14,15), PCa migration and invasion (16,17), and inhibition of several cyclin-dependent kinases complexes, including those inducing apoptosis (13,18). Furthermore, miR-221 levels can be obtained from blood, prostatic tissue and prostatic secretion, thus providing easily available samples (19). Disagreement characterises the early clinical evidence, with some finding no association amongst miR-221 downregulation and either BCR or CR (10,20), whilst others demonstrating significant correlations (8,9,16,17,45). Nonetheless, works yielding negative results suffer from methodological limitations. In one study mean follow-up was shorter than 2 years, yielding to low BCR rates (20), whereas in the other, a significant proportion of men had GS ≤6 and no PSA or clinical and pathological TNM information being available. In our study, miR-221 downregulation was significantly associated with BCR on univariate analysis only but not when accounting for multiple risk factors on multivariate analysis. Also, miR-221 was not able to predict CR and PcD. Although it has been shown that different procedural methods such as macro-dissection or miRNA extraction may influence results (20,46), this occurrence is unlikely as we adopted the same study protocol and miRNA extraction of others showing miR-221 significantly and well predicts adverse PCa outcomes (9,16). Conversely, other reasons may contribute to the overall absence of significant results in our cohort. Despite approaching six years, our follow-up was relatively short and the number of patients was low overall and compared to others (9,16). Low CR and PCa death rates may have also contributed to obtain non-significant results. Overall, well established risk factors such as GS, pathological stage, number of positive nodes, positive surgical margins and PSA did not have any correlation with biochemical or CR on multivariate analysis, arguing for the need of a longer follow-up and for a higher number of patients. Other possible limitations that may have hampered the results comprise the absence of hereditary PCa records and the inclusion of men undergoing neo-adjuvant, adjuvant and salvage treatments, which may modify RP histological features (47). Furthermore, considering all three investigated molecules appear to be involved in the androgenic pathway (9,22,34), it is not known which effect hormone treatments may have had on their expression. As these are frequently used in high-risk cohorts, the effect of salvage therapies on future biomarker levels also needs to be elucidated in the future. Finally, the assessment of a high-risk cohort is a point of strength of this study. In this group, RP alone has not proved superior to observation in reducing mortality (48). This still represents an unsolved issue as we are not able to discriminate patients who will possibly progress and die because of PCa, even after RP has been performed. Rather than a diagnostic marker that risks to enhance overtreatment, we need a prognostic marker able to predict the outcomes. Currently, we are performing analysis using a large high-risk cohort with a >10 years follow-up to evaluate Ki-67, TOPIIA and miR-221 ability in predicting PcD and metastasis. New analysis of the current cohort with has also been planned as a longer follow-up is indeed needed to draw stronger conclusions (9). Also, efforts must be made in increasing our genomic knowledge of PCa, as it is for breast and other cancers. In this sense “real-world” clinical-genomic database and platforms are being created and are already available to enhance high risk and advanced PCa characterisation, paving the way towards precision oncology and personalised care (49,50).
TOPIIA and Ki-67 did not yield any ability in predicting BCR, CR or PcD in high-risk PCa patients who underwent RP. miR-221 was able to predict BCR on univariate analysis only, and did not show any prognostic ability in regard to CR and PcD. Negative results may derive from a relatively short follow-up and a low number patients and events in our cohort. Further large, well-designed studies with appropriate follow-up are ongoing and needed to evaluate the ability of the investigated biomarkers in predicting risk of BCR, CR and PcD after RP in high-risk PCa.
The article’s supplementary files as 10.21037/tau-21-628 10.21037/tau-21-628 10.21037/tau-21-628 10.21037/tau-21-628 | true | true | true |
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PMC9547168 | Sheng Xue,Hanxu Guo,Shibo Wei,Yuan Song,Junfeng Huang,Shuo Deng,Qingwen Li,Wenyong Li | Identification of a combined lncRNA prognostic signature and knockdown of lncRNA MANCR to inhibit progression of clear cell renal cell carcinoma by bioinformatics analysis | 01-09-2022 | Clear cell renal cell carcinoma (ccRCC),mitotically-associated lncRNA (MANCR),prognosis | Background Long non-coding RNAs (lncRNAs) have become potential therapeutic targets or promising prognostic biomarkers in cancers. However, individual gene does not show sufficient prognostic value for clear cell renal cell carcinoma (ccRCC). Therefore, this study aims to develop a combined prognostic lncRNA signature to the prognosis of ccRCC. Methods The transcriptome profiling data for confirmed ccRCC cases were obtained from The Cancer Genome Atlas (TCGA; https://portal.gdc.cancer.gov/). The prognostic significance, survival time and diagnostic effectiveness of the lncRNAs in ccRCC was evaluated using Kaplan-Meier method, the log-rank test and receiver operating characteristic (ROC) curves, respectively. The area under the ROC curve (AUC) of the 4 lncRNAs was also performed. The expression of mitotically-associated lncRNA (MANCR) was measured in ccRCC cells or tissues by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Both Colony formation assays and Cell Counting Kit-8 (CCK-8) assay was conducted to detect the proliferation of both 786-O and SN12C cells. For apoptosis detection, flow cytometry in both 786-O and SN12C cells was performed. For migration of 786-O and SN12C cells detection, wound healing and transwell assays were performed. Results A total of 1,567 differentially expressed lncRNAs in ccRCC were discerned with 1,340 upregulation and 227 downregulation. Furthermore, a 4-lncRNA signature (FIRRE, MANCR, AC103706.1, and AC018648.1) model was obtained that showed good performance in the prognosis of ccRCC. Gene Ontology (GO) analysis showed that these protein-coding genes (PCGs) were mainly enriched in ATPase activity, catalytic activity, and acting on RNA protein serine/threonine kinase activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that PCGs were mainly involved in endocytosis, oocyte meiosis and spliceosome. In addition, we revealed that MANCR was highly expressed in ccRCC cells and tissues and downregulation of MANCR inhibited cell proliferation and migration. In contrast, apoptosis of 786-O and SN12C cells was promoted with MANCR suppression. Conclusions A 4-lncRNA prognostic model that presented good performance for prognosis of ccRCC patients was established. Knockdown of MANCR inhibited cell proliferation and migration, and promoted apoptosis of 786-O and SN12C cells, suggesting that a 4-lncRNA signature model might be an essential for ccRCC prognosis. | Identification of a combined lncRNA prognostic signature and knockdown of lncRNA MANCR to inhibit progression of clear cell renal cell carcinoma by bioinformatics analysis
Long non-coding RNAs (lncRNAs) have become potential therapeutic targets or promising prognostic biomarkers in cancers. However, individual gene does not show sufficient prognostic value for clear cell renal cell carcinoma (ccRCC). Therefore, this study aims to develop a combined prognostic lncRNA signature to the prognosis of ccRCC.
The transcriptome profiling data for confirmed ccRCC cases were obtained from The Cancer Genome Atlas (TCGA; https://portal.gdc.cancer.gov/). The prognostic significance, survival time and diagnostic effectiveness of the lncRNAs in ccRCC was evaluated using Kaplan-Meier method, the log-rank test and receiver operating characteristic (ROC) curves, respectively. The area under the ROC curve (AUC) of the 4 lncRNAs was also performed. The expression of mitotically-associated lncRNA (MANCR) was measured in ccRCC cells or tissues by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Both Colony formation assays and Cell Counting Kit-8 (CCK-8) assay was conducted to detect the proliferation of both 786-O and SN12C cells. For apoptosis detection, flow cytometry in both 786-O and SN12C cells was performed. For migration of 786-O and SN12C cells detection, wound healing and transwell assays were performed.
A total of 1,567 differentially expressed lncRNAs in ccRCC were discerned with 1,340 upregulation and 227 downregulation. Furthermore, a 4-lncRNA signature (FIRRE, MANCR, AC103706.1, and AC018648.1) model was obtained that showed good performance in the prognosis of ccRCC. Gene Ontology (GO) analysis showed that these protein-coding genes (PCGs) were mainly enriched in ATPase activity, catalytic activity, and acting on RNA protein serine/threonine kinase activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that PCGs were mainly involved in endocytosis, oocyte meiosis and spliceosome. In addition, we revealed that MANCR was highly expressed in ccRCC cells and tissues and downregulation of MANCR inhibited cell proliferation and migration. In contrast, apoptosis of 786-O and SN12C cells was promoted with MANCR suppression.
A 4-lncRNA prognostic model that presented good performance for prognosis of ccRCC patients was established. Knockdown of MANCR inhibited cell proliferation and migration, and promoted apoptosis of 786-O and SN12C cells, suggesting that a 4-lncRNA signature model might be an essential for ccRCC prognosis.
Clear cell renal cell carcinoma (ccRCC) is the second most common cancer of the urinary system after bladder cancer. It is the most common type which accounts for about 80% of renal cancer (1). In recent years, the incidence of ccRCC is increasing every year. It has been proved that ccRCC was usually insensitive to radiotherapy, chemotherapy, and immunotherapy. So far, surgery is the main treatment method for ccRCC (2). Around 60% of patients with ccRCC die within 1–2 years after diagnosis, and 30% of patients with ccRCC have developed distant metastasis by the time of diagnosis (3). Therefore, it is urgent to explore the novel effective biomarkers for the prognosis of ccRCC. At present, with the continuous understanding of the pathogenesis of ccRCC, important progresses have been made in the research of various molecular markers related to ccRCC prognosis, such as ferroptosis-related gene CHAC1, autophagy-related gene P4HB and glycolysis-related genes (4-6). However, these markers performed poorly in ccRCC prognosis. Therefore, biomarkers of prognosis evaluation for ccRCC patients deserved deep study. Long non-coding RNAs (lncRNAs) belongs to functional RNA molecules and the length of lncRNAs usually is more than 200 nucleotides. lncRNAs are important epigenetic regulators that control gene expression and affect diverse biological processes (7). They can participate in cell differentiation, growth development, stress response, disease development, and other biological processes via epigenetic regulation and biological information exchange. Studies have proved that lncRNAs are important molecular players in the regulation of various types of cancer progression (8), including that of ccRCC. An increasing number of studies have confirmed that abnormal expression of lncRNAs promoted or inhibited ccRCC development via regulating the proliferation, invasion, and migration of ccRCC. Such as, lncRNA DNAJC3-AS1 promoted ccRCC development via downregulating PRDM14 expression by sponging miR-27a-3p (9); lncRNA LINC00973 inhibited cancer immune via promoting the expression of Siglec-15 in ccRCC (10); and lncRNA SNHG16 decreased CDKN1A expression which will promote ccRCC development by regulating cell migration and invasion of ccRCC (11). These findings revealed that lncRNA plays crucial role in the progression of ccRCC. In fact, lncRNAs have been showed more potential prognostic value in different cancers owing to its widely regulation ability. Several lncRNAs have also been considered important prognostic parameters in ccRCC, such as lncRNA Fer1L4, LINC00460, and LncRNA SNHG17 (12-14). However, most of the members in the huge family of lncRNAs have not yet been studied. Therefore, it is necessary to identify more lncRNAs and clarify the function of lncRNAs to improve the prognostic assessment system of ccRCC. Recently, several prognostic model of lncRNA signature in ccRCC have been studied and the combined signature showed better performance in prognosis of ccRCC (15-17). Therefore, it will help to better perform prognostic assessment and precise treatment of ccRCC to screen key differentially expressed lncRNAs with a combined prognostic model. In the present study, differentially expressed lncRNAs were excavated and identified using The Cancer Genome Atlas (TCGA) high-throughput database data and a key ccRCC prognostic lncRNA signature was constructed, and the function of the key lncRNA in ccRCC was detected. We aimed to explore the useful lncRNA model for clinical judgment of ccRCC prognosis, and to supply new ideas for the research into the etiology and pathogenesis of ccRCC. We present the following article in accordance with the MDAR reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-22-527/rc).
In the present study, combined lncRNAs signature used for prognosis of ccRCC was established by bioinformatics analysis using the transcriptome profiling data from TCGA database. A 4-lncRNA signature (FIRRE, MANCR, AC103706.1, and AC018648.1) model with an area under the curve (AUC) value of 0.711 was obtained that showed good performance in the prognosis of ccRCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) assays were used to identify the pathways protein-coding genes (PCGs) involved in. The function of the key lncRNA MANCR from the combined lncRNAs signature was evaluated by downregulation of lncRNA MANCR in 786-O and SN12C cells.
Expression profiles of messenger RNA (mRNA) and lncRNAs of ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). The expression of mRNA and lncRNAs was analyzed by EdgeR on a HT-Seq platform, including 539 ccRCC tissues and 72 adjacent normal tissues. Matched clinical data from ccRCC patients were also downloaded from TCGA database. In the cohort, 611 patients were included, among whom 602 had intact survival data recorded. The clinicopathological indicators including stage (stage I–IV), pathologic_T (T1–T4), pathologic_N (N0–N3) and pathologic_ M (M0–M3). According to the annotation of the expression profiles from the National Center for Biotechnology Information (NCBI; https://www.ncbi.nlm.nih.gov/) and Ensembl (https://asia.ensembl.org/index.html0) databases, 33,800 mRNA and 14,142 IncRNAs were identified. For the differential expression of lncRNAs assay, a R language package DESeq was performed. And the parameter as follows: adjusted P<0.05 and absolute Log (2, Fold Change) >1. The IncRNAs with fold changes (FC) less than 1 were excluded. R Cluster Profiler package was used to conduct the GO and KEGG functional enrichment. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).
In order to pair the differentially expressed genes (DEGs) with survival data, the correlation analysis was performed based on the relevant clinical data from TCGA-kidney renal clear cell carcinoma (KIRC) database with a univariate Cox proportional hazards model. Briefly, the combined cases were input into the model and the P value was obtained. Then, based on the ranking of the P value, the top 4 IncRNAs were selected for further analysis. The hazard ratio (HR) was calculated in each significant lncRNA. The discrimination between real and prediction value was evaluated by the concordance index (C-index). The prognostic significance, survival time and diagnostic effectiveness of the lncRNAs in ccRCC was evaluated using Kaplan-Meier method, the log-rank test and receiver operating characteristic (ROC) curves, respectively. In addition, the area under the ROC curve (AUC) of the 4 lncRNAs was also used to further analysis. To better show the cases of ccRCC that are matched with IncRNAs, the risk curve, heatmap, and survival status figures were conducted.
In order to evaluate the co-expression relationships between the lncRNAs and PCGs, the Pearson correlation coefficient between the expression profiles of lncRNAs and PCGs was calculated. A Pearson correlation coefficient >0.40 indicated lncRNA-related PCGs.
The human ccRCC cell lines were purchased from the Procell Life Science&Technology Co., Ltd, including A498, ACHN, SN12C, 786-O, and 769-P. These cells were recovered, passaged and then cultured in Dulbecco’s modified Eagle medium (DMEM; Corning, Corning, NY, USA, R10-017-CV) containing 10% fetal bovine serum (FBS; Invitrogen, Carlsbad, CA, USA, 16000-044) and penicillin-streptomycin (Gibco, Grand Island, NY, USA, 15140122) in a humidified 5% CO2 atmosphere at 37 ℃. For cell transfection, 2×105 cells/well 786-O and SN12C cells were plated 6-well plates and cultured for 24 hours at 37 ℃ until the cell confluence reached at 70–90%. The cells were then transfected with lentivirus containing the short hairpin RNA (shRNA) of mitotically-associated lncRNA (MANCR) and the following experiments were conducted at 48 hours after transfection. The lentivirus containing shRNA of MANCR was purchased from Shanghai Yibeirui Biomedical Science and Technology Co., Ltd. The sequence of shRNA of MANCR as follows: (SH-114)-KD-1: GGAGATAGAGCACAGCCAT; (SH-114)-KD-2: GCTTGCTCTCACAGCCATT; (SH-114)-KD-3: CCGAGTGGCACTCATACAT.
Total RNA from the ccRCC cell lines with different treatment was extracted using TRIzol reagent (Sigma Aldrich, St. Louis, MO, USA, T9424-100 mL). Subsequently, complementary DNA (cDNA) was obtained by reverse transcription with 800 ng RNA using a commercial kit Hiscript QRT supermix for qPCR (+gDNA WIPER) (Vazyme, Beijing, China, R123-01). The relative expression of MANCR was performed in an ABI7500 instrument (Applied Biosystems, Waltham, MA, USA) using AceQ qPCR SYBR Green master mix (Vazyme, Beijing, China, Q111-02). The relative expression of MANCR was calculated by 2−∆∆Ct method with Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as the internal control. The primer sequences used for qRT-PCR were as follows: GAPDH, Forward: 5'-TGACTTCAACAGCGACACCCA-3', Reverse: 5'-CACCCTGTTGCTGTAGCCAAA-3' (antisense); and lncMANCR, Forward: 5'-TTGGGAGGCTGAGTCTAAGTGT-3', Reverse: 5'-GCGAGTGGTGAGTGGATGTG-3'.
Cell Counting Kit-8 (CCk-8; Dojindo, Kumamoto, Japan, ck04) was used to detect the cell proliferation with different treatment. Briefly, 100 µL cells (2,000 cells/well) were seeded in 96-well plates and then cells were incubated at 37 ℃ in a humidified 5% CO2 atmosphere for 0, 24, 48, and 72 hours, respectively. Subsequently, the wells were added with 10 µL of CCK-8 and incubated for 2 hours. The absorbance was measured by a microplate reader at 450 nm.
786-O and SN12C cells (500 cells per well) were seeded in 6-well plates and cultured at 37 ℃ in a humidified 5% CO2 atmosphere. The cells were harvested and fixed with 100% methanol after incubation for 14 days. Then, 0.1% (w/v) crystal violet was used to stain the cells and photographed with a microscope (CX41, Olympus) in bright field.
The 786-O and SN12C cells were cultured in DMEM (Corning, R10-017-CV) containing 10% FBS (Invitrogen, 16000-044). Then, the 786-O and SN12C cells were trypsinized in the logarithmic growth phase and resuspended in the complete medium. Subsequently, the cells (50,000 cells/well) were seeded in a 96-well plate and were incubated at 37 ℃ in a 5% CO2 incubator with a culture system of 100 µL/well. A scratch instrument was used to form a scratch at the lower center of the 96-well plate. Then, the serum-free medium was used to rinse the cells for 2–3 times. A low concentration serum (0.5%) medium was added and the cells were photographed at 0 hour. Subsequently, the cells were incubated at 37 ℃ in a 5% CO2 incubator for 12 hours. The migration of cells was scanned and the migration area was screened using cellomics (Thermo Fisher, Waltham, MA, USA).
Transwell assay was also used to detect cell migration. Briefly, the chamber was placed in a 24-well plate with 100 µL of serum-free medium and placed in the incubator for 1–2 hours. Then, 786-O and SN12C cells were seeded in the upper chambers of a transwell (Corning) without serum. Medium containing 30% FBS was placed in the lower chambers. Cells were stained with 400 µL crystal violet for 5 minutes after incubation at 37 ℃ in a 5% CO2 incubator for 24 hours. Finally, the images of the migrated cells were taken using an optical microscope.
The apoptosis rates of 786-O and SN12C cells were detected by flow cytometry using Annexin V-APC and PI Kit (SouthernBiotech, Birmingham, AL, USA, 10010-09). Briefly, the 786-O and SN12C cells were collected and then washed 2 times with phosphate buffer saline (PBS). Then, 5 µL annexin V-APC and 5 µL propidium iodide (PI) was used to stain the cells for 15 minutes. The cells were then resuspended to 1 mL with 1× apoptosis buffer after staining. Finally, 200 µL of cell suspension was added to the 96-well plate (3 duplicate wells in each group) and then transferred to a flow cytometer tube. The apoptosis of flow cytometry was detected by high-throughput flow cytometry (Millipore, Burlington, MA, USA, Guava easyCyte 6HT-2L).
Statistical analysis in the preset study was analyzed using the software GraphPad Prism 7.0 (GraphPad, San Diego, CA, USA) and SPSS 21.0 (IBM Corp., Armonk, NY, USA) with at least 3 biological repetitions in this study. AUC ≥0.7 indicated a good prognosis prediction for the prognostic model. This study aims to investigate the differentially expressed lncRNAs in ccRCC and established the combined lncRNAs prognosis prediction model. The training and validation samples for the development and validation of the lncRNAs based prognosis prediction model will be studies in the future study. Student’s t-test was performed to analyze the differences between two groups. With two-tailed P value <0.05 was defined as statistically significant.
In order to explore the differentially expressed lncRNAs in ccRCC, the transcriptome profiling data was downloaded from TCGA database and included 539 ccRCC tissues and 72 adjacent noncancerous renal tissues. A total of 1,567 differentially expressed lncRNAs in ccRCC were discerned with upregulation and 227 downregulation (Figure 1). Subsequently, FIRRE, MANCR, AC103706.1, and AC018648.1 were entered into the multivariate Cox proportional hazards model according to the ranking of the P value. RiskScore = (0.1744 × FIRRE expression value) + (0.2637 × AC103706.1 expression value) + (0.1869 × AC018648.1 expression value) + (0.1274 × MANCR expression value). All of them showed high-risk features, suggesting that high expression indicated that the shortened overall survival (OS) of patients. The C-index was 0.70 [95% confidence interval (CI): 0.66 to 0.74], which has significantly clinical value (P=5.44e-22). These results indicated that the FIRRE, MANCR, AC103706.1, and AC018648.1 cluster showed important clinical prognostic value.
Subsequently, the prognostic model of the FIRRE, MANCR, AC103706.1, and AC018648.1 cluster was evaluated in 530 ccRCC patients. These patients were divided into low-risk (n=265) and high-risk (n=265) groups with 0.964 as the cut-off value based on the median RiskScore (Figure 2A). The survival status of 530 patients in the training cohort according to the 4-lncRNA signature risk score showed that high risk score indicated lower survival time (Figure 2B,2C). Kaplan-Meier OS curve in high-risk groups showed that the 3-year OS was 65.0% (95% CI: 59.1% to 71.5%) and the 5-year OS was 46.0% (95% CI: 39.2% to 54.1%). In low-risk ccRCC patients, 86.4% (95% CI: 81.9% to 91.1%) 3-year OS and 79.4% (95% CI: 73.7% to 85.6%) 5-year OS were observed, suggesting that the 3- and 5-year OS of low-risk ccRCC were dramatically higher compared with these high-risk ccRCC patients (Figure 2D). In addition, a better performance of AUC value with 0.711 was obtained based on the ROC curve for 4-lncRNA signature model (Figure 2E). These results indicated that the prognostic model for the FIRRE, MANCR, AC103706.1, and AC018648.1 cluster showed good performance in the prognosis of ccRCC.
To elucidate the pathways the FIRRE, MANCR, AC103706.1, and AC018648.1 cluster is involved in, co-expression between the 4 lncRNAs and the PCGs was performed based on the Pearson correlation coefficients. A P value <0.05 was defined significantly associated with 4 lncRNAs. To further confirm the accurately prediction for the 4 lncRNAs model, GO and KEGG pathway enrichment were performed with 1,862 key PCGs (Pearson correlation coefficient >0.40 and P<1e-35). The GO analysis revealed that these PCGs were mainly enriched in ATPase activity and catalytic activity, and acting on RNA protein serine/threonine kinase activity (Figure 3A). The KEGG pathway analysis indicated that the key PCGs were mainly involved in endocytosis, oocyte meiosis, spliceosome, carbon metabolism, and cell cycle (Figure 3B). These results revealed that the essential PCGs significantly related to 4 lncRNAs might be participated in ccRCC progression.
To determine whether MANCR is involved in ccRCC development, MANCR expression was detected in ccRCC cells and tissues by RT-qPCR. The expression of MANCR was firstly detected in several ccRCC cell lines, including A498, ACHN, SN12C, 786-O, and 769-P cells. The results indicated that MANCR was highly expressed in A498, ACHN, SN12C, 786-O, and 769-P cells, with the highest expression in SN12C cells (Figure 4A). The expression of MANCR detected in ccRCC tissues indicated that compared with adjacent tissues, MANCR expression was upregulated in 5 ccRCC tissues was significantly upregulated in 2 paired ccRCC tissues (Figure 4B) which was consistent with the transcriptome data. Furthermore, we demonstrated that high expression of MANCR is positively related to the stage and pathologic_T (Table 1). For survival curve analysis, it was revealed that high expression paired with a lower survival probability (Figure 4C). These results suggested that MANCR might promote the ccRCC development.
To explore the function of MANCR in ccRCC, lentivirus carrying shRNA of MANCR (shLncMANCR-1, shLncMANCR-2, and shLncMANCR-3) were prepared and used to knockdown the expression of MANCR in 786-O and SN12C cells. MANCR expression was significantly downregulated following transfection with a lentivirus containing shLncMANCR-3 of MANCR both in 786-O (64.8%) and SN12C cells (75.2%) than that in control group (Figure 5A). Therefore, lentivirus carrying shLncMANCR-3 was selected for further study. CCK-8 assay indicated that MANCR suppression greatly inhibited the proliferation of both 786-O and SN12C cells compared with the control group (Figure 5B). Colony formation assays also confirmed the results which showed significantly proliferation capacity inhibition of both 786-O and SN12C cells with MANCR knockdown compared with control group (Figure 5C). In contrast, flow cytometry assay showed that compared with control group the apoptosis of both 786-O and SN12C cells was significantly promoted by suppressing MANCR expression (Figure 5D). These results demonstrated that knockdown of MANCR hindered cell proliferation and promoted apoptosis of 786-O and SN12C cells.
Subsequently, the function of MANCR on the migration of 786-O and SN12C cells was detected by both wound healing and transwell assays. The results indicated that the migration rate significantly decreased both in 786-O and SN12C cells when suppressing MANCR compared with the control group in wound healing assay (Figure 6A). The transwell assay showed that the number of both 786-O and SN12C cells with migration dramatically decreased when suppressing MANCR than that in the control group (Figure 6B). These results indicated that knockdown of MANCR inhibited the migration of 786-O and SN12C cells.
Currently, ccRCC is the most common pathological type of renal cell carcinoma and is mainly treated by surgery. The prognosis is poor because of most ccRCC patients have distant metastasis at the time of diagnosis. On one hand, ccRCC is insensitive to chemotherapy and radiotherapy. On the other hand, emerging treatments are currently ineffective and expensive, such as molecularly-targeted therapy and immunotherapy. Thus, it is really important to find key sensitive and specific molecular markers for the prognosis of ccRCC. Dysregulated lncRNAs have been shown to be involved in the occurrence and metastasis of tumors, suggesting that lncRNAs might be potential target for the prognosis and treatment in cancers. Therefore, it is urgent to develop a combined prognostic lncRNA signature with better performance for the prognosis of ccRCC. In the present study, a 4-lncRNAs prognostic model, which showed good performance for prognosis of ccRCC patients, was established. We demonstrated that MANCR was especially highly expressed in both ccRCC cells and tissues. Functionally, MANCR suppression inhibited cell proliferation and migration, and promoted apoptosis of 786-O and SN12C cells. The lncRNAs participated in the processes of epigenetic, transcriptional or post-transcriptional regulation which will lead the abnormal changes for various kinds of gene expression (18). Increasing numbers of studies have shown that lncRNA play crucial roles in the development of ccRCC via regulating cell proliferation, apoptosis, invasion, and migration (19). Many lncRNA have also been shown to participate in the pathogenesis of ccRCC, including lncRNA ADAMTS9-AS2, lncRNA AFAP1-AS1, and lncRNA Lucat1 (20-22). In addition, several lncRNAs have shown potential for prognostic assessment of ccRCC (23), such as lncRNA OTUD6B-AS1, lncRNA CCAT1, and lncRNA SNHG17 (13,24,25). Although previous studies have attempted to analyze association between lncRNA and the prognosis of ccRCC using risk scoring models., However, most of the studies only focus on the assessment for the prognosis of ccRCC from the perspective of the unique lncRNA. Recently, Zeng et al. constructed a 6-lncRNA-based risk score which could be used for ccRCC prognosis based on RNA-sequencing data (26). Dou et al. also constructed 7-metastasis-related genes that correlated with the prognosis with the metastasis-related lncRNA signature in ccRCC (27). Su et al. also showed that 3-key combined lncRNA signature was successfully used to predict poor prognosis in patients with ccRCC (28). In the present study, 1,567 differentially expressed lncRNAs in ccRCC were discerned with 1,340 upregulation and 227 downregulation. Subsequently, based on 4 lncRNA (MANCR, AC018648.1, AC103706.1, and FIRRE), awas used to establish a model that was further used to The model based on multivariate Cox regression analysis indicated that the OS of low-risk patients was greatly better than that in the high-risk patients. A good performance of the model was also obtained in predicting the OS of patients with ccRCC based on the AUC of the ROC curve. The accuracy of the model was also confirmed by the C-index. These results demonstrated that the 4-lncRNA risk score showed good performance for the prognosis of ccRCC patients. lncRNAs FIRRE and MANCR have been shown that they could participate in the development of cancers act as promoters. Multivariate Cox analysis in endometrial cancer patients indicated that highly FIRRE expression was considered as an independent risk factor for prognosis of endometrial cancer (29). Wang et al. showed that lncRNA FIRRE affected YOD1 expression which will promote gallbladder cancer progression via sponging miR-520a (30). Shen et al. indicated that cell proliferation and glycolysis of hepatocellular carcinoma was promoted by lncRNA FIRRE via regulating PFKFB4 expression (31). Liu et al. showed that lncRNA FIRRE promoted diffuse large B-cell lymphoma development by stimulating Smurf2 decay and stabilizing B-cell receptor (32). For lncRNA MANCR, it has been shown that MANCR promoted the malignant progression of lung adenocarcinoma, esophageal carcinoma, and prostate cancer (33-35). Upregulation of MANCR was also considered a biomarker for poor survival predication in gastric cancer (36) and potential diagnostic marker for breast carcinoma (37). However, the function of these 2 lncRNAs in ccRCC remains unclear. In the present study, MANCR was showed highly expressed in ccRCC cells and tissues. Further analysis showed that high expression of MANCR was positively related to the stage and pathologic_T and showed a lower survival probability. In addition, we found that knockdown of MANCR inhibited cell proliferation and migration and promoted apoptosis of 786-O and SN12C cells. These results suggested that MANCR might promote ccRCC development. On the other hand, the 4-lncRNA cluster was shown to be reliable for predicting the prognosis of ccRCC patients, and providing a reference for the effective formulation of individualized treatment plans and improving prognosis of patients.
In summary, we established a 4-lncRNAs prognostic model which showed good performance for prognosis assessment of ccRCC patients. We also demonstrated that knockdown of MANCR inhibited cell proliferation and migration, and promoted apoptosis of 786-O and SN12C cells, suggesting that MANCR promotes ccRCC progression. This model provides a theoretical basis for the prognosis evaluation of patients with ccRCC, and lncRNA MANCR in the model may be a new promising target for adjuvant therapy.
The article’s supplementary files as 10.21037/tau-22-527 10.21037/tau-22-527 10.21037/tau-22-527 | true | true | true |
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PMC9547189 | Mingyu Hu,Yangxi Zheng,Jiujiang Liao,Li Wen,Juan Cheng,Jiayu Huang,Biao Huang,Li Lin,Yao Long,Yue Wu,Xuan Ye,Yong Fu,Hongbo Qi,Philip N. Baker,Chao Tong | miR21 modulates the Hippo signaling pathway via interference with PP2A Bβ to inhibit trophoblast invasion and cause preeclampsia | 20-09-2022 | MT: Non-coding RNAs,preeclampsia,miR21,PP2A Bβ,hippo,trophoblast,invasion | Preeclampsia (PE) is a pregnancy-specific disorder attributed to deficient extravillous trophoblast (EVT) invasion into the uterus, but the mechanism of EVT invasion remains unclear. In this study, we found significantly elevated expression of microRNA 21 (miR21), which negatively regulates trophoblast invasion and migration, in preeclamptic placentae. Whole-genome RNA sequencing revealed that PPP2R2B, which encodes PP2A Bβ, and the Hippo pathway are downstream targets of miR21. The effects of miR21 on trophoblast mobility were abolished in LATS1T1079A/S909A and YAP-5SA mutants. Moreover, we found that PP2A Bβ dephosphorylates LATS1 via direct protein-protein interactions and thus modulates the phosphorylation and subcellular distribution of YAP. PPP2R2B overexpression ameliorated the miR21-induced LATS1-YAP phosphorylation and cytoplasmic sequestration of YAP, which resulted in the rescue of compromised trophoblast invasion and migration. The upregulation of placental miR21 abundance by placenta-specific nanoparticles loaded with agomir-miR21 during placentation interfered with PPP2R2B and activated the Hippo pathway in the placenta, leading to a PE-like phenotype. Thus, aberrant elevation of miR21 impairs EVT mobility by modulating the PP2A Bβ/Hippo axis, which is one of the causes of PE. | miR21 modulates the Hippo signaling pathway via interference with PP2A Bβ to inhibit trophoblast invasion and cause preeclampsia
Preeclampsia (PE) is a pregnancy-specific disorder attributed to deficient extravillous trophoblast (EVT) invasion into the uterus, but the mechanism of EVT invasion remains unclear. In this study, we found significantly elevated expression of microRNA 21 (miR21), which negatively regulates trophoblast invasion and migration, in preeclamptic placentae. Whole-genome RNA sequencing revealed that PPP2R2B, which encodes PP2A Bβ, and the Hippo pathway are downstream targets of miR21. The effects of miR21 on trophoblast mobility were abolished in LATS1T1079A/S909A and YAP-5SA mutants. Moreover, we found that PP2A Bβ dephosphorylates LATS1 via direct protein-protein interactions and thus modulates the phosphorylation and subcellular distribution of YAP. PPP2R2B overexpression ameliorated the miR21-induced LATS1-YAP phosphorylation and cytoplasmic sequestration of YAP, which resulted in the rescue of compromised trophoblast invasion and migration. The upregulation of placental miR21 abundance by placenta-specific nanoparticles loaded with agomir-miR21 during placentation interfered with PPP2R2B and activated the Hippo pathway in the placenta, leading to a PE-like phenotype. Thus, aberrant elevation of miR21 impairs EVT mobility by modulating the PP2A Bβ/Hippo axis, which is one of the causes of PE.
Preeclampsia (PE) is a leading complication of pregnancy characterized by new-onset hypertension and proteinuria at ≥20 weeks of gestation. This multisystem disorder affects up to 4%–5% of pregnancies worldwide and leads to a series of adverse perinatal outcomes that are mainly attributed to preterm delivery, which occurs secondary to maternal or fetal complications, intrauterine growth restriction (IUGR), and fetal death. PE is believed to be an ischemic placental disease that results from impaired spiral artery remodeling and inadequate trophoblast invasion., However, the pathophysiological mechanisms of dysfunctional migration and invasion of extravillous trophoblasts (EVTs) in PE remain to be elucidated. MicroRNAs (miRNAs) are a subset of 20- to 24-nucleotide-long noncoding RNAs that cause degradation of targeted genes or translational inhibition at the posttranscriptional level. miRNAs are involved in numerous important biological events, including placental development, tumorigenesis, and cardiac disease. Growing evidence indicates that dysregulation of miRNAs is correlated with trophoblastic dysfunction and PE development., Nevertheless, the role of placental miRNAs in the pathogenesis of PE remains unclear. Emerging studies have suggested that certain miRNAs, such as miR23a and miR199b, target protein phosphatase 2A (PP2A)., PP2A is a ubiquitously expressed and highly conserved serine threonine phosphatase that regulates biological functions by dephosphorylating core cellular molecules in many cellular processes, such as cell proliferation, cytoskeleton dynamics, and signaling pathways. The trimeric form of PP2A is an active holoenzyme complex composed of three subunits: scaffold (A), catalytic (C), and regulatory (B) subunits. The regulatory B subunit is the predominant regulator of the PP2A holoenzyme and determines the substrate specificity and intracellular localization of the enzyme. Previous research has demonstrated that the invasion of trophoblasts into the uterus and the development of the placenta are similar to tumorigenesis to a certain extent. Moreover, cytokine receptors participate in many inflammatory diseases, including PE, and are also involved in the pathogenesis of autoimmune diseases. Although PP2A has been intensively studied in cancer and autoimmune diseases, its role in placental development or pregnancy complications such as PE needs to be further explored. Increasing evidence has revealed that Hippo pathway proteins might be regulated by PP2A as its substrates. The mammalian Hippo pathway is a highly conserved pathway that regulates tissue homeostasis, organ size, and stem cell renewal and participates in tumor initiation or progression. The key components of the Hippo pathway kinase cascade include mammalian sterile 20-like kinase 1/2 (MST1/2), which phosphorylates and activates the downstream kinase large tumor suppressor 1/2 (LATS1/2) and the final transcriptional regulator Yes-associated protein 1 (YAP). YAP is a critical transcriptional coactivator that translocates between the cytoplasm and the nucleus; this protein can modulate target gene expression and thereby tumorigenesis and metastasis of most solid tumors. Once the cytoplasmic Hippo kinase module is active (Hippo ON), active MST1/2 (p-MST1Thr183/MST2Thr180) promotes phosphorylation of the LATS1/2 kinases (p-LATS1Thr1079 and p-LATS2Thr1041). Active LATS1/2 then phosphorylates YAP on various residues, and Ser127 (of YAP) is the predominant residue for its deactivation. In the absence of phosphorylated MST1/2 and LATS1/2, dephosphorylated YAP can translocate into the nucleus to act as a transcriptional coactivator. Furthermore, accumulating evidence has shown that LATS1 functions as a novel regulator in cellular homeostasis., YAP is also expressed in the human placenta, which suggests its involvement in placental development. Given that placental development shares substantial similarities with tumorigenesis, elucidation of the regulatory role of PP2A in the Hippo pathway in trophoblasts will contribute to our understanding of the etiology of PE. In this study, we found aberrant upregulation of miR21 expression in the placenta of pregnancies complicated by PE, which resulted in suppression of PP2A Bβ and thus decreased dephosphorylation of LATS1, and these effects ultimately lead to YAP hyperphosphorylation and sequestration in the cytoplasm. These data provide novel insights into the role of the miR21-PP2A Bβ-Hippo signaling axis in the pathogenesis of PE.
To investigate the involvement of miRNAs in PE, we identified differentially expressed miRNAs between normal and matched preeclamptic placentae by microarrays (Figure 1A) and found that miR21 was the top differentially expressed miRNA (fold change = 1.82, p < 0.05). The expression levels of this miRNA were further validated in normal and preeclamptic placental samples (Table 1) by droplet digital PCR (ddPCR), which confirmed upregulated miR21 expression in the preeclamptic placentae (Figure 1B). Primary human trophoblasts (PHTs) were isolated, and increased miR21 levels were found in PHTs from the PE group (Figure 1C). An analysis combining fluorescence in situ hybridization (FISH) and immunofluorescence (IF) staining demonstrated that placental miR21 is expressed in various types of trophoblasts and shows upregulated expression in EVTs from PE-complicated pregnancies (Figures 1D and 1E). Because the immortalized human trophoblast line HTR-8/SVneo expresses a high level of miR21 (Figure S1A), we manipulated miR21 abundance in HTR-8/SVneo cells by transfection with mimic and inhibitor (Figure S1B). Matrigel-based assays and scratch assays showed that both the invasion and migration of HTR-8/SVneo cells were significantly inhibited by the miR21 mimic but stimulated by the inhibitor (Figures 1F and 1G). Compared with the remarkable inhibitory effect of miR21 on the invasion and migration of trophoblasts, its effects on cell proliferation or apoptosis appeared less significant (Figures 1H–1J).
To elucidate the underlying regulatory mechanism of the effects of miR21 on trophoblast function, we subjected HTR-8/SVneo cells with upregulated and downregulated abundance of miR21 to whole-genome RNA sequencing. In comparison with the wild-type (WT) group, the group with upregulated miR21 level showed changes in 3,715 mRNAs, including 1,686 that exhibited upregulated expression and 2,029 that showed downregulated expression. In contrast, interference with miR21 elevated the levels of 1,704 mRNAs and suppressed the expression of 1,957 mRNAs (Figure 2A). A Gene Ontology (GO) enrichment analysis of differentially expressed genes decreased by the miR21 mimic and enhanced by the miR21 inhibitor revealed that the phosphoinositide 3-kinase-protein kinase B (PI3K-Akt) signaling pathway, focal adhesion, and the Hippo signaling pathway were influenced by miR21 regulation (Figure 2B). Recent work by our group and other groups has demonstrated that YAP, a key protein in the Hippo pathway, plays a critical role in the maintenance of invasive trophoblasts and is thus needed for expansion of the human placenta. Moreover, the PI3K-Akt, Wnt, and mammalian target of rapamycin (mTOR) signaling pathways have been linked to Hippo signaling,, whereas focal adhesion has been shown to be closely correlated with trophoblast migration and invasion. Together, these findings prompted us to determine whether the regulatory effects of miR21 on trophoblast invasion and migration involve the Hippo pathway. Interestingly, our results showed that upregulation of miR21 elevated the levels of p-LATS1Thr1079 and p-YAPSer127, but not p-LATS1Ser909 and p-YAPSer397, in HTR8/SVneo cells. Suppression of miR21 level specifically diminished the levels of p-LATS1Thr1079 and p-YAPSer127 (Figure 2C). Nevertheless, changes in miR21 abundance did not significantly interfere with MST1/2 phosphorylation. Because dephosphorylated YAP can be transported to the nucleus to facilitate gene transcription, whereas phosphorylated YAP is retained in the cytoplasm, we next investigated whether the phosphorylation status of YAP in response to miR21 expression was associated with its subcellular redistribution in trophoblasts. Western blotting analysis demonstrated that cytoplasmic YAP was increased in miR21-overexpressing HTR8/SVneo cells, whereas nuclear YAP was sharply decreased (Figure 2D). Similarly, IF staining showed marked retention of cytoplasmic YAP in the presence of the miR21 mimic, whereas the miR21 inhibitor induced notable accumulation of YAP in the nuclei of HTR8/SVneo cells (Figure 2E). These results demonstrated an inverse correlation between miR21 expression and the nuclear localization of YAP in trophoblasts. Furthermore, the expression levels of downstream target genes of YAP, including CTGF, AMTOL2, and CTNNB1, were negatively correlated with miR21 regulation (Figure 2F). Consistent with our findings in HTR8/SVneo cells, human preeclamptic placentae with upregulated miR21 expression exhibited significantly higher levels of p-LATS1Thr1079 and p-YAPSer127 than the controls (Figure 2G), but the p-MST1/2 levels did not differ. Additionally, significantly elevated cytoplasmic YAP levels and decreased nuclear YAP levels were observed in the preeclamptic placentas (Figure 2H). The reduction in YAP expression observed in the nuclei of preeclamptic placental tissue was further confirmed by IF staining (Figure 2I), and the transcription of CTGF, AMTOL2, and CTNNB1 was found to be significantly compromised in the preeclamptic placentae (Figure 2J). Moreover, the p-LATS1Thr1079 and p-YAPSer127 levels were significantly elevated in PHTs of the preeclamptic placentae, and the phosphorylation of MST1/2 remained similar in the PE and normal groups (Figure 2K). Altogether, the above-described evidence strongly indicated that aberrant miR21 elevation leads to activation of the Hippo pathway in trophoblasts, resulting in the sequestration of YAP in the cytoplasm and subsequent suppression of downstream genes.
By 10× single-cell RNA sequencing of placentae and deciduae from three healthy subjects, we generated a transcriptomic resource of 44,790 cells and identified 15 cell clusters (Figures 3A and S2). This study is the first to reveal the different expression patterns of LATS1 and YAP1 in different cell types of the human placenta. The expression levels of YAP1 and LATS1 in EVTs were abundant (Figure 3B), indicating that the Hippo pathway may play a crucial role in EVTs. Moreover, these expression patterns of LATS1 and YAP in EVTs were then validated by IF staining of decidual cells from normal and preeclamptic pregnancies. Intriguingly, the colocalization of YAP and DAPI staining was compromised in EVTs of preeclamptic pregnancies compared with those of normal pregnancies, but this difference was not found for LATS1 (Figures S3A and S3B). Notably, the expression of miR21, LATS1, and YAP in human primary EVTs indicated their involvement in the biological regulation of trophoblasts during early placentation (Figure S3C). To further determine whether phosphorylation of the LATS1-YAP signaling axis mediates the impact of miR21 on trophoblast invasion and migration, we generated an HTR-8/SVneo cell line that constitutively expressed an inactive (unphosphorylated) form of LATS1 (FLAG-LATS1T1079A/S909A), in which Thr1079 and Ser909 were mutated to alanine (Figure S4A). Moreover, we confirmed that the introduced FLAG-LATS1T1079A/S909A competitively bound to YAP in HTR-8/SVneo cells (Figure S4B). In addition, we established an HTR-8/SVneo cell line with constitutively active YAP (Myc-YAP-5SA) that expresses a YAP protein bearing five serine-to-alanine mutations (S61A, S109A, S127A, S164A, S381A). These mutations are reportedly resistant to phosphorylation and cytoplasmic sequestration, even though they bind to LATS1 in HTR-8/SVneo cells (Figures S4C and S4D). miR21 abundance in FLAG-LATS1T1079A/S909A and Myc-YAP-5SA mutant HTR8/SVneo cells was then increased by the mimic or suppressed by the inhibitor (Figures S4E and S4F). Neither overexpression nor inhibition of miR21 altered the phosphorylation of LATS1Thr1079, LATS1Ser909, or YAPSer127 in these cells (Figures 3C, 3D, S5A, and S5B). Accordingly, both the accumulation of cytoplasmic YAP induced by miR21 overexpression and the retention of nuclear YAP induced by miR21 inhibition were blunted in the FLAG-LATS1T1079A/S909A and Myc-YAP-5SA cells (Figures 3E and 3F); this effect was confirmed by IF staining (Figures S5C and S5D). These results demonstrated that phosphorylation of LATS1Thr1079 and YAP Ser127 is needed for the miR21-induced redistribution of YAP in trophoblasts. To further confirm the involvement of LATS1 and YAP phosphorylation in the miR21-mediated regulation of trophoblastic function, we treated FLAG-LATS1T1079A/S909A and Myc-YAP-5SA cells with a miR21 mimic or inhibitor and then performed cell invasion and migration assays. The modulation of miR21 level disturbed neither invasiveness nor migration (Figures 3G–3J) and did not significantly interfere with the proliferation and apoptosis of the FLAG-LATS1T1079A/S909A and Myc-YAP-5SA cells (Figures S5E–S5J). These results indicated that the miR21-induced phosphorylation of LATS1 and YAP is essential for the inhibitory regulation of trophoblast invasion and migration.
The Hippo signaling pathway maintains regulatory function by balancing the phosphorylation and dephosphorylation of its components between kinases and phosphatases. Several phosphatases, such as PP2A, protein phosphatase 1 (PP1), striatin-interacting phosphatases and kinases (STRIPAK), and protein tyrosine phosphatase nonreceptor type 14 (PTPN14), reportedly interact with the Hippo pathway to regulate cell proliferation and migration. Pertinently, the involvement of the protein serine/threonine phosphatase (PSP) family in the regulation of the Hippo pathway has been well documented.29, 30, 31 Our RNA sequencing of HTR8/SVneo cells with miR21 upregulation and silencing revealed a differentially expressed mRNA, PPP2R2B, which encodes PP2A Bβ, the regulatory subunit of PP2A. We then conducted luciferase-based reporter assays to validate the putative binding between miR21 and PPP2R2B. Moreover, the mutation was introduced in the putative target sequence to prevent miR21 interaction (Figure 4A). Our data showed that the miR21 mimic significantly reduced the luciferase activity of the WT rather than mutant (MUT) PPP2R2B plasmids (Figure 4B), confirming the direct binding of miR21 with PPP2R2B. To validate the putative negative regulatory effect of miR21 on PPP2R2B expression, we measured the PPP2R2B expression levels and found that the mRNA levels in HTR8/SVneo cells were downregulated by the miR21 mimic but upregulated by the inhibitor (Figure 4C). Accordingly, the PPP2R2B mRNA levels were significantly lower in preeclamptic placentas than in placentas of uncomplicated pregnancies (Figure 4D). We then measured the PP2A Bβ protein levels in whole placenta lysate and PHTs from PE-complicated pregnancies and found that the PP2A Bβ protein levels in these pregnancies were significantly lower than those in uncomplicated pregnancies (Figures 4E and 4F). PP2A modulates the Hippo pathway by dephosphorylating its component proteins,, thus, to ascertain whether PP2A Bβ is directly involved in the regulation of the Hippo pathway by miR21, we verified the interaction between PP2A Bβ and Hippo pathway molecules. Coimmunoprecipitation (coIP) using human placental tissues, PHTs, and HTR8/SVneo cells showed that PP2A Bβ physically binds with LATS1 (Figure 4G) but not MST1 or YAP (Figures S6A–S6F), which indicates that miR21 may regulate the Hippo pathway in trophoblasts via the PP2A Bβ/LATS1 axis. To verify the putative role of PP2A Bβ in mediating the miR21-induced activation of the Hippo pathway in trophoblasts, we established PPP2R2B-overexpressing HTR8/SVneo cells via transfection with pc-PPP2R2B plasmids. These cells exhibited a 2-fold increase in the PP2A Bβ protein levels (Figure S7A). Nevertheless, PP2A Bβ overexpression alone had no significant impact on the viability of trophoblasts but markedly promoted invasion (Figures S7B–S7F). Cotransfection of the miR21 mimic with the pc-PPP2R2B plasmids showed that the decreased dephosphorylation of LATS1Thr1079 and YAPSer127 in HTR8/SVneo cells via the miR21-mediated downregulation of PP2A Bβ was notably diminished by overexpression of PP2A Bβ (Figure 4H). Moreover, PP2A Bβ overexpression led to significant accumulation of nuclear YAP, while concurrently alleviating cytoplasmic YAP retention caused by upregulation of miR21 (Figures 4I and 4J). Consistent with our observed changes in Hippo signaling, the inhibition of cell invasion and migration due to miR21 was significantly rescued by upregulated PP2A Bβ expression (Figures 4K and 4L), and this rescue did not affect cell viability (Figures 4M and 4N). These results suggest that miR21 regulates trophoblast invasion and migration by suppressing PP2A Bβ.
To validate the regulatory effects of miR21 on PP2A Bβ/Hippo and cell invasion in vivo, we developed placental chondroitin sulfate A (CSA)-binding peptide (plCSA-BP)-conjugated nanoparticles loaded with methotrexate (plCSA-MNPs) according to previously described methods for specific delivery to the mouse placenta (Figure 5A). Transmission electron microscopy (TEM) and scanning electron microscopy revealed that the nanoparticles displayed spherical morphologies (Figure 5B) with an approximate mean diameter of 190 nm (Figure 5C). Moreover, these nanoparticles showed electronegative properties with a zeta potential distribution of plCSA-MNPs of nearly −21.4 ± 1.027 mV (Figure 5D). An assessment of stabilities in vitro demonstrated that these nanoparticles exhibited a relatively narrow change in size in 10% fetal bovine serum (FBS) over nearly 5 weeks, indicating strong dispersal and long-term stability (Figure 5E). Moreover, the in vitro release profiles of the nanoparticles showed a rapid release of cargo within the first 24 h and a sustained release from 24 to 70 h, indicating efficient release capabilities (Figure 5F). Next, to verify the delivery specificity of these nanoparticles loaded with agomir-miR21 to the placenta, we loaded placenta-specific nanoparticles with agomir-miR21-Cy3 and administered them to pregnant mice on embryonic day 9.5 (E9.5) via intravenous injection. We detected signals from the agomir-miR21-Cy3 nanoparticles in the placenta 1 h after injection by ex vivo fluorescence imaging (Figure 5G). Based on the 60% loading capacity of our nanoparticles, nanoparticles containing gradient doses of agomir-miR21 (100, 200, 400, or 800 μmol/kg) were then suspended in 300 μL of phosphate-buffered saline (PBS) and administered to pregnant mice via tail vein injection daily during E7.5–E9.5 (i.e., in early placentation). The specificity of agomir-miR21 delivery to the placenta was further confirmed by measuring the abundance of miR21 in the major organs of the dams and fetuses. miR21 abundance was only upregulated in the placenta and exhibited a dose-dependent increase (Figures S8A–S8J). Then, 800 μmol/kg agomir-miR21 nanoparticles or an equivalent amount of agomir-NC nanoparticles were administered to pregnant mice daily during E7.5–E9.5 (experimental design illustrated in Figure 5H). Our data showed that treatment with agomir-miR21 nanoparticles rather than agomir-NC nanoparticles resulted in significantly higher miR21 levels in mouse placentae collected on both E13.5 and E18.5 (Figure 5I), indicating that the administration of agomir-miR21 nanoparticles during early pregnancy could effectively upregulate placental miR21 level until late pregnancy.
According to a previously described mouse model, the placenta-specific delivery of agomir-miR21 could substantially elevate the systolic blood pressure of pregnant mice (Figure 6A). However, this elevation was not observed in nonpregnant mice (Figure S9). Moreover, agomir-miR21 nanoparticle administration led to a significant increase in soluble FLT1 (sFLT1) (Figure 6A), a well-known antiangiogenic factor that has been implicated in the pathogenesis of PE. Pertinently, augmented urinary albumin levels were detected in the agomir-miR21 group (Figure 6C). Notably, a reduction in the glomerulus open capillary area was observed on E18.5 but not on E13.5 (Figure 6D), indicating that the PE-like phenotype observed in the agomir-miR21 nanoparticle treatment group was not nephrogenic but rather placental in origin. In addition, the agomir-miR21 group demonstrated a lower placental weight (Figure 6E). H&E staining of the placentae collected at E13.5 and E18.5 revealed that the ratio of the labyrinth area (Lab) to the junctional zone (JZ) was decreased in the agomir-miR21 group due to a reduction of the Lab and vacuolization of the JZ (Figure 6F). This decrease indicated that upregulation of miR21 led to aberrant development of the placentae. Furthermore, agomir-miR21 treatment led to fetal growth restriction, as manifested by a significantly lower birthweight and crown-rump length (CRL) (Figures 6G–6I). Together, these data indicated that specifically upregulating placental miR21 abundance during placentation induces a PE-like syndrome. Consistent with our findings from in vitro models and human placenta, specific upregulation of miR21 in mouse placenta led to a significant reduction in the PP2A Bβ levels and decreased the dephosphorylation of LATS1 and YAP (Figure 7A). Moreover, upregulated miR21 led to YAP retention in the cytoplasm, which resulted in the attenuation of nuclear localization (Figures 7B and 7C) and downregulation of CTGF, AMTOL2, and CTNNB1 expression (Figure 7D).
Accumulating evidence suggests that dysregulation of miRNAs in the placenta is involved in the pathogenesis of PE. Nevertheless, the expression of miR21 in the placentae of pregnancies complicated by PE remains controversial: some studies have found an association between preeclamptic placentae and downregulated miR21 expression, and other studies have reported opposing findings., In the present study, the upregulation of miR21 expression in preeclamptic human placentae was first identified via unbiased high-throughput microarray screening and then confirmed by ddPCR, which measures the absolute number of transcript copies. Given the recognized interaction between miRNAs and long noncoding RNAs (lncRNAs), previous studies have suggested potential explanations for the correlation between abnormal levels of miR21 in PE and lncRNAs. lncRNA taurine-upregulated gene 1 (TUG1), as a miR21 sponge, promotes migration and invasion via miR-29b in trophoblasts. Moreover, lncRNA maternally expressed gene 3 (MEG3), another lncRNA reportedly implicated in miR21 modulation, has been shown to serve as a positive regulator in trophoblasts and is suppressed by miR210 in PE. However, the involvement of TUG1, MEG3, or other lncRNAs in the pathogenesis of PE through miR21 requires further investigation. The mechanism of miR21 in the downstream regulatory network that drives the development of PE requires further study. Since the development of PE has long been attributed to loss of trophoblast invasion and consequent spiral artery remodeling deficiencies, we speculate that excessive miR21 in the placenta may contribute to this process. First, we revealed that placental miR21 is predominantly expressed in various trophoblasts. We then found that miR21 indeed inhibits trophoblast invasion and migration in vitro and may thus contribute to the development of PE. A previous study demonstrated that the Forkhead box M1 (FOXM1) mRNA and protein levels are decreased in preeclamptic placentas, whereas the expression of miR21 is upregulated. The results confirmed that miR21 might alter trophoblast proliferation by affecting FOXM1, which might participate in promoting the development of PE. Although we observed that upregulation of miR21 moderately inhibited trophoblast proliferation and promoted apoptosis, consistent with this report, the marked inhibition of trophoblast invasion and migration by miR21 cannot be fully explained through its relatively subtle impact on cell viability. To determine the functions of miR21 in vivo, we generated a placenta-specific miR21 overexpression mouse model using a novel nanotechnology-based drug delivery system. Compared with traditional strategies for generating tissue-specific transgenic mice or systemic administration of the miR21 mimic, our approach demonstrated unparalleled advantages in cost and time savings. In addition, our model shows markedly higher bioavailability and specificity compared with systemic administration of the miR21 mimic. Most importantly, this mouse model confirmed that the specific upregulation of miR21 in placentae during placentation impairs placental development and induces PE-like features. Because excessive miR21 can inhibit trophoblast invasion in vitro and induce a PE-like phenotype in vivo, further investigation of the molecular mechanisms regulated by miR21 is needed. miRNAs play critical roles in posttranscriptional gene regulation by destabilizing mRNAs containing complementary base sequences; therefore, aberrant expression of a single miRNA may result in marked changes in the transcriptome. To elucidate the molecular basis underlying the regulatory mechanisms of miR21 in trophoblast motility, we profiled transcriptome changes in miR21-overexpressing and miR21-underexpressing HTR8/SVneo cells by whole-genome RNA sequencing. The results suggested that PPP2R2B, which encodes PP2A Bβ, a subunit of PP2A phosphatases, is a putative downstream target of miR21. Phosphatases have previously been reported to participate in various biological processes. Functional PP2A is a trimer consisting of regulatory subunits (B) that bind with catalytic (C) and scaffolding subunits (A), which participate in tumor progression. The B regulatory subunit determines the substrate specificity of the holoenzyme. Several studies have demonstrated that the transcriptional regulation of PP2A by miRNAs usually involves targeting of different regulatory subunits. Although PP2A is generally recognized as a tumor suppressor with genetic alterations or functional inactivation in cancer, previous studies have revealed that the PP2A B subunit promotes cell proliferation in various cancer cells., Here, we demonstrated that upregulation of the expression of PP2A Bβ alone did not significantly affect cell viability but promoted trophoblast invasion, consistent with the results from previous research in tumorigenesis. According to our whole-genome RNA sequencing results, the Hippo pathway may be a critical signaling pathway involved in the regulation of PP2A Bβ in trophoblasts. The phosphorylation cascade of kinases in the Hippo pathway is partially regulated by PP2A. Thus, we hypothesized that the interference of PPP2R2B by miR21 may influence the dephosphorylation-mediated regulation of PP2A on Hippo molecules and ultimately alter Hippo pathway activity. Key components of the Hippo pathway, such as phosphorylation of kinase MST1 and LATS1, result in phosphorylation-dependent cytoplasmic retention of the transcriptional coactivator YAP by the 14-3-3 proteins. This phosphorylation MST/LATS/YAP cascade is reportedly involved in tumorigenesis and tightly regulated by phosphatases, including PP2A. Tang et al. reported that striatin3 (STRN3), encoded by PPP2R6B, directly interacts with MST2 in HEK293FT cells. These researchers further revealed a distinct binding site for STRN3 on PP2A subunit A, specifically a short C-terminal portion of the coiled coil of STRN3 (composed of amino acid residues termed STRN3Core). Moreover, a recent study demonstrated that the inhibition of catalytic subunit C reduced vessel growth by inactivating YAP in endothelial cells and thus provide new insights into the involvement of PP2A and the Hippo pathway in placental development. Here, we report that PP2A Bβ interacts with LATS1 rather than MST1 or YAP in human placental tissues, PHTs, and HTR8/SVneo cells, which has been proposed in cancer research., This finding identified a novel regulatory mechanism of YAP activation that relies on PP2A Bβ. However, the molecular basis and features underlying the interaction between PP2A Bβ and LATS1 warrant further study. Moreover, we found that the phosphorylation of LATS1 at Thr1079 rather than Ser909 responds to miR21 abundance. The phosphorylation of LATS1 at Thr1079 led to the cytoplasmic retention of YAP in vitro and in vivo. Moreover, we demonstrated that YAP phosphorylation at Ser127 rather than Ser397 occurs in response to miR21 in trophoblasts; p-YAPSer127 is involved in YAP cytoplasmic retention, whereas p-YAPSer397 is correlated with proteasomal degradation. Considering this information, we focused on p-YAPSer127 in miR21-regulated YAP localization. As expected, upregulated miR21 levels in preeclamptic placentae, mouse placentae or HTR8/SVneo cells suppressed PP2A Bβ and enhanced p-YAPSer127. Subsequently, the expression levels of downstream genes of YAP, such as CTGF, AMTOL2, and CTBNN1, were downregulated due to reductions in nuclear YAP. In summary, abnormal elevation of miR21 during placentation interferes with PP2A Bβ, which leads to decreased dephosphorylation of LATS1 and YAP. Compromised inhibition, in turn, impedes the cytoplasmic-to-nuclear translocation of YAP and subsequent gene transcription involved in trophoblast invasion and migration, which ultimately causes PE (Figure 7E). Our findings highlight the importance of the miR21-mediated degradation of PPP2R2B mRNA leading to decreased PP2A Bβ phosphatase abundance in the regulation of trophoblast invasion and migration and thus provide in-depth insights into the etiology of PE from the perspective of posttranscriptional gene regulation.
This study involving patients and animals was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University (no. 2018-108) in accordance with the principles set out in the Declaration of Helsinki. All samples were collected with written informed consent provided by the participants. The animal procedures were conducted in accordance with the Guidelines of Chongqing Medical University and approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University.
Placental and decidual tissues were collected from women with PE (n = 20) with normotensive pregnancies admitted to the First Affiliated Hospital of Chongqing Medical University for elective cesarean deliveries. PE was diagnosed according to the guidelines of the American College of Obstetrics and Gynecology (ACOG). Patients with other major pregnancy complications, such as infection, gestational diabetes mellitus (GDM), chronic hypertension, immune diseases, other gestational complications, and chronic health conditions, were excluded. Individuals with noninfective premature deliveries were recruited to match the gestational age of PE. The clinical characteristics of the subjects are shown in Table 1. Placental villous tissue (n = 10) was collected from women who underwent legal termination for nonmedical reasons during the first trimester (6–9 weeks), and patients with a history of spontaneous abortion or ectopic pregnancy were excluded. Placental specimens were randomly collected as previously described by Yang et al. immediately after delivery and then washed with cold PBS, flash frozen in liquid nitrogen and stored at −80°C for further use, or fixed in 4% formaldehyde.
Eight- to 12-week-old CD-1 female mice weighing 25–35 g from the Experimental Animal Center of Chongqing Medical University were mated with age-matched male mice. Upon observation of a vaginal plug, the day of mating was considered E0.5. All mice were kept in a temperature-controlled room (23°C) with a 12-h light:12-h dark cycle.
Pregnant mice were randomly assigned to three groups (control, n = 12; agomir-NC, n = 12; agomir-miR21, n = 12). On E7.5, nanoparticles suspended in 300 μL of PBS were administered to pregnant mice daily through the tail vein over three consecutive days at a dose of agomir-NC or agomir-miR21 equivalent to 800 μmol/kg. The mice belonging to the control group did not receive any treatment. The mice were sacrificed on E18.5 for sample collection. All animal experiments were carried out in accordance with the National Institutes of Health guidelines for the use and care of animals and approved by the Institutional Animal Care and Use Committee of Chongqing Medical University.
The blood pressure was measured by tail-cuff plethysmography (Visitech Systems, USA) every 2 days during E1.5–7.5 and then every day during E7.5–17.5. The mice were maintained conscious and in restraints, and 10–20 actual measurements were obtained after normalization.
Spot urine of pregnant mice was collected at E18.5 and centrifuged at 4,000 × g and 4°C for 10 min, and the supernatant was collected and frozen at −80°C. Urinary albumin was measured using a Mouse Albumin ELISA Quantitation kit (Assaypro, USA) according to the manufacturer’s protocols, and the absorbances were read using a microplate reader (Thermo Fisher Scientific, USA).
After sacrifice on E18.5, mouse plasma was collected using EDTA as an anticoagulant and centrifuged at 1,000 × g for 30 min. Plasma was then removed and stored in aliquots at −80°C. Plasma s-FLT1 was measured with a Mouse s-FLT1 ELISA Quantitation kit (Cloud-Clone Corp., China) according to the manufacturer’s protocols.
Placentae and kidneys were fixed in 4% paraformaldehyde, embedded in paraffin, and cut into 3-μm-thick sections. The sections were deparaffinized, rehydrated, and then stained with hematoxylin for 5 min and then with eosin for 2 min. Images were captured with an EVOS microscope (Life Technologies, USA).
PHTs were isolated from first-trimester placental villi as previously described. Briefly, immediately after legal termination, placental villus tissue (6–9 weeks of gestation, n = 3–5 per isolation) was cut into small pieces (1–3 mm). The first digestion was performed with 0.125% trypsin (Gibco, USA) for 15 min at 37°C. After the digestion was stopped with 10% FBS (Gibco, USA), the cells were filtered through a 700-μm cell strainer (Miltenyi, Germany), and the remaining tissues were digested with 0.25% trypsin for 15 min at 37°C. After two consecutive digestion steps followed by Percoll (Bio-Rad, USA) density gradient centrifugation at 300 × g and 4°C for 20 min, trophoblast cells were isolated. The PHTs were then seeded on 4-μg/mL fibronectin-coated dishes and fixed for IF after 24 h.
PHTs from term placental tissues were isolated as previously described. Briefly, immediately after delivery, placental tissue was rinsed in ice-cold saline and minced into small pieces (1–3 mm). For digestion of the placental tissue, 625 mg of dispase II (Roche, Switzerland) and 400 μL of DNase (Roche, Switzerland) were added and incubated for 1 h and 15 min, respectively, at 37°C. After filtering (70 μm, Miltenyi, Germany) and centrifuging at 300 × g and 4°C for 7 min, the precipitate was resuspended in 40 mL of platelet lysis solution (Gibco, USA) and washed twice gently with DMEM/F12 (Gibco, USA), which contained 10% FBS (Gibco, USA). The suspension was then added to a Percoll gradient (60%, 50%, 40%, 30%, and 20%, Bio-Rad, USA) and centrifuged at 1,000 × g for 20 min. The 20%–40% Percoll layer was collected, suspended in DMEM/F12 mixed with 10% FBS, and then centrifuged at 300 × g for 7 min. The pellet was resuspended in DMEM/F12 containing 10% FBS and antibiotics and then seeded onto dishes for 3 h to adhere.
The immortalized human trophoblast cell line HTR8/SVneo was purchased from the American Type Culture Collection (ATCC, USA). The human choriocarcinoma cell lines JAR, JEG3, and BeWo were obtained from the Cell Bank of the Chinese Academy of Sciences. Both HTR-8/SVneo and JAR cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 (Gibco, USA) containing 10% FBS (Gibco, USA) and 1% penicillin–streptomycin (Beyotime, China). JEG3 cells were cultured with DMEM/F12 medium (Gibco, USA). BeWo cells were cultured with DMEM/F12K medium (Gibco, USA). All the cells were cultured at 37°C in 5% CO2 humidified air.
Cy3-hsa-miR21 (5′-TCAACATCAGTCTGATAAGCTA-3′) probes were synthesized and obtained from GenePharma (China). Hybridization assays were performed using a FISH Detection Kit (Gene Pharma, China) according to the manufacturer’s instructions. All images were captured with a fluorescence microscope (Life Technologies, USA).
The detailed immunoblotting procedure was completed according to our previous study. Primary antibodies against PP2A Bβ (1:1,000, 13123-1-AP), CK7 (1:1,000, 17513-1-AP), human leukocyte antigen G (HLA-G) (1:1,000, 66447-1-Ig), anti-ɑ-tubulin (1:1,000, 11224-1-AP), and anti-β-actin (1:1,000, 66009-1-Ig) were purchased from Proteintech (China). Anti-MST1 (1:500, bs-28134R) and anti-MST2 (1:500, bs-4663R) were purchased from Bioss (China). Anti-LATS1 (1:1,000, #3477), anti-p-LATS1 Ser909 (1:1,000, #9157S), anti-p-LATS1 Thr1079 (1:1,000, #8654S), anti-YAP (1:1,000, #14074S), anti-p-YAP Ser127 (1:1,000, #13008S), and anti-p-MST1/2 (1:1,000, #49332S) were purchased from Cell Signaling Technology (USA). Anti-p-YAP Ser127 (1:5,000, ab226760) and anti-CD31 (1:1,000, ab9498) were purchased from Abcam (UK). Anti-YAP (1:500, sc-376830) was purchased from Santa Cruz (USA).
Anti-MST1 (Cell Signaling Technology, USA), anti-LATS1 (Cell Signaling Technology, USA), anti-YAP (Cell Signaling Technology, USA), anti-YAP (Santa Cruz, USA), anti-PP2A Bβ (Proteintech, China), anti-Myc (Proteintech, China), anti-FLAG (Proteintech, China), or anti-IgG (Santa Cruz, USA) antibodies were incubated with Protein A/G Magnetic Beads (Bimake, USA) for 4 h at 4°C. Samples were lysed with Thermo Scientific Pierce IP Lysis Buffer (Thermo Fisher Scientific, USA) with protease inhibitor mixture (Bimake, USA) and incubated with an antibody-bead complex overnight at 4°C. The immunoprecipitation products were then precipitated by the antibody-bead complex using a magnetic rack and analyzed by western blotting.
Placental tissues were fixed in 4% paraformaldehyde and subsequently embedded in paraffin. Serial sections (3 μm) of paraffin-embedded tissues were analyzed by IF as described elsewhere. Briefly, tissue slides were deparaffinized in xylene, rehydrated in a serial ethanol gradient, and blocked with 3% H2O2 for 10 min. The slides were then immersed in TE buffer (10 mM Tris and 1.0 mM EDTA, pH 9.0), warmed in a microwave oven at 92°C–98°C for 15 min for antigen retrieval, and cooled to room temperature. The slides were then blocked with 10% goat serum (Boster, China) for 1 h at room temperature, incubated with primary antibodies overnight at 4°C, and then incubated with fluorescence-labeled secondary antibodies (Bioservice, China) at 37°C for 1 h. The nuclei were subsequently counterstained with 4′,6-diamidino-2-phenylindole (DAPI, Boster, China) and mounted with antifade mounting medium (Boster, China). The cells were fixed with 4% paraformaldehyde, permeabilized in 0.2% Triton X-100, and blocked with 10% goat serum (Boster, China). After overnight incubation with primary antibodies at 4°C, the cells were incubated with fluorescence-labeled secondary antibodies (Bioservice, China) at 37°C for 1 h. The nuclei were stained with DAPI, and images were captured with an EVOS microscope (Life Technologies, USA) and/or confocal microscope (Zeiss, Germany).
Total RNA from tissues or cells was extracted using TRIzol reagent (Invitrogen, USA) according to the manufacturer’s instructions. For miR21 measurement, 20 ng of total RNA was first reverse transcribed using the TaqMan microRNA reverse transcription kit (Thermo Fisher Scientific, USA), and miR21 (000397, Thermo Fisher Scientific, USA) and U6 (001973, Thermo Fisher Scientific, USA) snRNA-specific primers and probes and then quantified using a TaqMan PCR kit (Thermo Fisher Scientific, USA) with a Bio-Rad CFX Manager System (Bio-Rad, USA). The expression levels relative to that of U6 were determined using the ΔΔCq method. For mRNA quantification, 1 μg of total RNA was used for reverse transcription with a Prime Script RT reagent kit (Roche, Switzerland). Real-time PCR was then performed using SYBR Green dye (Roche, Switzerland) with an Applied Biosystems PCR cycler (Bio-Rad, USA). The primers were designed and synthesized by TaKaRa (China); β-actin was used as an internal control. The primer sequences are shown in Table 2. The reactions were incubated in a 96-well plate at 95°C for 10 min and then subjected to 40 cycles of 95°C for 10 s, 63.3°C for 30 s, and 72°C for 10 s. All experiments were performed in triplicate. The threshold cycle (Ct) value was defined as the fractional cycle number at which the fluorescence passed the fixed threshold. For ddPCR, the copy numbers of miR21 were measured with ddPCR Supermix for Probes (Bio-Rad, USA) according to the manufacturer’s protocols.
The isolation of nuclear and cytoplasmic proteins from tissues or cells was carried out using a commercial kit (Invent, USA) according to the manufacturer’s instructions. Briefly, for nuclear isolation, 200 μL of cytoplasmic extraction buffer was added to cell dishes and incubated on ice for 5 min. The lysed cells were then scraped with a pipette tip and transferred to a prechilled 1.5-mL microcentrifuge tube. After vigorous vortexing for 15 s, the tube was centrifuged in a microcentrifuge at 16,000 × g and 4°C for 5 min. The supernatant (cytoplasmic lysate) was collected as the cytoplasmic protein. Subsequently, appropriate amounts of nuclear extraction buffer were added to the pellet, vortexed vigorously for 15 s, and then incubated on ice for 1 min. The process of vortexing for 15 s and incubation for 1 min was repeated four times. The nuclear extract was transferred to a prechilled filter cartridge with a collection tube and centrifuged in a microcentrifuge at 16,000 × g for 30 s. The cytoplasmic and nuclear lysates were stored at −80°C for further use.
The oligonucleotide sequences of the miR21 mimic, inhibitor, or negative control (Table 3) were purchased from GenePharma (China). pQCXIH-Myc-YAP-5SA was a generous gift from Kunliang Guan (Addgene plasmid # 33093; http://www.addgene.org/33093/. RRID: Addgene_33093). The FLAG-LATS1T1079A/S909A plasmid, PPP2R2B reporter plasmid, and PPP2R2B overexpression plasmid were synthesized by Hanbio Biotechnology (China). HTR8/SVneo cells at 70% confluency were transfected with 100 nM oligonucleotides or 1 μg of plasmids in the presence of Lipofectamine 2000 (Thermo Fisher Scientific, USA) in six-well plates according to the manufacturer’s instructions.
HTR8/SVneo cells were seeded on 96-well plates at 5000 cells/well and transfected with each of the oligonucleotides or plasmids (miR21 mimic, inhibitor, negative control, Myc-YAP 5SA and FLAG-LATS1T1079A/S909A) after adhesion. The supernatant was discarded after treatment for 48 h. Base medium with 10% Cell Counting Kit-8 (CCK-8) assay buffer (MedChemExpress, USA) was then added to the plates at 100 μL/well, and, after 4 h of incubation, the samples were measured with a microplate reader (Thermo Fisher Scientific, USA) at 450 nm.
The 5-ethynyl-2′-deoxyuridine (EdU) assay was performed using the Click-iTR EdU Kit (RiboBio, China) according to the manufacturer’s instructions. Specifically, cells were plated in 96-well plates and treated after adhesion. A total of 100 μL of culture medium containing 50 mM EdU was added to each well, and, 4 h later, the cells were fixed with 4% formaldehyde for 30 min. After washing, the cells were incubated with a solution in the kit for 30 min and stained with Hoechst (RiboBio, China) to identify nuclei, and images were captured with a fluorescence microscope (Thermo Fisher Scientific, USA). EdU-positive cells were determined using ImageJ 1.50i software (https://imagej.en.softonic.com/).
Cell apoptosis was analyzed by flow cytometry using an Annexin V-FITC kit (Beyotime, China) according to the manufacturer’s protocols. The cells were plated on six-well plates at 4 × 105 cells/mL per well, harvested, and washed with PBS. The cells were then mixed with Annexin V-FITC and phosphatidylinositol propidium iodide (PI)-binding buffer for 20 min, and the mixture was then analyzed using a flow cytometer (BD Biosciences, USA).
HTR8/SVneo cells (50,000 cells/well) were resuspended in RPMI-1640 medium without FBS and seeded into the upper compartment of the invasion chamber (8 μm, BD Falcon, USA), which was coated with previously diluted Matrigel (Corning, USA) in a 24-well plate. After 24 h, the upper chambers were fixed with 4% paraformaldehyde, washed with PBS, and stained with crystal violet boric acid. The cleaned upper chambers were photographed with an EVOS microscope (Life Technologies, USA). Cell counts were calculated using ImageJ 1.50i software.
HTR8/SVneo cells were seeded on six-well plates and grown to more than 90% confluence. A cross shape was scratched into plates with a 200-μL pipette tip, and pictures were taken at 0 and 24 h. The area of wound healing was quantified using ImageJ 1.50i software.
To generate luciferase reporter plasmids for PPP2R2B, the 3′ UTR of PPP2R2B (407 nt) containing putative miR21-binding sites was cloned into a pSI-CHECK2 vector (Sangon Biotech, China). The putative miR21 target sequences shown in panel A in Figure 4 were longer sequences, which included the putative miR21 target and a portion of the sequences preceding and following the target. A day before transfection, HTR8/SVneo cells were seeded into 12-well plates. Cells were cotransfected with miR21 mimic and the WT or MUT luciferase vectors using Lipofectamine 2000 Reagent (Thermo Fisher, USA). Forty-eight hours after transfection, the luciferase activity was measured by the Dual-Luciferase Reporter System (Promega, USA) using a fluorescence microplate reader (Thermo Fisher, USA) according to the manufacturer’s instructions.
Total RNA was extracted using TRIzol reagent (Invitrogen, USA) according to the manufacturer’s instructions and then purified with Agencourt AMPure magnetic beads (Beckman Coulter, USA). Target preparation for microarray processing was performed according to the instructions provided in the GeneChip® WT PLUS Reagent Kit (Thermo Fisher Scientific, USA). After hybridization with Affymetrix Human Gene 1.0ST Array chips, the microarrays were washed, stained with streptavidin-phycoerythrin on Affymetrix Fluidics Station 450 (Affymetrix, USA), and then scanned using an Affymetrix® GeneChip Command Console installed in a GeneChip® Scanner 3000 7G (Affymetrix, USA). The microarray data were analyzed by the robust multichip analysis (RMA) algorithm using the default analysis settings and global scaling as the normalization method with Partek® Genomics Suite 6.6. The log2-transformed values of the RMA signal intensities were calculated, and differential expression analysis was further performed by one-way analysis of variance (ANOVA).
HTR8/SVneo cells were grown to 60%–70% confluency and then transfected with miR21 mimic and inhibitor oligonucleotides for 48 h. Total RNA was extracted using TRIzol reagent (Invitrogen, USA), and the concentration was measured by Nanodrop 2000 UV spectroscopy (Thermo Fisher, USA). A total of 5 μg of RNA per sample was used as the input material for the transcriptome libraries. The sequencing libraries were generated with a NEBNext® Ultra™TM Directional RNA Library Prep Kit for Illumina® (NEB) following the manufacturer’s recommendations. The differential expression analysis of two samples was performed using the DEGseq (2010) R package. The p value was adjusted using the q value. Significantly differential expression was defined based on q value <0.01 and |log2(fold change)|>2 as the default thresholds. A GO enrichment analysis of the target gene candidates of differentially expressed miRNAs (hereafter referred to as target gene candidates) was then performed.
Lecithin and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-maleimide (polyethylene glycol 2000) carboxylic acid (DSPE-PEG-COOH) were purchased from Avanti Polar Lipids (USA). Poly(lactide-co-glycolide) (PLGA), 1-ethyl-3-(3- dimethylaminopropyl) carbodiimide hydrochloride (EDC), N-hydroxysuccinimide (NHS), and methotrexate (MTX) were obtained from Sigma-Aldrich (USA). First, lecithin (50 mg) contained ethanol, and DSPE-PEG-COOH (6 mg) was dissolved in deionized water. The mixture was stirred for 0.5 h at 65°C. Then, PLGA (25 mg), guanidinylated hyperbranched poly(ethyleneimine) (GPEI) (12.5 mg), and RNA (1 nm) were added, and the mixture was stirred for 2 h at room temperature and centrifuged at 16,000 rpm for 10 min; these steps were repeated three times. The resulting mixture was precooled at −80°C and then subjected to deposition and lyophilization in a vacuum dryer (EYELA, China) at −53°C. The peptides were conjugated to DSPE-PEG-COOH using EDC and NHS. First, 18 mg of the lipid-polymer nanoparticles (NPs) were suspended in 6 mL of 0.1 M 2-morpholinothanesulfonic acid (MES) buffer (pH 5.5). For preactivation of the carboxylic group, 15 mg of EDC and 5 mg of NHS were added, and the mixture was stirred for 15 min at room temperature. Three milligrams of plCSA-BP was then dissolved in 500 μL of deionized water, and the solution was added to the reaction mixture separately. Next, 350 μL of 20× PBS was added to buffer the reaction, and the pH was maintained at 7.0–8.0. The reaction mixture was stirred overnight at room temperature. Excess peptides and other impurities, such as EDC and NHS, were removed by centrifugation at 16,000 rpm to obtain the final plCSA-conjugated nanoparticles loaded with RNA. The same procedures were used to prepare plCSA-BP-conjugated nanoparticles loaded with agomir-miR21-Cy3 or MTX. After deposition and lyophilization, the nanoparticles were stored at −20°C for further experiments and resuspended in PBS before use.
The morphology and size of the nanoparticles were observed by TEM (Hitachi, Japan) at an acceleration voltage of 80 kV. Scanning electron microscopy images were obtained with a focused ion beam (FIB) scanning electron microscope (Zeiss, Germany). Zeta potential and size measurements were performed at 25°C using a Malvern Zetasizer Nano ZS instrument (Malvern, USA). The stability of the nanoparticles in serum was evaluated by examining the size changes of the particles in 10% FBS. The release profiles of the nanoparticles were assessed using a dialysis experiment to measure the release of MTX in PBS (pH 7.4) release medium. The dialysate was removed at different scheduled time points to measure the concentration of MTX by high-performance liquid chromatography (Agilent, USA) at 307 nm.
Decidual and placental tissues were minced into approximately 0.2–1-mm3 cubes with scissors and digested with 10 mL of 10 mg/mL collagenase IV (Sigma, USA) solution in RPMI 1640 medium (Gibco, USA) with 10% FBS (Gibco, USA) at 37°C for 90 min in a shaking incubator. The supernatant was diluted with medium and filtered through 100-μm, 70-μm, and 40-μm cell strainers (Miltenyi, Germany) in sequence. The flow-through was centrifuged and resuspended in 5 mL of red blood cell lysis buffer (Biosharp, China) for 8 min. The mixture was centrifuged at 300 × g and 4°C for 5 min, and the cell pellet was resuspended in 1 mL of medium for 10× single-cell sequencing.
A Cell Ranger Single-Cell Software Suite (version 3.0, 10x Genomics) was used to align and quantify 10× sequencing data. Alignment, filtering, barcode counting, and unique molecular identifier (UMI) counting were performed with a Cell Ranger count module to generate a feature-barcode matrix and determine clusters. Seurat (version 4.0.1) was used to analyze downstream data. Cells with a gene number lower than 500 or higher than 8,000 or with a mitochondrial gene ratio higher than 30% were regarded as abnormal and filtered out. All Seurat objects for individual samples were integrated into one combined object. The union of the top 2,000 variable genes for combined objects was then used to perform canonical correlation analysis (CCA) of different samples of data. The CCA subspaces were then aligned using 1:25 CCA dimensions, and uniform manifold approximation and projection (UMAP) was performed to visualize all the cells. The expression of established lineage marker genes was used to assign cell types. The gene expression levels were visualized using VlnPlot.
All data were collected using Prism 7 software (GraphPad). The data in bar and line graphs represent the means ± standard errors of the mean (SEMs). Two-tailed Student’s t test was used for comparisons between two groups. For comparisons among multiple groups, one-way ANOVA followed by Tukey’s multiple comparisons test was applied. For multiple groups with multiple characteristics, two-way ANOVA was used. All the data are presented as the means ± SEMs, and a p value <0.05 was considered to indicate statistical significance. | true | true | true |
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PMC9547305 | Khine Myint,Linda Shyue Huey Chuang,Yu Xuan Teh,Nur Astiana Mawan,Edward Jizhong Shi,Michelle Meng Huang Mok,Napat Nuttonmanit,Junichi Matsuo,Ying Li,Henry Yang,Atsushi Okabe,Atsushi Kaneda,Motomi Osato,Jimmy Bok-Yan So,Wei Peng Yong,Patrick Tan,Khay Guan Yeoh,Yoshiaki Ito | Oncofetal protein IGF2BP1 regulates IQGAP3 expression to maintain stem cell potential in cancer | 23-09-2022 | Cell biology,stem cells research,cancer | Summary We reported earlier that IQGAP3 is an important stem cell factor in rapidly proliferating isthmus stem cells in the stomach and that IQGAP3 expression is robustly induced in terminally differentiated chief cells and de-differentiated cells following tissue damage. The elevated IQGAP3 expression in cancer and its association with metastasis suggest a fundamental role for IQGAP3 in proliferating cancer stem cells. What causes IQGAP3 upregulation in cancer is unclear. Here, we show that IGF2BP1 and IQGAP3 expression levels are highest in the blastocyst, with both decreasing during adulthood. This suggests that IQGAP3, like IGF2BP1, is an early developmental gene that is aberrantly upregulated upon re-expression of IGF2BP1 during carcinogenesis. IGF2BP1 binds and stabilizes m6A-modified IQGAP3 transcripts. Downstream targets of IGF2BP1, namely SRF and FOXM1, also upregulate IQGAP3 expression. These multiple layers of IQGAP3 regulation, which may safeguard against inappropriate stem cell proliferation, present additional drug targets to inhibit IQGAP3-driven malignant growth. | Oncofetal protein IGF2BP1 regulates IQGAP3 expression to maintain stem cell potential in cancer
We reported earlier that IQGAP3 is an important stem cell factor in rapidly proliferating isthmus stem cells in the stomach and that IQGAP3 expression is robustly induced in terminally differentiated chief cells and de-differentiated cells following tissue damage. The elevated IQGAP3 expression in cancer and its association with metastasis suggest a fundamental role for IQGAP3 in proliferating cancer stem cells. What causes IQGAP3 upregulation in cancer is unclear. Here, we show that IGF2BP1 and IQGAP3 expression levels are highest in the blastocyst, with both decreasing during adulthood. This suggests that IQGAP3, like IGF2BP1, is an early developmental gene that is aberrantly upregulated upon re-expression of IGF2BP1 during carcinogenesis. IGF2BP1 binds and stabilizes m6A-modified IQGAP3 transcripts. Downstream targets of IGF2BP1, namely SRF and FOXM1, also upregulate IQGAP3 expression. These multiple layers of IQGAP3 regulation, which may safeguard against inappropriate stem cell proliferation, present additional drug targets to inhibit IQGAP3-driven malignant growth.
The study of stem cell regulators is necessary to understand how proliferation and multipotency are maintained in stem cells and how they are hijacked in cancer. Our recent work identified cytoskeletal protein IQGAP3 (IQ motif containing GTPase-activating protein 3) as a highly specific marker of proliferating stem cells in the stomach corpus (Matsuo et al., 2021). We further found rapid upregulation of IQGAP3 expression, which was accompanied by massive dedifferentiation of mature lineages, upon tissue damage (Matsuo et al., 2021). Our observation that the depletion of IQGAP3 led to differentiation indicated a strong requirement for IQGAP3 in the maintenance of stem cell potential and proliferation (Matsuo et al., 2021). IQGAP3 is a scaffold protein with multiple protein binding modules, such as the calponin homology domain (CHD) for F-actin-binding, the WW domain that interacts with ERK ½, calmodulin-binding IQ motifs, Ras GTPase-activating protein-related domain (GRD) that interacts with Rac1/Cdc42, and the RasGAP binding domain at the C-terminus (RGCT) (Hedman et al., 2015; Nojima et al., 2008). These domains allow IQGAP3 to integrate diverse biological pathways for important roles in cell adhesion, motility, proliferation, and signal transduction (eg. RAS-ERK cascade and Rho-Rac1) (Nojima et al., 2008; Wang et al., 2007). The Bgee database (Swiss Institute of Bioinformatics) revealed that IQGAP3 expression is highest during mammalian embryonic/fetal development when compared to the adult. Moreover, IQGAP3 is essential for cell proliferation and motility—through FGFR1-Ras signaling—during zebrafish embryonic development (Fang et al., 2015), thereby reinforcing the notion that IQGAP3 is necessary for development across species. IQGAP3 is overexpressed in several types of human malignant tumors including gastric, colorectal, liver, pancreatic, lung, ovarian, and breast cancers (Dongol et al., 2020; Hu et al., 2016; Oue et al., 2018; Skawran et al., 2008; Wu et al., 2019; Xu et al., 2016; Yang et al., 2014). Importantly, high expression levels of IQGAP3 are associated with poor prognosis in different cancer types (Koon et al., 2004; Kumar et al., 2017; Skawran et al., 2008; Wu et al., 2015). Our finding that IQGAP3 is involved in the maintenance of stem cell properties in human embryonic and undifferentiated gastric cancer cells (Matsuo et al., 2021) suggests that IQGAP3 could be a potential therapeutic target for cancer treatment. The mechanisms underlying the tight association of IQGAP3 expression with proliferating stem cells and cancer cells are unclear. Our study aims to delineate the regulation of IQGAP3 expression in the pluripotent embryonic cancer cell line model NTERA-2 and the undifferentiated human gastric cancer cell line, HGC-27. We found that IQGAP3 RNA stability is enhanced by the oncofetal protein IGF2BP1 (insulin-like growth factor 2 mRNA-binding protein 1) in an N6-methyladenosine (m6A) RNA methyltransferase METTL3/14-dependent manner. IGF2BP1 has earlier been shown to bind to m6A-modified mRNAs, thereby stabilizing the RNA of cancer-associated genes such as MYC, E2F1, and Serum Response Factor (SRF) (Degrauwe et al., 2016; Huang et al., 2018; Muller et al., 2019, 2020). SRF regulates gene expression through cooperation with ternary complex factors (TCFs) and with myocardin-related transcription factors (MRTFs) (Clark and Graves, 2014). SRF-TCF complexes modulate the transcription of genes involved proliferation and response to growth factors while SRF-MRTF drives the transcription of genes related to cytoskeleton regulation, cell adhesion, and migration (Clark and Graves, 2014; Esnault et al., 2014; Leitner et al., 2011). More recently, SRF has been shown to destabilize cellular identity through its regulation of cytoskeletal genes (Ikeda et al., 2018). We found that SRF strongly upregulates IQGAP3 expression in NTERA-2 and HGC-27. We also identified FOXM1 (forkhead box protein M1) RNA as a novel direct target of IGF2BP1 and as an upstream regulator of IQGAP3. Together, our study suggests that the aberrant upregulation of IQGAP3 in cancer may be owing to the re-expression of IGF2BP1 in malignant tissues and its interplay with SRF and FOXM1. IGF2BP1, SRF, FOXM1, and IQGAP3 may therefore form a critical axis for tumorigenesis and cancer stem cell viability of undifferentiated cancer cells, such as HGC-27.
To identify the regulatory factors of IQGAP3 gene expression, we first queried the public database The Encyclopedia of RNA Interactomes (ENCORI) (http://starbase.sysu.edu.cn/) (Li et al., 2014). This interface provides access to the enhanced crosslinking and immunoprecipitation (eCLIP) datasets, which are used for the identification of target sites of RNA binding proteins (Van Nostrand et al., 2016). Distinct enrichment of IGF2BP1 at the 3′ untranslated region (3′UTR) of IQGAP3 RNA from the human liver hepatocellular carcinoma cell line HepG2 and the multipotential, hematopoietic malignant cells K562 cell line were observed (Figure S1A). IGF2BP1 is expressed mainly during embryonic development, with likely roles in cell migration, metabolism, and stem cells (Degrauwe et al., 2016). After birth, IGF2BP1 expression drops to very low or negligible levels in most tissues (Degrauwe et al., 2016). Importantly, it is re-expressed in a broad range of cancer types and typically associated with poor prognosis (Degrauwe et al., 2016). We compared the RNA expression levels of Iqgap3 and Igf2bp1 in the mouse blastocyst stage and various adult tissues and found stronger co-expression of both in the blastocyst compared to adult tissues (Figure 1A). It would seem that Iqgap3 and Igf2bp1 play prominent roles in embryonic development. Interestingly, Iqgap3 expression is higher in the adult stomach than in tissues such as adult brain, heart, kidney, and liver, whereas Igf2bp1 levels are negligible in all adult tissues (Figure 1A). We had earlier detected high IQGAP3 expression specifically in rapidly proliferating isthmus stem cells in the adult stomach corpus (Matsuo et al., 2021). It is possible that, while markedly reduced in the adult, IQGAP3 expression is still maintained in proliferative tissues with high regeneration capacity. By contrast, IGF2BP1 expression and function appear to be mainly fetal. As IGF2BP1 is expressed in pluripotent and various cancer cell lines, we selected the pluripotent human testicular embryonal carcinoma cell NTERA-2 to further explore the oncofetal association between IQGAP3 and IGF2BP1. We introduced FLAG-tagged IGF2BP1 into NTERA-2 cells and used FLAG-affinity beads to immunoprecipitate FLAG-IGF2BP1-ribonucleoprotein complexes for RNA immunoprecipitation sequencing (RIP-seq). Motif analysis revealed the enrichment of various motifs resembling the known IGF2BP1 consensus binding motif 5’-GGAC-3′at the IGF2BP1 peaks (Figure 1B). Gene ontology (GO) analysis of the IGF2BP1 binding sites indicated significant enrichment for genes involved in Rho GTPase signaling, insulin receptor signaling, organelle organization, developmental growth, positive regulation of epithelial cell proliferation, and negative regulation of differentiation (Figure 1C). As expected, RIP-seq showed enriched IGF2BP1 binding at the previously identified targets MYC and SRF mRNA, thereby indicating the specificity of our screen (Figure 1D). Importantly, the IGF2BP1 peaks observed throughout the IQGAP3 RNA—with strong enrichment at the 3′ UTR—confirmed IQGAP3 as a high-confidence RNA target of IGF2BP1 (Figure 1E). It is interesting that of the three IQGAP family members, IQGAP3 mRNA showed the strongest binding by IGF2BP1: IGF2BP1 binding of IQGAP1 RNA was 2-fold less than that in IQGAP3, while the binding of IGF2BP1 to IQGAP2 RNA was negligible (Figure S1B). Intriguingly, we also detected the interaction between IGF2BP1 and FOXM1 RNA (Figure S2A). FOXM1 is a transcription factor that has been strongly linked to cell proliferation as well as stem cell self-renewal (Liao et al., 2018). In the same vein, we also identified RNA of pluripotency factors NANOG and KLF4 as IGF2BP1 binding targets (Figure S1C). To validate the RIP-seq data, we performed RIP of endogenous IGF2BP1 in NTERA-2 cells. RIP-quantitative PCR (RIP-qPCR) confirmed strong enrichment of IQGAP3 RNA in IGF2BP1 immunoprecipitates, relative to the HIST2H3A antibody which served as negative control (Figure 1F). Similarly, MYC and SRF RNA were also bound by IGF2BP1, which served as positive controls for the RIP-qPCR (Figure 1F). IGF2BP1 preferentially binds m6A-modified RNA. Therefore, we performed methylated RNA immunoprecipitation with m6A antibody followed by qPCR. We confirmed that IQGAP3 RNA was modified by m6A methylation at levels comparable to that of SRF and MYC RNA Figure 1G). The heterodimer comprising methyltransferases METTL3 and METTL14 catalyzes m6A methylation of RNA (Liu et al., 2014). We found that knockdown (KD) of METTL3/L14 abolished the ability of IGF2BP1 to interact with IQGAP3 RNA, thus indicating that m6A modification of IQGAP3 RNA is necessary for binding to IGF2BP1 (Figure 2A). Likewise, the interactions of IGF2BP1 with its known targets MYC and SRF RNA were strongly impaired after METTL3/L14 knockdown (Figure 2A). Of note, IQGAP3, MYC, and SRF protein levels were depleted after METTL3/L14 knockdown, suggesting that m6A may be involved in regulating the protein abundance of its target genes through the modulation of RNA levels (Figure 2B). We next ascertained whether IGF2BP1 regulates IQGAP3 mRNA turnover in an m6A-dependent manner. NTERA-2 cells were treated with control siRNA, siRNA targeting IGF2BP1 or METTL3/L14, followed by actinomycin D to inhibit the transcription. Cells were harvested at various time durations and assayed for IQGAP3 mRNA by RT-qPCR. We found that IGF2BP1 knockdown was associated with a significant reduction of IQGAP3 mRNA half-life (Figure 2C). Similarly, METTL3/L14 knockdown also resulted in reduced IQGAP3 mRNA half-life. We also found that the half-lives of known IGF2BP1 targets MYC and SRF mRNAs were reduced upon the knockdown of IGF2BP1 or METTL3/14 (Figures 2D and 2E). Therefore, our results indicate that IGF2BP1 bound and stabilized m6A modified IQGAP3 mRNA (Figure 2C). We further examined whether IGF2BP1 controls the stability of IQGAP3, MYC, and SRF mRNAs in another cell type, HEK293T. Similar to NTERA-2, knockdown of IGF2BP1 in HEK293T led to a dramatic reduction in the half-life of IQGAP3 mRNA (Figure S3A). The half-lives of MYC and SRF mRNAs were also reduced after the knockdown of IGF2BP1 in HEK293T cells (Figures S3B and S3C). Of note, the mRNA decay process in HEK293T cells follows the one-phase decay phenomenon (non-linear) while the linear regression analysis was conducted to generate the line that best fits the data of NTERA-2 cells. Moreover, the half-lives of IQGAP3, MYC, and SRF mRNAs in HEK293T cells were shorter compared to that of NTERA-2 cells.
We recently reported the specific expression of IQGAP3 in rapidly proliferating isthmus stem cells of the stomach corpus (Matsuo et al., 2021). Moreover, we showed that IQGAP3 knockdown in NTERA-2 cells was associated with the reduction of the mRNA of Yamanaka factors NANOG, KLF4, SOX2, and MYC (Matsuo et al., 2021). Therefore, in addition to its critical role in proliferation (Nojima et al., 2008), we hypothesize that IQGAP3 is necessary for the maintenance of pluripotency and/or stem cell properties. Indeed, the induction of differentiation in NTERA-2 cells through treatment with retinoic acid (RA) led to the dramatic reduction of mRNA and protein levels of both IQGAP3 and IGF2BP1, with concomitant decrease of pluripotency factors (Figure 3A). The expression of neuronal differentiation marker GFAP was strongly induced, thereby confirming differentiation onset (Figure 3A). We next knocked down IGF2BP1 in NTERA-2 cells. qPCR and Western blot analysis revealed drastic reductions of the pluripotency/stem cell markers (ie. OCT4, CD44v9, SOX2, NANOG, KLF4), reminiscent of RA-induced differentiated cells (Figure 3B). Importantly, IGF2BP1 knockdown in NTERA-2, similar to IQGAP3 knockdown, was associated with morphological changes resembling differentiation (Figure 3E). Of note, FOXM1 and SRF expression levels were reduced following IGF2BP1 depletion and onset of differentiation. Our RIP-seq data revealed IGF2BP1 binding sites within the FOXM1 RNA, with the highest peaks at the 3′ UTR. We further validated the RIP-seq data by performing IGF2BP1 RIP-qPCR assay to show strong enrichment of IGF2BP1 on FOXM1 RNA (Figure S2B). The FOXM1 RNA bound by IGF2BP1 was enriched with m6A, as shown by m6A-IP (Figure S2C). Depletion of m6A by METTL3/14 knockdown resulted in reduced binding of IGF2BP1 to FOXM1 RNA (Figure S2D). It was reported that FOXM1 expression increases at the start of the S-phase and that FOXM1 induces cell proliferation (Laoukili et al., 2005). Moreover, FOXM1 has been described as an oncofetal protein that regulates stem cell renewal (Bella et al., 2014). All these traits are reminiscent of IQGAP3, which is induced by serum and associated with stem cell potential (Matsuo et al., 2021; Nojima et al., 2008). Moreover, the gene expression analysis of The Cancer Genome Atlas (TCGA) dataset which comprises 407 stomach adenocarcinoma samples revealed a strong positive correlation of IQGAP3 mRNA expression with that of FOXM1 (Figure S2E). The UCSC genome browser ChIP-seq public database showed small but clear FOXM1 binding in proximity to the H3K4me3 mark at the IQGAP3 promoter (data not shown). We and others have shown that SRF is a direct target of IGF2BP1 (this work and Muller et al., 2020). SRF is a well-established transcription regulator of mitogen-activated genes (eg. cytoskeletal genes) (Posern and Treisman, 2006). More recently, SRF was reported to repress cell-type-specific genes and promote pluripotency (Ikeda et al., 2018). We queried the publicly available UCSC genome browser ChIP-seq database using the IGV tool (Kent et al., 2002; Robinson et al., 2011) and observed the occupancy of SRF, which overlapped with its consensus binding sequence, at the IQGAP3 gene promoter in HCT-116 and MCF-7 cells (Figures S4A and S4B). The SRF binding site was enriched with the H3K4me3 epigenetic mark, which indicates active transcription. We, therefore, performed ChIP-qPCR using SRF antibody and confirmed the SRF binding site between 200 and 450 base pairs upstream of IQGAP3 promoter in NTERA-2 cells (Figures S4C and S4D). Unfortunately, our ChIP-seq experiment did not show SRF binding to IQGAP3, suggesting highly dynamic or transient interaction (data not shown). It would seem that IGF2BP1 regulates SRF and FOXM1 mRNA, which in turn influences IQGAP3 gene activity. Therefore, we performed siRNA knockdown of SRF and FOXM1 in NTERA-2 cells. Similar to NTERA-2 singly treated with IQGAP3 and IGF2BP1 siRNA, SRF and FOXM1 siRNA led to reductions in the expression of the core pluripotency markers NANOG, KLF4, SOX2, and MYC, whereas GFAP levels were increased (Figures 3C and 3D). Moreover, the morphology of cells after IQGAP3, IGF2BP1, SRF, or FOXM1 knockdown resembled that of differentiated NTERA-2 cells, suggesting that the NTERA-2 cells had undergone differentiation after IQGAP3, IGF2BP1, SRF, or FOXM1 knockdown (Figure 3E). Taken together, our results are indicative of an IGF2BP1-SRF-FOXM1-IQGAP3 cooperative in maintaining pluripotency in NTERA-2 cells. To further investigate the biological significance of this network, NTERA-2 cells treated with control siRNA (siC), siRNA targeting IQGAP3 (siIQGAP3), IGF2BP1 (siIGF2BP1), SRF (siSRF), or FOXM1 (siFOXM1) were subjected to RNA sequencing (RNAseq)-based transcriptome profiling. Gene set enrichment analysis (GSEA) of the RNAseq data revealed blastocyst formation among the top-ranked enriched gene signatures which were downregulated in siIGF2BP1-treated cells (Figure 3F). IGF2BP1 knockdown, therefore, promoted a more differentiated and less proliferative state in NTERA-2 cells. Similarly, GSEA of siSRF cells showed that genes related to blastocyst formation were downregulated (Figure 3F). Given that SRF destabilizes cell identity (Ikeda et al., 2018), and that SRF is a downstream target of IGF2BP1, it is not surprising that SRF knockdown is associated with a shift to the differentiation state. The GSEA of siFOXM1 also revealed the downregulation of blastocyst formation, suggesting the shutdown of embryogenesis upon FOXM1 downregulation (Figure 3F). Analysis of siIQGAP3 revealed the downregulation of genes associated with self-renewal (Figure 3F). These gene signatures indicate that IQGAP3 plays regulatory roles in the determination of cell fates and stemness. The GSEA of siIGF2BP1, siSRF, siFOXM1, and siIQGAP3 indicated the induction of the differentiated state, in agreement with the observations obtained from changes in cell morphology and RT-qPCR analysis after siRNA treatment. We next queried the shared gene targets of IGF2BP1, SRF, FOXM1, and IQGAP3. Of the 2755 genes that were downregulated in siIGF2BP1, siSRF, siFOXM1, and siIQGAP3 cells, 74 genes were common targets (Figure 3G and Table S3). Gene ontology analysis (GO) of these 74 genes revealed signaling pathways regulating pluripotency of stem cells, cellular response to retinoic acid, and let-7 inhibition of ES cell reprogramming as the top-ranked program, reflecting the transition of NTERA-2 cells toward the differentiated state upon knockdown of IGF2BP1, SRF, FOXM1, and IQGAP3 (Figure 3H). Moreover, pathways that have been highly associated with IQGAP3 and SRF such as the positive regulation of MAPK cascade, regulation of cell-cell adhesion, and regulation of actin cytoskeleton are among the top significant pathways, highlighting the important roles of SRF and IQGAP3 in this network (Figure 3H). Interestingly, the significant associations of these shared differentially expressed genes with tissue regeneration and degradation of extracellular matrix is reminiscent of the notion that “cancer is a wound that never heals” (Ge et al., 2017). We queried the TCGA dataset and observed that IQGAP3 expression is significantly increased in tumor lesions, compared to adjacent normal, in most of the tissues (Figures S5A and S5B). Moreover, IQGAP3 overexpression is associated with poor survival across all TCGA cancer datasets, and a similar pattern is observed for IGF2BP1 (Figure S5C).
We, therefore, examined the interplay of IGF2BP1, SRF, FOXM1, and IQGAP3 in regulating stem cell potential in cancer and the possibility of inhibiting this interplay for cancer treatment. Undifferentiated gastric cancer cell line HGC-27 was treated with siRNA targeting IGF2BP1, SRF, FOXM1, and IQGAP3. Similar to NTERA-2 cells, knockdown of IGF2BP1, SRF, FOXM1, or IQGAP3 resulted in reduced stemness and a more differentiated state. qPCR and Western blot analysis revealed drastic reductions in stem cell markers, such as OCT4, SOX2, NANOG, and CD44v9 (Figures 4A–4C). In gastric cells, KLF4 was reported to reduce self-renewal and promote differentiation (Miao et al., 2020). Accordingly, KLF4 levels remained unchanged in the differentiated cells. Moreover, differentiated cell marker Pepsinogen C (PGC) was induced in siIGF2BP1, siSRF, siFOXM1, and siIQGAP3, compared to control (siC) cells. To ascertain the proliferative capacity of the stem cells in control (siC) and IGF2BP1, SRF, FOXM1, and IQGAP3 siRNA-treated HGC-27 cells, we next performed the tumor spheroid assay. The treated cells were assessed for growth in serum-free and non-adherent conditions as only stem cells can proliferate in this environment (Johnson et al., 2013). In agreement with the gene expression data reported here (Figures 4A–4C) and previously reported data (Matsuo et al., 2021), siIGF2BP1, siSRF, siFOXM1, and siIQGAP3 treated cells showed a significant reduction in size and viability, relative to control (Figure 4D). Together, the siRNA treatments showed that the individual depletion of IGF2BP1, SRF, FOXM1, and IQGAP3 was sufficient to reduce stemness and promote the differentiation of HGC-27.
IQGAP3 expression is elevated in most, if not all, cancer cells (Dongol et al., 2020; Jinawath et al., 2020; Kumar et al., 2017; Matsuo et al., 2021; Monteleon et al., 2015; Shi et al., 2017; Wu et al., 2015, 2019; Xu et al., 2016). This indicates the importance of IQGAP3 as a cancer driver gene and its involvement in the fundamental aspect of carcinogenesis. That IQGAP3 is essential for cell proliferation and maintenance of stemness suggests that it is mainly associated with proliferating cancer stem cells. Depletion of IQGAP3 reduced the proliferation of breast and gastric cancer cell lines (Hu et al., 2016; Oue et al., 2018). Moreover, IQGAP3 has been shown to regulate metastasis and EMT (Jinawath et al., 2020; Shi et al., 2017). IQGAP3 is therefore a likely target for the treatment of aggressively proliferating cells as well as metastasis in most cancers. However, what causes the specific increase of IQGAP3 expression in cancer is unclear. Cell cycle regulator E2F1 was shown to transactivate the IQGAP3 promoter (Lin et al., 2019). More recently, YAP was reported to promote the binding of B-MYB to the IQGAP3 promoter and enhancer, thereby upregulating IQGAP3 transcription (Leone et al., 2021). Here, we identified regulators of IQGAP3 expression, which may explain its specific expression in proliferating stem cells and cancer cells. We report the importance of IGF2BP1-SRF-FOXM1-IQGAP3 signaling axis in maintaining stem cell properties in a pluripotent stem cell NTERA-2 and an undifferentiated gastric cancer cell line HGC-27. IGF2BP1 has long been implicated in cell metabolism and stem cell maintenance during early development (Degrauwe et al., 2016). We show that IGF2BP1 and IQGAP3 expression levels are highest in the blastocyst stage and that expression of both showed corresponding decreases during adulthood. The re-expression of IGF2BP1 during malignant transformation is likely to increase IQGAP3 mRNA stability. On the other hand, the differences between the Iqgap3 and Igf2bp1 expression levels in adult mouse stomach tissues suggest that there are mechanisms other than IGF2BP1, which regulate the IQGAP3 expression, especially in rapidly proliferating tissues similar to stomach. E2F1 or YAP, previously reported to have a role in the transcriptional regulation of IQGAP3, may be accountable for these mechanisms. Moreover, IGF2BP1-mediated increase of SRF and FOXM1 mRNA levels afford a further layer of IQGAP3 regulation, namely a link to mitogenic stimulation. SRF is a major regulator of actin cytoskeleton genes (Miano et al., 2007). It is, therefore, not surprising that IQGAP3, with its activities in the reorganization of cytoskeletal architecture and cell proliferation (Nojima et al., 2008; Wang et al., 2007), is an SRF downstream gene. Although the public dataset and our ChIP-qPCR showed SRF binding at or near its consensus sites at the IQGAP3 promoter, our inability to use ChIP-seq to show SRF binding to the IQGAP3 gene indicates that its binding is transient. FOXM1 is important for proliferation, self-renewal, and tumorigenesis (Liao et al., 2018). Similar to IQGAP3, FOXM1 is found mainly in highly proliferative cells, such as stem/progenitor cells, regenerating tissues, and cancer cells (Liao et al., 2018; Matsuo et al., 2021). The similarities between robust proliferation during tissue damage repair/regeneration and cancer have long been observed. IGF2BP1 plays important role in the tissue repair and homeostasis of the colonic epithelium (Chatterji et al., 2021; Hamilton et al., 2015; Manieri et al., 2012; Singh et al., 2020). Although our earlier study on stomach tissues did not show the upregulation of IGF2BP1 after tamoxifen-induced tissues damage, FOXM1 and SRF levels were increased, suggesting that both may be contributing to the strong IQGAP3 upregulation in the stomach during tissue repair. Our findings, which linked SRF and FOXM1 to the upregulation of IQGAP3 gene expression, raise many interesting questions: are they critical for IQGAP3’s ability to maintain self-renewal and drive proliferation in cancer cells? FOXM1 and SRF have been linked to chemoresistance (Okada et al., 2013; Whitson et al., 2018). Do they, in response to external stimuli, activate IQGAP3 to stimulate proliferation in rare quiescent cancer stem cells and thus confer chemotherapy resistance? Clearly, more research is required to determine the mechanistic basis of the associations between IQGAP3, SRF, and FOXM1. Undifferentiated cancer cells are regarded to be more malignant than well-differentiated cancers, which possess limited tumorigenic potential. Undifferentiated cancer cells, with stem-like properties, are responsible for aggressive metastasis. Drugs that target this IGF2BP1-SRF-FOXM1-IQGAP3 axis will be therapeutically attractive as inducers of terminal differentiation in cancer stem cells. Given the commonality of elevated IQGAP3 in many cancer types, our work suggests that, in addition to identifying drug inhibitors of IQGAP3, inhibitors of IGF2BP1 binding activity (Mahapatra et al., 2017), SRF/Rho/MRTF activity (Leal et al., 2019) and FOXM1 transcription (Petrovic et al., 2010; Sleiman et al., 2011)—some of which are in clinical trials—may potentially be used to deplete IQGAP3 and improve cancer treatment.
A limitation was that our study was performed using only two cell types, namely the pluripotent embryonic cancer cell line model NTERA-2 and the undifferentiated human gastric cancer cell line HGC-27. To assess the commonality of the IGF2BP1-SRF-FOXM1-IQGAP3 network, more cell types including adult stem cells as well as undifferentiated cancer cell lines from diverse tissues should be studied. Moreover, the comparison of protein expression levels between IGF2BP1, SRF, FOXM1, and IQGAP3 in tumor tissue microarrays may be needed. Nevertheless, this proof-of-concept study reveals the hitherto unknown relationship of IGF2BP1, SRF, FOXM1, and IQGAP3 and suggests avenues for future mechanistic studies on the regulation and pharmacological inhibition of IQGAP3 in cancer stem cells.
Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Yoshiaki Ito ([email protected]).
This study did not generate new unique reagents.
NTERA-2, human malignant pluripotent embryonal carcinoma cell line, obtained from ATCC (NTERA-2 cl.D1, Cat#CRL-1973, Lot#70004008) were cultured in DMEM (Dulbecco’s Modified Medium, Nacalai Tesque) with 10% FBS (Fetal bovine serum) at 37°C in a humidified 5% CO2 incubator according to the manufacturer’s instructions. Cells were maintained at high density and the medium was changed every 2–3 days. On confluency, cells were passaged at 1:4 ratio. For differentiation of NTERA-2, cells were treated with 10 μM of all-trans retinoic acid (Sigma-Aldrich, Cat#R2625) every 3–4 days for 28 days. HGC-27, human gastric cancer cell line, obtained from CellBank Australia, the European Collection of Cell Cultures (Cat#94042256), and HEK293T and HEK293FT cells obtained from ATCC were cultured respectively in RPMI 1640 (Nacalai Tesque) or DMEM (Dulbecco’s Modified Medium, Nacalai Tesque) with 10% FBS at 37°C in a humidified 5% CO2 incubator according to the manufacturer’s instructions. Cells were passaged at 1:10 ratio when the confluency reached 80–90%.
ON-TARGET plus SMARTpool siRNAs targeting human FOXM1, IGF2BP1, IQGAP3, SRF, METTL3/14 and a non-targeting siRNA pool (Dharmacon, Cat#D001810-10-50) as the control siRNA were used for the knockdown experiments. At 24 h after seeding in a 6-well culture plate, cells were transfected with 35 nM of siRNAs using jetPRIME (Polypus Transfection) according to the manufacturer’s protocol. At 48 h after transfection, cells were reseeded into a 6-well plate and a 6 cm dish which were then transfected in a similar manner at 6-8 h after seeding, and cells were harvested at 72 h later for RNA and protein quantification. The details of siRNA sequences are as described in Table S1.
Total RNA from the cell pellets was extracted using RNeasy Kit (Qiagen) with the removal of genomic DNA using the RNase-free DNase Set (Qiagen) according to the manufacturer’s instructions. Complementary DNA (cDNA) was prepared from 1 μg of total RNA extracted using iScript reverse transcription supermix for RT-qPCR (Bio-Rad). qPCR was performed using iTaq Universal SYBR green kit (Bio-Rad) and QuantStudio3 Real-Time PCR systems (Thermo Fisher Scientific), and the primers used are listed in Table S2. The fold-change in the expression levels of target genes in treated cells compared to control cells was calculated using the 2-ΔCT method where GAPDH was used as a housekeeping gene.
Cell pellets were first lysed by resuspending of the cell pellets with the lysis buffer (50 mM Tris pH 8, 150 mM NaCl, 0.1% SDS, 0.5% Sodium Deoxycholate and 1% NP-40) supplemented with Halt phosphatase inhibitor (Thermo Fisher Scientific), Complete protease inhibitor (Merck) and PMSF (Sigma-Aldrich) and incubating at 4°C for 45 min. After centrifugation of the lysates at 13500 rpm for 15 min at 4°C, the supernatant of each lysate was collected and the protein concentrations were measured using the Pierce BCA Protein Assay kit (Thermo Fisher Scientific, Cat # 23225) according to the manufacturer’s protocol. 40 μg of protein was loaded into each well of 8% SDS/PAGE. The antibodies used listed in key resources table.
For tumour spheroid assay, 1000 cells per well were seeded in an ultra-low attachment round bottom 96-well plate (Thermo Fisher Scientific, Cat # 174929), and cultured in normal growth medium. Cells were treated with siRNAs targeting genes of interest using reverse transfection method where suspension of cells were treated with 35 nM of siRNAs prior to seeding and jetPRIME (Polypus Transfection) was used according to the manufacturer’s protocol. Spheroid growth viability was determined on 5 days after seeding using CellTiter-GLO (Promega, Cat #G9681). Spheroid size was measured by using ImageJ software.
Blastocysts and adult mouse tissues samples were derived from C57BL/6 mouse. For adult mouse tissue samples, 16-week old mice were sacrificed and tissues (brain, heart, kidney, liver and stomach) were extracted. Tissues samples were washed in ice-cold PBS for 3 times, and processed for RNA extraction using Trizol reagent (Invitrogen). After adding Trizol, aqueous phase was collected, and RNA was precipitated at −20°C for overnight using isopropanol and glycogen. Precipitated RNA was then cleaned up using ethanol. cDNA synthesis and qPCR analysis were done as described above.
RNA immunoprecipitation (RIP) was performed with some modifications (Kwok et al., 2021). Briefly, cells seeded in a 10-cm plate were cross-linked by UV at 375J/cm2 and harvested by scraping. Total cell extracts were prepared using polysome lysis buffer (100 mM KCl, 5 mM MgCl2 , 10 mM Hepes (pH 7) and 0.5% NP-40) supplemented with 1× protease inhibitor, 200 units/ml Rnase out (Invitrogen, Cat #10777019) and 200 units/ml SUPERase IN (Ambion, Cat #AM2694), and 10% of the lysate was kept as an input. IGF2BP1 (MBL, Cat# RN007P) or rabbit IgG antibody (CST, Cat#2729) were incubated with Protein A/G Dynabeads® (Life Technologies, Cat #10015D) in 5% BSA (Bovine serum albumin) in PBS for 2 h at 4°C followed by an overnight incubation with 400 μg of cellular extracts at 4°C. Antibodies were used at the dilution of 1:75 for one RIP reaction. Reaction mixture was then washed for 5 times with NT2 buffer (50 mM Tris-HCL (pH 7.0), 150 mM NaCl, 10 mM MgCl2, 0.05% (v/v) NP-40) and RNA was eluted by incubating beads with 200ul of 1%SDS-TE buffer supplemented with 20ug of Proteinase K at 55°C for 30mins. RNA was extracted using Trizol reagent (Invitrogen), precipitated with ethanol and cleaned up using Phenol:Chloroform:Isoamyl Alcohol. For RIP-qPCR assay, cDNA was generated from input and IP samples using iScript cDNA synthesis kit (BioRad) and the transcript enrichment of known target genes and genes of interest were examined by doing real-time qPCR with iTaq Universal SYBR green kit (Bio-Rad) and QuantStudio3 Real-Time PCR systems (Thermo Fisher Scientific). Primers used in the experiments were listed in Table S2. For RIP-sequencing, NTERA-2 cells overexpressed with FLAG-IGF2BP1 and FLAG-affinity beads (Sigma Aldrich) were used, and RIP was performed as described above. RNA samples were sent to Beijing Genomics Institute (BGI) for cDNA synthesis, PCR amplification, transcriptome library preparation and sequencing.
Cells were treated with 5 μg/ml actinomycin D (Sigma, Cat# A9415) and harvested at 0 (no treatment), 30, 60, 120, 240 and 360 min after treatment. The extraction of total RNA from the cell lysate, cDNA synthesis, and the measurement of mRNA levels of target genes and housekeeping genes were done as described previously. The expression levels of target genes were calculated using the 2-ΔCT method where GAPDH was used as a housekeeping gene. The mRNA levels of target genes at different time points were normalized to the amount of mRNA at time 0. Using the GraphPad Prism 7.03 software, the linear regression analysis was done to generate the line that best fits the data from NTERA-2 cells, while the non-linear curve (one-phase decay) was used for the data from HEK293T cells, and the half-life of mRNA was calculated. For statistical analysis, area under curve (AUC) was calculated and compared between the lines that best fits the data using GraphPad Prism 7.03.
m6A-IP was done with some modifications from previously reported method (Dominissini et al., 2012). Total RNA was extracted using TRIzol (Invitrogen) and DNase I (QIAGEN) treatment was done to eliminate genomic DNA contamination. 150 ng of total RNA as an input, and 3 μg of RNA was used to incubate with 10 μg of m6A antibody (Sigma-Aldrich, Cat# MABE1006) or rabbit IgG antibody (CST, Cat#2729) conjugated to Protein A/G Dynabeads® (Life Technologies, Cat #10015D) in IP buffer (50 mM Tris-HCL (pH 7.4), 750 mM NaCl and 0.5% NP-40) supplemented with 200 units/ml Rnase out (Invitrogen, Cat #10777019) and 200 units/ml SUPERase IN (Ambion, Cat #AM2694). After overnight incubation at 4°C, RNA-antibody complexes were pelleted and washed with IP buffer for 3 times followed by the isolation of RNA with Trizol reagent (Invitrogen) and the RNA precipitation with ethanol. RNA was then cleaned up using Phenol:Chloro-form:Isoamyl Alcohol method. cDNA was generated from input and IP samples using iScript cDNA synthesis kit (BioRad) and the transcript enrichment of known target genes and genes of interest were examined by doing real-time qPCR with iTaq Universal SYBR green kit (Bio-Rad) and QuantStudio3 Real-Time PCR systems (Thermo Fisher Scientific). Primers used in the experiments were listed in Table S2.
For the pathway enrichment analysis of IGF2BP1’s target genes identified by RNA-IP sequencing, the target genes with the most statistically significant enrichment scores were selected and analysed using Metascape analysis tool (Zhou et al., 2019). The details of the analysis could be found on the webpage (https://metascape.org). Briefly, for each given gene list, pathway and process enrichment analysis has been carried out using the different ontology sources including KEGG Pathway, GO Biological Processes, Reactome Gene Sets, Canonical Pathways and WikiPathways. Gene ontology terms with p value < 0.01, a minimum count of 3, and an enrichment factor >1.5 (the enrichment factor is defined as the ratio between the observed counts and the counts expected by chance) are grouped into clusters. The term with the most statistically significant value within a cluster is taken to represent the cluster. "Log10(P)" means the p value in log base 10, and "Log10(q)" means the multi-test adjusted p value in log base 10. For the pathway enrichment analysis of commonly downregulated genes in all 4 different knockdown gene sets (downregulated genes in NTERA-2 cells after IGF2BP1, IQGAP3, SRF or FOXM1 knockdown), commonly downregulated genes were firstly defined using the publicly available tool called Draw Venn Diagram (ugent.be). The 74 commonly downregulated genes were then analyzed using Metascape analysis tool as described above.
Chromatin IP was performed with some modifications of previously published method (Lee et al., 2006). Briefly, cells were fixed with 1% formaldehyde for 10 min at room temperature (RT) and quenched by glycine (final concentration 125 mM) for 5 min at RT. Cells were washed 3 times by ice-cold PBS supplemented with 1 mM PMSF, collected by scrapping and then spinning down at 1500 rpm for 5 min. Nuclear extraction was done and nuclear extracts were resuspended in shearing buffer (1 mM EDTA, 10 mM Tris-HCl pH 7.6, 0.1% SDS) followed by sonication with ME220 Focused-ultrasonicator (Covaris) to achieve DNA fragments of sizes between 200 and 500 bp. Sonicated samples were then centrifuged at 13,000 rpm for 10 min to remove the cell debris and 1 mL of supernatant was incubated with 3 μg of desired antibody conjugated with Protein A/G Dynabeads (Life Technologies, Cat #10015D) for overnight at 4°C. Antibodies were listed in key resources table. Reaction mixture was then washed with ice-cold low salt wash buffer, high salt wash buffer, LiCl wash buffer and TE buffer supplemented with proteinase inhibitor. Bound DNA was then eluted by incubating with elution buffer (50 mM Tris-HCl, pH 8.0, 10 mM EDTA, 1% SDS) at 65°C for 30 min where tubes were quickly vortexed every 7–8 min. The eluted DNA-protein complexes were then treated with RNase A and proteinase K followed by incubating the reaction for overnight at 65°C for reverse cross-linking. DNAs were then purified by using QIAquick PCR purification kit (Qiagen). qPCR was done to measure the enrichment of the genes of interest bound by the target proteins.
For the analysis of the IQGAP3 mRNA expression in different human cancer types, IQGAP3 mRNA expression data available in TCGA Pan-cancer Atlas dataset was downloaded via UCSC Xena analysis tool (http://xena.ucsc.edu) (Goldman et al., 2020). The expression data for three subtypes which are adjacent normal, primary tumor, and metastatic tumor tissue samples in 33 different cancer types (n = 10,833) were then analyzed using GraphPad Prism 7.03 software. To compare IQGAP3 mRNA expression levels between normal and tumor samples in 18 different human tissues, IQGAP3 mRNA expression data available in TCGA and GTEX datasets were downloaded from UCSC Xena analysis tool (http://xena.ucsc.edu) (Goldman et al., 2020). The expression data derived from the normal and tumor tissue samples (n = 11493) were analysed using GraphPad Prism 7.03 software. GEPIA (http://gepia.cancer-pku.cn/) was used to analyse the association between the expression levels of IQGAP3 and the overall survival in months across 33 different human cancer types available on TCGA datasets(Tang et al., 2017). GEPIA uses the Mantel-Cox test to calculate the hazards-ratio, and high-expression and low-expression cohorts were defined with the cut-off threshold set at 50%. Percent survival was calculated as the percentage of patient in the defined cohort who remained alive for a given period in months. Hazards ration of greater than 1 was defined as high and p value of less than 0.05 was defined as statistical significance.
RNA-seq reads were mapped by STAR to the human reference genome GRCh37 with reference gene annotation GENCODE 26 (Dobin et al., 2013; Harrow et al., 2012). Reads with low mapping quality <20 were not used for further analysis. Next, PCR duplicates were removed in the paired-end alignments using SAMtools. Gene expression levels of individual genes/transcripts were generated using featureCounts (Liao et al., 2014). Cross-sample normalization of reads counts was based on total mappable counts using RPKM. Normalized read counts were then applied to perform GSEA analysis to identify significantly enriched pathways/gene sets between the wildtypes and their corresponding knockdowns. The full version of MSigDB v7.2 was employed as GSEA dataset database.
Reads from the RIP-Seq samples and the corresponding controls were mapped against human reference genome GRCh37 by STAR with GENCODE 26 for transcriptome annotation. First, peak calling was performed by MACS2 to identify RIP binding enriched regions (Zhang et al., 2008). For reads mapped to multiple exons or peaks presented in neighboring exons, the peaks were merged together. Sequences covered by the reproducible peaks of the duplicated samples were extracted for motif finding. The upstream and downstream sequences of reproducible peaks were also extracted and served as the background sequences in the motif finding. Motif discovery is performed with MEME suite using differential enrichment mode (Bailey et al., 2009; Bailey and Elkan, 1994).
Statistical analyses were done by using Student’s t-tests (two-tailed) and all experiments were conducted at least for three replicates as indicated in the figure legends. For the overall survival curves, log rank analysis method was used to determine statistical significance. Data were presented as mean with standard deviation and p-value of <0.05 was considered as a statistical significance. For RNA-seq, three sets of RNA samples were used, and for RIP-seq, two sets of RNA samples were used. All western blot and brightfield images were representative of three independent experiments. | true | true | true |
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PMC9547309 | Rulu Pan,Yan Yu,Haiyan Zhu,Wenyi Zhang,Yuan Qin,Lin Ye,Juji Dai,Ren Huang,Xinyan Peng,Siqi Ye,Ziqi Lin,Shishun Huang,Shuyi Chong,Liting Lu,Xincheng Lu | RSPO2 promotes progression of ovarian cancer through dual receptor-mediated FAK/Src signaling activation | 23-09-2022 | Cell biology,cancer | Summary R-spondin 2 (RSPO2) drives the potentiation of Wnt signaling and is implicated in tumorigenesis in multiple cancers, but its role in ovarian cancer has not been investigated. Here, we reported that RSPO2 promoted the growth and metastasis of ovarian cancer through the activation of FAK/Src signaling cascades. RSPO2 enhanced the autophosphorylation of FAK and Src through a unique dual receptors mechanism. First, RSPO2-LGR4 interaction prevented the endocytic degradation of LGR4 and promoted LGR4-mediated translocation of Src to the plasma membrane. Second, RSPO2 directly bound to integrin β3 as a ligand and enhanced the stability of integrins, and both actions potentiated autoactivation of FAK and/or Src in ovarian cancer cells. RSPO2 expression was increased in ovarian tumors and was associated with poor prognosis in patients. Our study highlights the importance of RSPO2 in ovarian tumor progression and suggests that targeting RSPO2/FAK/Src cascades may constitute potential approaches to inhibit the progression of aggressive ovarian cancer. | RSPO2 promotes progression of ovarian cancer through dual receptor-mediated FAK/Src signaling activation
R-spondin 2 (RSPO2) drives the potentiation of Wnt signaling and is implicated in tumorigenesis in multiple cancers, but its role in ovarian cancer has not been investigated. Here, we reported that RSPO2 promoted the growth and metastasis of ovarian cancer through the activation of FAK/Src signaling cascades. RSPO2 enhanced the autophosphorylation of FAK and Src through a unique dual receptors mechanism. First, RSPO2-LGR4 interaction prevented the endocytic degradation of LGR4 and promoted LGR4-mediated translocation of Src to the plasma membrane. Second, RSPO2 directly bound to integrin β3 as a ligand and enhanced the stability of integrins, and both actions potentiated autoactivation of FAK and/or Src in ovarian cancer cells. RSPO2 expression was increased in ovarian tumors and was associated with poor prognosis in patients. Our study highlights the importance of RSPO2 in ovarian tumor progression and suggests that targeting RSPO2/FAK/Src cascades may constitute potential approaches to inhibit the progression of aggressive ovarian cancer.
Ovarian cancer, with epithelial ovarian cancer (EOC) as the most common histological type, is the most lethal gynecological malignancy, causing 184,799 deaths annually (Bray et al., 2018). Owing to its late-stage diagnosis, peritoneal dissemination, high relapse rate, and acquisition of drug resistance, EOC has a poor prognosis, with a 5-year survival rate of approximately 30% (Reid et al., 2017; Lheureux et al., 2019). Therefore, characterizing novel therapeutic targets and molecular mechanisms that mediate tumor progression is of great clinical significance to improve the treatment of ovarian cancer. The R-spondin (RSPO) protein family has four homologous members that are evolutionarily conserved in vertebrates, showing 60% amino acid sequence homology (Jin and Yoon, 2012). All four RSPOs contain tandem furin-like repeats (FUs), a thrombospondin type 1 (TSP) domain, and a basic region (BR) (Jin and Yoon, 2012; Yoon and Lee, 2012). RSPOs were first identified as potent agonists of the Wnt/β-catenin signaling pathway (Kim et al., 2008; Nam et al., 2006). Mechanistically, RSPOs bind to three leucine-rich repeat-containing G-protein-coupled receptors (LGRs), LGR4/5/6, through their FUs domain. RSPO/LGR interactions neutralize two transmembrane E3 ubiquitin ligases, ZNRF3 and RNF43, which prevents the internalization and degradation of cell surface Wnt receptors and eventually amplifies Wnt/β-catenin signaling (Carmon et al., 2011; Hao et al., 2012). RSPO-mediated Wnt/β-catenin signaling activation participates in a broad range of biological and physiological processes, such as cell proliferation, development, stem cell maintenance, and tumorigenesis (Yan et al., 2017; Vidal et al., 2020; Knight and Hankenson, 2014; Ter Steege and Bakker, 2021; Kim et al., 2005). R-spondin 2 (RSPO2) is an important member of the RSPO family. In humans, polymorphisms in the RSPO2 gene lead to genetic susceptibility to Dupuytren contracture (Dolmans et al., 2011). Mice with the knockout of Rspo2 exhibit severe developmental abnormalities, including lung hypoplasia and defects in craniofacial and limb development (Szenker-Ravi et al., 2018; Bell et al., 2008). RSPO2 has also been implicated in hair growth, osteoblastic differentiation, and osteoarthritis through the potentiation of Wnt/β-catenin signaling (Knight et al., 2018; Smith et al., 2016; Okura et al., 2019). Notably, RSPO2 has recently been identified as an important regulator of tumorigenicity. Rearrangement and fusion of RSPO2 occur in several types of tumors, such as colon, prostate, and liver tumors (Seshagiri et al., 2012; Longerich et al., 2019; Robinson et al., 2015). RSPO2-mediated activation of Wnt/β-catenin signaling has been shown to promote the growth and metastasis of diverse tumors, including tongue squamous cell carcinomas, pancreatic and breast tumors (Ilmer et al., 2015; Ter Steege and Bakker, 2021; Zhang et al., 2019). Intriguingly, two previous studies demonstrated that RSPO2 inhibits colorectal cancer growth through unique LGR5-mediated Wnt/β-catenin signaling negative feedback mechanism, and RSPO2-mediated suppression of noncanonical Wnt signaling also exerted an inhibitory effect on colon tumor metastasis (Wu et al., 2014; Dong et al., 2017). A recent study showed that RSPO2 acts as a tumor suppressor in HCC by inhibiting the MAPK signaling pathway (Zheng et al., 2020). Taken together, these findings suggest that the role of RSPO2 in tumorigenesis is complex and that its functions may be dependent on the type of cancer, the presence of receptors, and the cellular context. RSPO2 signaling has been shown to be essential for oocyte-driven intercellular communication and follicular growth (Cheng et al., 2013; De Cian et al., 2020). Moreover, the mutation of RSPO2 is associated with primary ovarian insufficiency and the survival of patients with high-grade serous ovarian cancer (Bouilly et al., 2017; Lee et al., 2020). These findings imply that RSPO2 may play a role in female fertility, ovarian follicle maturation, and even ovarian carcinogenesis. However, the biological function of RSPO2 in ovarian cancer progression remains unexplored. In this study, we investigated the role of RSPO2 in ovarian cancer progression. We demonstrated that RSPO2 enhanced the malignant biological behaviors of ovarian cancer cells, including proliferation, migration, and invasion, as well as their ability to adhere to the extracellular matrix in vitro. Furthermore, we showed that RSPO2 promoted the metastatic spread of cancer cells in an orthotopic ovarian xenograft model and that these phenotypes were primarily ascribed to the activation of FAK/Src signaling pathways. Mechanistically, we revealed novel crosstalk between RSPO2 and FAK/Src signaling and determined that RSPO2 can mediate the autoactivation of FAK and Src by binding to two specific receptors.
To determine whether the expression of RSPO2 is dysregulated in ovarian cancer, we first examined the expression of RSPO2 in multiple ovarian cancer cell lines by qRT-PCR. The mRNA expression of RSPO2 in cancer cells was generally higher than that in ovarian epithelial IOSE80 cells (Figure 1A). Next, we measured RSPO2 protein expression in ovarian cancer specimens by tissue microarray analysis. The microarray test set comprised 30 patients newly diagnosed with EOC and aged 27 to 84 years (mean, 55 years). Immunohistochemical analysis of paired tumor and nontumor tissue specimens showed that RSPO2 was more intensely and extensively expressed in tumor tissues than in normal tissues (Figure 1B). Staining quantification showed that RSPO2 expression in ovarian tumor tissues was significantly higher than that detected in the paired normal tissues (Figure 1C). Moreover, mining of the ovarian cancer cohort in the TCGA database showed that high RSPO2 expression was associated with a lower survival rate in patients with ovarian cancer (Figure 1D). Kaplan-Meier analysis of another ovarian cancer dataset (GSE26193) also showed a significant association between high RSPO2 expression and poor survival (Figure 1E). Collectively, these results suggest that the expression of RSPO2 is elevated in ovarian cancer and associated with poor prognosis in patients.
The dysregulated expression of RSPO2 in tumor tissues inspired us to investigate its role in ovarian malignancy. Based on the characteristic that RSPO2 is a secretory protein, we first established stable transfectants of RSPO2-overexpressing ovarian tumor cells by pooling G418-resistant clones (Figure S1A). Overexpression of RSPO2 in A2780 and OVCAR3 tumor cells markedly enhanced their growth capability as evaluated by MTT and colony formation assays (Figures 2A and S1B). To determine the specificity of RSPO2 on tumor growth, we next screened two siRNAs (siRS2-1# and siRS2-2#) that can effectively target RSPO2 in two ovarian cancer cell lines, and then used the most effective interference sequence siRS2-2# to construct the lentiviral vector (shRS2) (Figures S1C and S1D). siRNA and shRNA-mediated RSPO2 knockdown both significantly reduced cell growth of A2780 and OVCAR3 tumor cells (Figures 2B, S1E, and S1F). Together, these results indicate that RSPO2 plays a promotive role in ovarian cancer cell growth in vitro. Peritoneal dissemination and metastasis are characteristics of ovarian malignancy (Yeung et al., 2015). Ectopic overexpression of RSPO2 resulted in increases of 4- to 6-fold in the migration and invasion abilities of A2780 and OVCAR3 cells (Figures 2C and 2D). RSPO2 overexpression also increased motility in both ovarian cancer cell lines (Figure 2E). In contrast, knockdown of RSPO2 markedly suppressed the migration and invasion of A2780 and OVCAR3 tumor cells (Figures S2A and S2B). Consistent with the migration-promoting function of RSPO2 in vitro, stable overexpression of RSPO2 markedly promoted metastatic colonization of ovarian cancer cells in an orthotopic mouse model, including increases in the number of metastatic nodules, tumor size, and tumor weight (Figures 2F–2H and S2E). Mice injected with RSPO2-overexpressing cells also showed greater accumulation of ascites fluid in the peritoneal cavity than did control mice (Figure 2I). In addition, mice injected subcutaneously with A2780 cells (with a high level of RSPO2 expression) harboring shRSPO2 developed a markedly decreased tumor burden compared to that in mice injected with shNC control cells (Figures S2C and S2D). Taken together, these results strongly suggest that RSPO2 functions as an oncogene in ovarian cancer progression by promoting tumor cell growth and metastasis.
Gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the TCGA database showed that genes composing the actin cytoskeleton and focal adhesion program signatures, two programs associated with metastatic properties of cancer cells, were highly enriched in ovarian tumor samples with high RSPO2 expression (Figure 3A). Consistent with the bioinformatic analysis results, overexpression of RSPO2 led to increased adhesion of A2780 and OVCAR3 cells to the extracellular matrix component in culture (Figure 3B). Morphologically, overexpression of RSPO2 promoted the transformation of most ovarian cancer cells from a round (epithelial phenotype) to a spindle shape (mesenchymal phenotype) (Figure 3C). F-actin staining further confirmed RSPO2-mediated cytoskeletal rearrangement, including the gain of actin stress fibers and increased lamellipodia and filopodia formation (Figure 3D). As the reorganization of the actin cytoskeleton and concomitant formation of membrane protrusions are essential steps in cell migration during the activation of the epithelial-mesenchymal transition (EMT) program (Nieto et al., 2016), we next assessed the effect of RSPO2 on protein markers associated with EMT. In RSPO2-overexpressing A2780 and OVCAR3 cells, the expression levels of N-cadherin and fibronectin were increased, whereas those of E-cadherin and ZO-1 were markedly reduced (Figure 3E). In addition, RSPO2 overexpression induced the upregulation of matrix metalloproteinases (MMPs), including MMP2 and MMP7, in both cell lines (Figure 3E). These data suggest that RSPO2 affects the EMT process and extracellular matrix degradation, both of which play a significant role in the invasion of ovarian cancer cells. Overexpression of RSPO2 also elicited elevated expression of cell cycle proteins such as cyclin D1 and E1 (Figure 3E). Correspondingly, the knockdown of RSPO2 triggered G1 arrest (Figure 3F). These data indicate that RSPO2 is involved in cell cycle regulation. Taken together, the above results suggest that RSPO2 promotes ovarian cancer progression by affecting cell adhesion, EMT, and cell cycle progression.
RSPO2 promotes a variety of biological processes involved in tumor progression by potentiating Wnt/β-catenin signaling (Yoon and Lee, 2012; Ter Steege and Bakker, 2021). Surprisingly, our initial experiments showed that overexpression of RSPO2 or treatment with recombinant RSPO2 protein did not stimulate obvious Wnt/β-catenin signaling responsiveness in A2780 and OVCAR3 cells (Figures S3A–S3D). Manipulating the expression of RSPO2 did not change the levels of Frizzled 6/7, nor did the Frizzled inhibitor niclosamide abolish the tumor-promoting effect of RSPO2 in two cells (Figures S3E–S3H). To elucidate the Wnt-independent mechanisms by which RSPO2 promotes ovarian cancer progression, we compared the gene expression profiles of parental and RSPO2-overexpressing A2780 cells through transcriptomic sequencing. Similar to the findings in the previous KEGG analysis using a TCGA cohort, the dysregulated genes were enriched in cytoskeletal/focal adhesion-related signatures. Tumor growth- and cell survival-related pathways, such as MAPK and PI3K/Akt, were profoundly enriched and upregulated in RSPO2-overexpressing A2780 cells (Figure 4A). Consistent with the transcriptome analysis results, either overexpression of RSPO2 or treatment with recombinant RSPO2 protein enhanced the phosphorylation of FAK at Tyr397 (p-FAK), Src at Tyr416 (p-Src, Y416), EGFR at Tyr1068 (p-EGFR) and Akt at Ser473 (p-Akt) without affecting the abundance of the corresponding proteins (Figures 4B, S4A, and S4B). Markedly increased FAK/Src/Akt phosphorylation was also observed in RSPO2-high metastases from xenograft tumors (Figure S4C). Conversely, RSPO2-depleted cells showed lower p-FAK, p-Src and p-Akt levels than the nontargeting control-transduced cells (Figure 4C). Furthermore, treatment with Src and FAK inhibitors abrogated the promotive effect of RSPO2 on the proliferation and the migration of ovarian cancer cells (Figures 4D, 4E, S4D, and S4E). These results suggest that the activation of FAK and Src is responsible for RSPO2-promoted ovarian cancer progression. In addition, the inhibition of FAK activity abolished the effect of RSPO2 on EMT marker and MMP7 expression, supporting its critical role in cell migration and invasion (Figure 4F). Inhibition of Src activity attenuated RSPO2-induced EGFR/Akt phosphorylation (Figure 4G), whereas the suppression of Akt activity largely reduced the promotive effect of RSPO2 on cell proliferation (Figures S4F–S4G), suggesting that RSPO2-induced Src/Akt activation mainly accounts for tumor growth. Taken together, these sets of data suggest that RSPO2 promotes ovarian cancer progression through the activation of FAK/Src signaling cascades.
Next, we investigated the molecular mechanisms by which RSPO2 activates FAK/Src signaling cascades in ovarian tumor cells. As RSPOs often directly bind to their receptors, LGRs, to potentiate downstream signaling pathways (Yoon and Lee, 2012), we first examined the changes in LGRs expression in response to RSPO2 stimulation. Western blot analysis showed that either ectopic RSPO2 overexpression or RSPO2 protein treatment increased the protein level of LGR4 but had no significant effect on the level of LGR5 (Figures 5A and S5A). Upregulated LGR4 protein expression was also confirmed in xenograft tumor samples with high RSPO2 expression (Figure S5B). Moreover, knockdown of LGR4 in A2780 and OVCAR3 cells largely antagonized the growth promotive effect of RSPO2 and partially impaired the RSPO2-induced cancer cell migration (Figures 5B, S5C, and S5D). These results suggest that the upregulation of LGR4 plays a key role in RSPO2-promoted ovarian cancer growth. RSPO2 did not affect the mRNA level of LGR4 in either of these ovarian cancer cell lines (Figure S5E). However, cycloheximide (CHX)-chase assay showed that overexpression of RSPO2 markedly delayed the degradation of LGR4 protein (Figure 5C). Moreover, dense colocalization of LGR4 and LAMP1 was observed in the cytoplasm of A2780 and OVCAR3 cells, whereas RSPO2 protein treatment attenuated the colocalization of these two proteins and significantly increased the distribution of LGR4 on the plasma membrane (Figure S5F). Taken together; these results suggest that RSPO2 prevents the endocytosis and lysosome-mediated degradation of LGR4 in ovarian cancer cells. Presilencing of LGR4 impaired RSPO2-stimulated Src/Akt activation (Figure 5E). In addition, ectopic overexpression of LGR4 enhanced Src phosphorylation in A2780 and OVCAR3 cells, whereas concomitant overexpression of LGR4 and RSPO2 further sensitized cells to Src activation induced by RSPO2 or LGR4 alone (Figures S6A and S6B). Collectively, these results suggest that LGR4 plays a key role in RSPO2-induced Src activation. Immunofluorescence imaging showed that Src was diffusely expressed throughout the cytoplasm in A2780 and OVCAR3 cells and that RSPO2 protein treatment caused its translocation from the cytosol to the plasma membrane (Figure 5D), which is the characteristic of Src autophosphorylation (Roskoski, 2015). Notably, significantly increased the colocalization of LGR4 and Src was observed on the plasma membrane of RSPO2-treated cells (Figure 5D). These results prompted us to consider that RSPO2 may promote membrane translocation and autophosphorylation of Src through the LGR4-Src interaction. Indeed, ectopically expressed RSPO2 pulled down endogenous LGR4 or Src in both A2780 and OVCAR3 cells (Figure S6C), and reciprocal interactions between endogenous LGR4 and Src were validated by Co-IP (Figure 5F). Furthermore, RSPO2 protein treatment obviously increased the affinity of LGR4 for Src (Figure 5G). Taken together; these results suggest that RSPO2, LGR4, and Src can form a complex on the plasma membrane and that RSPO2 stimulates the autoactivation of Src through LGR4-mediated membrane translocation of Src.
Integrins are well-established upstream inducers of FAK/Src signaling activation (Mitra and Schlaepfer, 2006). In a small-scale screen, we found that knockdown of RSPO2 decreased endogenous integrin αv and β3 levels in A2780 and OVCAR3 cells (Figure 6A). Correspondingly, stable overexpression of RSPO2 elevated the protein levels of integrin αv and β3 in these cells (Figures S7A and S7B). These results suggest that integrins may be involved in RSPO2- induced FAK/SRC signal activation. In A2780 and OVCAR3 cells, presilencing of integrin αv/β3 abolished the enhancing effect of RSPO2 on FAK phosphorylation and partially diminished the activation of Src (Figures 6B, and S7C). Furthermore, knockdown of integrin αv/β3 also reduced the promotive effects of RSPO2 on cell adhesion and migration and partially blocked RSPO2-enhanced cancer cell growth (Figures 6C, S7D, and S7E). These results indicate that the upregulation of integrin αv/β3 participates in RSPO2-induced FAK/Src activation and tumor progression. Treatment with MG132 blocked the reduction of integrin αv/β3 in RSPO2-silenced ovarian cancer cells (Figure S7F). Moreover, higher levels of ubiquitinated integrin αv and β3 were observed in RSPO2-silenced cells than in control cells (Figure 6D). These results suggest that RSPO2 prevents the ubiquitination and degradation of integrin αv/β3. RSPOs have been shown to bind to several different intracellular signal proteins to regulate their stability (Carmon et al., 2011; Nam et al., 2006). Indeed, reciprocal interactions between RSPO2 and integrin αv and β3 were verified in both cell lines by Co-IP (Figures 6E and S7G). These results suggest that RSPO2 may serve as a binding ligand for integrin αv and/or β3. To show a direct physical interaction, we performed an in vitro pulldown assay using recombinant RSPO2 protein and found that purified RSPO2 pulled down integrin β3 but not integrin αv in cell lysates (Figure 6F). To further determine the specific regions of RSPO2 responsible for mediating its interaction with integrin β3, we generated mutants with two FUs or a C-terminal TSP domain. Co-IP assays demonstrated that both full-length RSPO2 and its FUs fragment bound specifically to LGR4 and integrin β3, whereas no binding of the TSP fragment to either LGR4 or integrin β3 was detected (Figure 6G). Furthermore, the FUs fragment potentiated the phosphorylation of both Src and FAK (Figure S7H). These results suggest that RSPO2 directly binds to integrin β3 via the FUs domain. Taken together, the above results support the hypothesis that RSPO2 acts as a ligand for integrin β3 and thus increases the stability of integrins, which induces downstream FAK/Src signaling activation and ovarian cancer progression.
Recently, the importance of RSPO2 in development and tumorigenicity has been increasingly recognized (Ter Steege and Bakker, 2021). However, little is known about the function of RSPO2 in ovarian cancer. In this study, we demonstrated that RSPO2 plays an oncogenic role in ovarian cancer progression by promoting the growth and metastasis of ovarian cancer cells. Consistent with its oncogenic function, the RSPO2 protein level was increased in human ovarian tumor specimens and associated with poor prognosis. Mechanistically, we revealed that RSPO2 promotes ovarian cancer progression by enhancing FAK/Src signaling cascades via two unexpected actions. First, RSPO2 promoted LGR4-mediated recruitment of Src to the plasma membrane. Second, RSPO2 is directly bound to integrin β3 as a ligand and thus increased the stability of integrins, and both actions potentiate the autoactivation of FAK and/or Src in ovarian cancer cells. Based on our results, we proposed a novel Wnt-independent mechanism underlying the promotive effect of RSPO2 on ovarian cancer progression (Figure 7). RSPOs have been shown to potentiate the Wnt/β-catenin signaling pathway in a variety of cancers (Ter Steege and Bakker, 2021), but whether RSPOs crosstalk with other intracellular signaling pathways to regulate tumor progression remains poorly understood. In the current study, we provided evidence that independent of Wnt signaling, RSPO2 promotes ovarian cancer progression by potentiating FAK/Src signaling cascades. Both FAK and Src are nonreceptor tyrosine kinases that are implicated in nearly every step of cancer progression (Sulzmaier et al., 2014; Frame, 2002). FAK/Src overexpression and/or activation occur in most epithelial ovarian cancers and are significantly associated with poor patient survival (Sood et al., 2004; Wiener et al., 2003; Huang et al., 2013). Via FAK/Src inhibitor treatment and functional rescue experiments, we validated the critical role of FAK/Src signaling activation in RSPO2-promoted ovarian cancer progression. Our data suggested that RSPO2-mediated hyperactivation of Src/Akt participates in cell cycle progression, thus providing a growth advantage to ovarian cancer cells. Moreover, we demonstrated that the inhibition of FAK activity largely reduced the promotive effects of RSPO2 on tumor metastasis indicators such as EMT, MMPs secretion, cell adhesion, and migration. These results suggest that FAK signal activation may primarily contribute to the RSPO2-triggered ovarian cancer metastasis. Inhibition of FAK or Src also partially impaired RSPO2-promoted cancer cell proliferation and migration, respectively, indicating that FAK/Src mutual activation in RSPO2-overexpressing tumor cells may synergistically promote tumor progression. Several studies have reported that aberrant activation of FAK/Src is an important cause of chemotherapeutic resistance in ovarian cancers (Levy et al., 2019; George et al., 2005; Halder et al., 2005). Here, we demonstrated that the pharmacological inhibition of RSPO2-induced FAK/Src activation significantly impaired ovarian cancer cell growth and migration, suggesting that the RSPO2/FAK/Src axis is a druggable target. Given that targeting tumor-derived RSPO2 with monoclonal antibodies effectively retarded the growth of patient-derived xenograft (PDX) tumors, including ovarian tumor (Chartier et al., 2016; Storm et al., 2016), the antibody-based RSPO2 blockage may be a useful adjuvant treatment to improve the outcomes of ovarian cancer patients with high RSPO2 expression. Abnormal activation of Src has been documented in ovarian cancer, but the regulatory mechanism of Src activation has not been fully clarified (Simpkins et al., 2018; George et al., 2005). In the current study, we identified RSPO2 as a novel positive regulator of Src autoactivation. Activation of Src is tightly regulated by phosphorylation/dephosphorylation processes, and dephosphorylation of the Tyr527 residue results in its activation by the autophosphorylation of Tyr416 (Roskoski, 2005). Translocation of inactive Src to the plasma membrane is an alternative way to trigger Src autophosphorylation (Roskoski, 2015; Sandilands and Frame, 2008). Here, we found that RSPO2 stimulation increased the distribution of Src on the plasma membrane but did not affect the total amount of Src or the phosphorylation of Src at Tyr527. Our results suggest that the membrane translocation of Src is the main cause of Src activation in RSPO2-treated ovarian cancer cells. We showed that RSPO2 increased the distribution of LGR4 on the plasma membrane and thereby prevented its endocytic degradation. More importantly, we demonstrated that the presilencing of LGR4 counteracted RSPO2-induced Src hyperactivation and cell proliferation. Our study suggests that LGR4 is a key mediator in RSPO2-induced Src autoactivation. The RSPO-LGR4 complex is well-established to bind with intracellular Wnt signaling proteins such as ZNRF3, RNF43, and IQGAP1 to form supercomplex (Carmon et al., 2011, 2014). We validated a physical interaction between endogenous LGR4 and Src. On the other hand, we showed that RSPO2 was intimately associated with the interaction of LGR4 with Src. Our data showed for the first time that there is a physical interaction between LGR4 and Src, indicating that RSPO2, LGR4, and Src can form a supercomplex on the plasma membrane. Taken together; our study provides new mechanistic insights into the activation of Src in ovarian cancer cells: the RSPO2-LGR4 interaction increases the distribution of LGR4 on the plasma membrane as well as its association with Src, which, in turn, enhances Src recruitment to the inner surface of the plasma membrane for autoactivation. Integrins regulate multiple cellular functions crucial to the growth and metastasis of solid tumors (Mitra and Schlaepfer, 2006). In ovarian tumors, altered integrins expression or abnormal activation of integrins has been shown to contribute to the proliferation, invasion, and chemoresistance of ovarian cancer cells (Davidson et al., 2003; Dolinschek et al., 2021; Lengyel, 2010). In this study, we found that overexpression of RSPO2 increased the total amounts of integrin-αv/β3 in ovarian cancer cells by preventing their ubiquitination and degradation. Several studies have claimed that the FAK/Src dual-kinase complex is a key adapter in integrin-mediated signal transduction pathways for tumor growth and metastasis (Mitra and Schlaepfer, 2006; Seguin et al., 2015). Consistent with these findings, we demonstrated that the presilencing of integrin-αv/β3 not only blocked RSPO2-induced FAK/Src phosphorylation but also attenuated the RSPO2-promoted tumor cell proliferation and migration. Our results suggested that integrin-mediated FAK/Src signaling activation plays a critical role in RSPO2-promoted ovarian cancer progression. Integrins are multifunctional receptors that exist as heterodimers composed of α and β subunits and bind to various ligands (Mitra and Schlaepfer, 2006). We demonstrated that RSPO2 enhanced the stability of integrins by direct physical interaction with integrin β3. Our data suggest that the secreted protein RSPO2 acts as a new ligand for integrin β3 and that the binding of RSPO2 to integrin β3 may enhance the stability of the integrin-αv/β3 heterodimer and thus activates downstream FAK/Src signaling. In this study, we further mapped the integrin β3 binding site in RSPO2 to its FUs domain, similar to the domain that interacts with LGRs. Intriguingly, a recent study showed that the binding of the TSP domain of RSPO2 to the ALK3 receptor inhibited BMP signaling in acute myeloid leukemia (AML) cells (Sun et al., 2021). Taken together, these findings suggest that RSPO2 is a multipotent ligand that can bind to different plasma membrane receptors through its FUs or TSP domain to regulate different cell signaling cascades. In summary, we demonstrated that RSPO2 acts as an oncogene in ovarian cancer progression. We elucidated a Wnt-independent mechanism by which RSPO2 promotes ovarian cancer cell growth and metastasis through the potentiation of FAK/Src signaling. RSPO2 enhances the autoactivation of FAK and Src by binding with the specific receptors integrin β3 and LGR4, respectively. Our study suggests that the disruption of RSPO2/FAK/Src signaling cascades may be a therapeutic strategy for aggressive ovarian cancer.
There are three major limitations in this study that could be addressed in future research. First, this study would be strengthened by including more high-grade ovarian cancer (HGOC) cell lines to consolidate the major findings. Second, the association between RSPO2 expression and clinical pathologic features of individuals could not be analyzed owing to the unavailability of sufficient paired ovarian tumor samples, and exploration with a large sample size is needed to further support this finding. In addition, further investigations are required to elucidate the underlying mechanism of how RSPO2 expression is upregulated in ovarian cancer tissues.
Information and requests for resources should be directed to and will be fulfilled by the lead contact, Xincheng Lu ([email protected]).
This study did not generate new unique reagents.
The A2780, OVCAR3 and HEK293T cell lines were originally obtained from the American Type Culture Collection (ATCC, USA). All cells were cultured in the recommended medium (DMEM for A2780 and RPMI-1640 for HEK293T and OVCAR3 cells) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin at 37°C in 5% CO2. The A2780, OVCAR3 and HEK293T cell lines had recently been authenticated using short tandem repeat DNA profiling, and all cell lines tested negative for mycoplasma contamination before the experiment.
Recombinant human RSPO2 protein (3266-rs-025/cf) and Wnt3a (5036-WN-500) was purchased from R&D Systems (USA). The FAK inhibitor defactinib (1073154-85-4) was purchased from RayStar Biosystems (China). The Src inhibitor saracatinib (S1006) and Akt inhibitor LY294002 (S1105) were purchased from Selleck (China). The Frizzled inhibitor Niclosamide was purchased from Sigma-Aldrich (St. Louis, MO). Cycloheximide(CHX) was purchased from Sigma (C7698). SiRNAs targeting the open reading frames of RSPO2, LGR4, ITGAV, and ITGB3 were synthesized by GenePharma (Shanghai, China). Lentivirus containing shRNA against RSPO2 was designed and produced by GeneChem Co. (Shanghai, China), siRNA and shRNA sequences are listed in Table S1. Cells grown to a confluence of 50–70% were transfected with siRNA using Lipofectamine RNAiMAX (Invitrogen) according to the manufacturer’s instructions and plated again for further experiments. The knockdown efficiency was determined using qRT-PCR or western blotting. All antibodies were purchased from commercial manufacturers, and detailed information is listed in Table S2.
The construction of the myc-tagged full-length RSPO2 expression plasmid was described previously (Wu et al., 2014). To construct RSPO2 mutants, the following amino acid sequences of RSPO2 were subcloned into the pcDNA3.1 vector: FUs, 1–146; TSP, 145–243. The TOPFlash and pRL-TK plasmids were obtained from Promega (E2241). The flag-tagged ITGAV (NM_002210.5:284–3430) and ITGB3 (NM_000212.2) expression plasmid was purchased from Miaoling Biotech (China). The myc-tagged LGR4 expression plasmid was a gift from Qiang Hou (Wenzhou Medical University, China). The primer sequences used for plasmid construction are listed in Table S3.
Female athymic nude mice were purchased from Vital River Experimental Animal Center (Beijing, China) and housed under pathogen-free conditions. All in vivo experiments and protocols were approved by the Institutional Animal Care and Use Committee of Wenzhou Medical University.
Ovarian tissue samples or microarrays containing human ovarian cancer and paired nontumor ovarian tissues were purchased from Shanghai Superbiotek Inc. (China), with appropriate Institutional Review Board approval and informed patient consent.
To obtain stable RSPO2 transfectants, transfected cells were cultured in G418-containing medium, resistant clones were pooled, and the expression of RSPO2 was confirmed by quantitative reverse transcription–PCR (qRT-PCR) and Western blotting. For the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, cells were incubated with MTT (Sangon Biotech, TB0799-1G-N) solution (final concentration, 5 mg/mL) for 5 h, and cell viability was analyzed as described previously (Wu et al., 2014). For the clonogenic assay, 1 × 10 3 cells were seeded in ṣix-well plates in triplicate. At the end of the experiment, colonies (≥50 cells) were counted after staining with 0.5% crystal violet in 20% methanol.
The Transwell migration assay was performed using Corning chambers (Corning, 3422). A total of 1 × 105 cells in 100 μL of serum-free medium were seeded in the upper compartment of the chamber, whereas 600 μL of complete medium containing 10% FBS was placed in the lower compartment of the chamber. After incubation for 24 h, the cells that migrated to the bottom surface of the membrane were fixed with methanol and stained with 0.5% crystal violet. Cells in five randomly selected fields of the membrane were counted under an inverted microscope. The Transwell invasion assay was performed following the same protocol used for the migration assay except that Corning Matrigel Invasion Chambers (Corning, 354480) were used.
The protocol for the wound healing assay was described previously (Dong et al., 2017). For the cell adhesion assay, 96-well plates were precoated with 50 μg/mL vitronectin (Sigma, 5051) overnight at 4°C. Cells were resuspended in serum-free medium, and 50,000 cells were seeded in the coated plates for 2 h at 37°C. After washing twice with PBS, adherent cells were stained with 0.5% crystal violet in 20% methanol, photographed, and solubilized in 100% ethanol. The absorbance at 540 nm was measured in a microplate reader.
Female athymic nude mice were purchased from Vital River Experimental Animal Center (Beijing, China) and housed under pathogen-free conditions. All in vivo experiments and protocols were approved by the Institutional Animal Care and Use Committee of Wenzhou Medical University. A2780 cells (3 × 106 cells suspended in 200 μL of PBS) infected with lentivirus were injected subcutaneously into nude mice Tumor volume was measured every two days with a caliper and calculated using the standard equation: V = A × B2 × 0.5326 (A = long axis and B = short axis). RSPO2-overexpressing or control A2780 or OVCAR3 cells were implanted orthotopically (1 × 106 cells suspended in 20 μL of PBS) into the left ovaries of mice for 5 weeks. At the end of the experiments, all mice were euthanized, and subcutaneous or metastatic tumors were harvested and photographed. The tumor weight, ascites weight, and number of nodules were recorded. Tumor tissues were then fixed in formalin for paraffin embedding or were snap frozen.
Protein preparation and concentration determination were performed as described previously (Dong et al., 2017). Nuclear proteins were isolated using NE-PER™ Nuclear and Cytoplasmic Extraction Reagents (Pierce, 78833) according to the manufacturer’s instructions. Proteins were separated using sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto polyvinylidene difluoride membranes (Bio-Rad, 1620177). After blocking with 5% milk in TBS containing 0.1% Tween 20 (TBST), the membranes were incubated with the corresponding primary antibodies (dilutions are listed in Table S2) followed by horseradish peroxidase (HRP)-conjugated secondary antibodies. Protein bands were visualized with an Immun-Star HRP Chemiluminescence Kit (Bio-Rad, 1705061).
Immunohistochemical staining of tissue microarrays was performed with an antibody against RSPO2 (1:200). The stained tissue microarray chips were digitally scanned, and the levels of RSPO2 were scored semiquantitatively. The immunohistochemical score was determined by multiplying the intensity score by the positive staining score of the cells. The intensity score was assigned as follows: 0 = negative staining, 1 = weak staining, 2 = moderate staining, or 3 = strong staining. The positive staining score was defined as the percentage of cells positive for RSPO2 staining. Paraffin-embedded tumor nodules were sectioned and stained with primary antibody against RSPO2 (1:200) followed by a biotinylated and peroxidase-conjugated secondary antibody. The stained slides or tissue microarray chips were visualized and imaged with a Zeiss microscope with a 10× or 40× objective lens.
Immunofluorescence analysis was performed as described previously (Wu et al., 2014). In brief, cells were seeded on coverslips for 48 h and treated with or without exogenous RSPO2 protein. After gentle washes with PBS, cells were fixed with 4% formaldehyde and permeabilized with 0.5% Triton X-100 in PBS. Cells were subsequently blocked with 2% bovine serum albumin in PBS containing 0.1% Triton X-100 prior to incubation with antibodies against the Myc tag (Cell Signaling Technology, #2278), lysosomal-associated membrane protein-1 (LAMP1; Santa Cruz Biotechnology, sc-20011), integrin β3 (Santa Cruz Biotechnology, sc-365679), integrin αv (Santa Cruz Biotechnology, sc-9969), β-catenin (Cell Signaling Technology, #9587) (diluted 1:100) and Src (Cell Signaling Technology, #2101) (diluted 1:400) at 4°C overnight. After three washes with PBST, samples were incubated with Alexa Fluor 488- or 594-conjugated secondary antibodies (diluted 1:500). Filamentous actin (F-actin) was stained with Acti-stain 488 phalloidin (diluted 1:50, Thermo Fisher Scientific, A12379). Coverslips were mounted on glass slides in the presence of DAPI for nuclear staining, and cell images were acquired with a confocal microscope via Nikon NIS-Elements software.
Cells were washed with ice-cold PBS and lysed in immunoprecipitation assay buffer (50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Triton X-100, 1 mM EDTA, and 10% glycerol) supplemented with Protease/Phosphatase Inhibitor Cocktail (Cell Signaling Technology, #5872). Lysates were incubated on ice for 20 min and centrifuged at 12,000 rpm for 20 min. Cell lysates were incubated first with the corresponding primary antibody overnight at 4°C and then with Protein G-Sepharose (GE Healthcare, 17-0618-01) for 3 h at 4°C. The beads were washed four times with immunoprecipitation assay buffer, suspended in Laemmli buffer, and boiled for 5 min. Samples were analyzed by Western blotting with the indicated antibodies.
His-tagged recombinant human RSPO2 protein (R&D System, 3266-rs-025/CF) and cell lysates from HEK293T cells overexpressing Flag-tagged Integrin αv or Integrin β3 were used for His-pulldown assays according to the instructions from a Pierce Cobalt kit (Thermo Fisher Scientific, #21277). His-tagged RSPO2 (approximately 20 μg of protein) was bound to Ni2+-NTA agarose beads. After washing with wash buffer, the agarose beads were incubated for 3 h at 4°C with 200 μg of HEK293T cell extract containing the potential interacting Flag-tagged fusion protein. After washing again, bound proteins were analyzed by Western blotting. Anti-His (Cell Signaling Technology, #12698) and anti-Flag (Cell Signaling Technology, #8146) primary antibodies were used.
The ubiquitination assay was performed as described previously (Dong et al., 2017). In brief, cells were transfected with the HA-Ubiquitin plasmid. Twenty-four hours after transfection, cells were treated with the proteasome inhibitor MG132 (25 mM) (Sigma, M7449) for 4 h and were then lysed in ubiquitination assay buffer containing protease/phosphatase inhibitors. Cell lysates were clarified and incubated with an anti-integrin αv or β3 antibody overnight at 4°C. Immunocomplexes were incubated with Protein G-Sepharose (GE Healthcare) for another 3 h at 4°C, washed four times with wash buffer, and boiled for 5 min in Laemmli buffer before separation by SDS-PAGE. Western blotting was performed with an anti-HA antibody to detect ubiquitinated integrin αv or β3.
Cells were lysed, total RNA was purified using TRIzol Reagent (Invitrogen, 15596018), and reverse transcription was performed using an M-MLV reverse transcriptase kit (Invitrogen, 28025-013). qRT-PCR was carried out with SYBR Green (Tiangen, China, FP202-02) in biological triplicate in an ABI 7500 Real-Time detection system (Applied Biosystems) according to the manufacturer’s protocol. The primer sequences are listed in Table S1. Relative quantification of mRNA expression was performed using the comparative threshold cycle (Ct) method with normalization to GAPDH. When necessary, we converted ▵▵Ct values to expression fold change values using the formula 2-▵▵Ct.
The cell cycle was analyzed by flow cytometry. In brief, a total of 5 × 105 cells were seeded in 6-well plates and cultured for 24 h. The adherent cells were collected, washed twice with PBS, fixed with ice-cold 70% ethanol, and stored at −20°C overnight. Cell pellets were centrifuged at 1000 rpm for 5 min and were then washed with cold PBS; suspended in 500 mL of PBS containing 50 mg/mL propidium iodide, 0.1 mg/mL RNase A and 0.05% Triton X-100; and incubated at 37°C for 40 min in the dark. The cell cycle distribution was analyzed in a Becton Dickinson FACSCalibur flow cytometer. The experiment was repeated three times under the same conditions.
Total RNA was isolated from vector control A2780 cells and A2780 cells stably overexpressing RSPO2 using TRIzol reagent (Invitrogen). RNA was reverse transcribed to cDNA, and cDNA was amplified and fragmented. The final products were sequenced on the Illumina HiSeq 4000 or X Ten platform (BGI-Shenzhen, China). The RNA-seq data are available under NCBI Bioproject ID: PRJNA783149. DESeq2 (http://www.bioconductor.org/packages/release/bioc/html/DESeq2.htm) was used to perform differential expression analysis. Phyper (https://en.wikipedia.org/wiki/Hypergeometric_distribution) was used to perform KEGG enrichment analysis of annotated differentially expressed genes.
Cells were transfected with TOPFlash and Renilla-TK (Promega, E2241) plasmids using Lipofectamine 2000 reagent (Invitrogen, 11668019). Forty-eight hours after transfection, the luciferase reporter assay was performed using a Dual Luciferase Reporter Assay System (Promega, E1910). Luminescence data are presented as the firefly luminescence intensity normalized to the Renilla luminescence intensity and then to the control condition.
Data are presented as the mean ± SD values. Statistical analysis was performed using GraphPad Prism 8.0 and SPSS Statistics software (SPSS 20). Kaplan–Meier survival plots were generated using R2: Genomics Analysis and Visualization Platform (http://r2.amc.nl, http://r2platform.com). Kaplan Scan (KaplanScan) was used to find the most significant expression cutoff for survival analysis based on statistical testing. The Kaplan scanner separates the samples of tumor ovarian serous cystadenocarcinoma from TCGA dataset or GSE26193 dataset into two groups (high/low) based on the mRNA expression of RSPO2. Two-tailed Student’s t test was used for comparisons between different groups. Values of p < 0.05 were considered statistically significant. Error bars represent standard error from at least three biological replicates. | true | true | true |
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PMC9547417 | Ho-min Park,Yunseol Park,Urta Berani,Eunkyu Bang,Joris Vankerschaver,Arnout Van Messem,Wesley De Neve,Hyunjin Shim | In silico optimization of RNA–protein interactions for CRISPR-Cas13-based antimicrobials | 07-10-2022 | CRISPR-based antimicrobials,RNA–protein interaction,RNA secondary structure,RNA tertiary structure,In silico docking,Drug design,Structural biology | RNA–protein interactions are crucial for diverse biological processes. In prokaryotes, RNA–protein interactions enable adaptive immunity through CRISPR-Cas systems. These defence systems utilize CRISPR RNA (crRNA) templates acquired from past infections to destroy foreign genetic elements through crRNA-mediated nuclease activities of Cas proteins. Thanks to the programmability and specificity of CRISPR-Cas systems, CRISPR-based antimicrobials have the potential to be repurposed as new types of antibiotics. Unlike traditional antibiotics, these CRISPR-based antimicrobials can be designed to target specific bacteria and minimize detrimental effects on the human microbiome during antibacterial therapy. In this study, we explore the potential of CRISPR-based antimicrobials by optimizing the RNA–protein interactions of crRNAs and Cas13 proteins. CRISPR-Cas13 systems are unique as they degrade specific foreign RNAs using the crRNA template, which leads to non-specific RNase activities and cell cycle arrest. We show that a high proportion of the Cas13 systems have no colocalized CRISPR arrays, and the lack of direct association between crRNAs and Cas proteins may result in suboptimal RNA–protein interactions in the current tools. Here, we investigate the RNA–protein interactions of the Cas13-based systems by curating the validation dataset of Cas13 protein and CRISPR repeat pairs that are experimentally validated to interact, and the candidate dataset of CRISPR repeats that reside on the same genome as the currently known Cas13 proteins. To find optimal CRISPR-Cas13 interactions, we first validate the 3-D structure prediction of crRNAs based on their experimental structures. Next, we test a number of RNA–protein interaction programs to optimize the in silico docking of crRNAs with the Cas13 proteins. From this optimized pipeline, we find a number of candidate crRNAs that have comparable or better in silico docking with the Cas13 proteins of the current tools. This study fully automatizes the in silico optimization of RNA–protein interactions as an efficient preliminary step for designing effective CRISPR-Cas13-based antimicrobials. Supplementary Information The online version contains supplementary material available at 10.1186/s13062-022-00339-5. | In silico optimization of RNA–protein interactions for CRISPR-Cas13-based antimicrobials
RNA–protein interactions are crucial for diverse biological processes. In prokaryotes, RNA–protein interactions enable adaptive immunity through CRISPR-Cas systems. These defence systems utilize CRISPR RNA (crRNA) templates acquired from past infections to destroy foreign genetic elements through crRNA-mediated nuclease activities of Cas proteins. Thanks to the programmability and specificity of CRISPR-Cas systems, CRISPR-based antimicrobials have the potential to be repurposed as new types of antibiotics. Unlike traditional antibiotics, these CRISPR-based antimicrobials can be designed to target specific bacteria and minimize detrimental effects on the human microbiome during antibacterial therapy. In this study, we explore the potential of CRISPR-based antimicrobials by optimizing the RNA–protein interactions of crRNAs and Cas13 proteins. CRISPR-Cas13 systems are unique as they degrade specific foreign RNAs using the crRNA template, which leads to non-specific RNase activities and cell cycle arrest. We show that a high proportion of the Cas13 systems have no colocalized CRISPR arrays, and the lack of direct association between crRNAs and Cas proteins may result in suboptimal RNA–protein interactions in the current tools. Here, we investigate the RNA–protein interactions of the Cas13-based systems by curating the validation dataset of Cas13 protein and CRISPR repeat pairs that are experimentally validated to interact, and the candidate dataset of CRISPR repeats that reside on the same genome as the currently known Cas13 proteins. To find optimal CRISPR-Cas13 interactions, we first validate the 3-D structure prediction of crRNAs based on their experimental structures. Next, we test a number of RNA–protein interaction programs to optimize the in silico docking of crRNAs with the Cas13 proteins. From this optimized pipeline, we find a number of candidate crRNAs that have comparable or better in silico docking with the Cas13 proteins of the current tools. This study fully automatizes the in silico optimization of RNA–protein interactions as an efficient preliminary step for designing effective CRISPR-Cas13-based antimicrobials.
The online version contains supplementary material available at 10.1186/s13062-022-00339-5.
The central dogma of molecular biology attributes the main role of RNA as the intermediate messenger between DNA and protein [1]. Recent studies reveal that RNA is involved in diverse cellular processes such as regulatory activities of gene expression, catalytic activities of various substrates, and molecular chaperoning and scaffolding [2]. The ability of RNAs to interact with RNA-binding proteins (RBPs), which rely on both RNA sequence and structure, has been studied in a number of RNA–protein complexes, including ribosomal RNA complexes [3]. In prokaryotes, RNA–protein interactions play a vital role in the highly intricate process of adaptive immunity against foreign genetic elements through Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated system (Cas) proteins [4, 5]. Prokaryotic genomes with CRISPR-Cas systems have the ability to store sequence information of previous infections in their CRISPR arrays. A complex of Cas proteins uses this sequence information as a genetic template to find and neutralize invaders of the same sequence. To achieve such specificity, the interaction between a complex of Cas proteins with nuclease activities and a CRISPR RNA (crRNA) with the protein-binding component (CRISPR repeat) is essential for this RNA-mediated adaptive immunity. The redesign of the protein-binding component of crRNAs associated with the Cas9 protein (trans-activating RNA) led to an efficient genome-editing tool in diverse eukaryotic cells [6–8]. Thanks to the interest in genome-editing applications, there was an active discovery of new CRISPR-Cas systems based on Cas proteins, which revealed the immense diversity of CRISPR-Cas systems in nature [9–11]. Recently, CRISPR-Cas systems are being repurposed as antibiotic tools against multidrug-resistant bacteria due to their programmability and specificity [12–15]. The uncontrolled spread of antimicrobial resistance (AMR) against traditional antibiotics of small molecules has become a global health issue [16], and we are in urgent need of novel antibiotics to combat multidrug-resistant bacteria. Some novel strategies are bacteriophage-derived, such as phage therapy that has been used successfully to treat multidrug-resistant infections as breakthrough therapy [17–19]. Several phage-derived endolysins are in clinical development for their antimicrobial activities to lyse the peptidoglycan layer of Gram-positive bacteria [20, 21]. Another promising strategy is to use bacterial defence systems such as CRISPR-Cas systems against themselves by reprogramming CRISPR templates to target AMR genes in the chromosome or on plasmids [12, 13, 22]. For this purpose, Cas9 proteins have been explored extensively, but the double-stranded breaks in DNA resulting from their nuclease activities leave the blunt-ends susceptible to DNA repair pathways in bacteria [23, 24]. Recently, Class 2 CRISPR-Cas systems of type VI are being investigated as promising antimicrobial tools, whose activity is characterized by RNA-guided single-stranded RNA (ssRNA) cleavage [25, 26]. These systems encompass a single-effector Cas13 protein consisting of two Higher Eukaryotes and Prokaryotes Nucleotide-binding (HEPN) domains with ribonuclease activity (Fig. 1). Cas13 proteins bind and cleave specific RNAs, which sequentially activate nonspecific RNase activities by changing their structural conformation [26, 27]. Such promiscuous RNA cleavage is effective in restricting bacteria growth by degrading bacterial transcript RNAs. As the effects of CRISPR-Cas13 systems cannot be repaired like those of CRISPR-Cas9 systems in prokaryotes, they are one of the most promising antimicrobial tools to resensitize and neutralize multidrug-resistant bacteria. A recent experimental study demonstrated that CRISPR-Cas13a systems could be designed to trigger such activities in a sequence-specific manner that led to successful bacteria growth arrest [28]. Currently, CRISPR-Cas13 systems are divided into five subtypes (VI-A, VI-B1, VI-B2, VI-C, VI-D), depending on the Cas13 protein and its accessory proteins. However, the architecture of CRISPR-Cas13 systems is highly variable [11]. In this study, we observe that many CRISPR-Cas13 systems have no adjacent CRISPR arrays, particularly the Cas13a systems. This genomic architecture implies that CRISPR-Cas13 systems often share CRISPR arrays with other CRISPR-Cas systems in the genome, and some structural studies used synthetic constructs due to the lack of clear association between the Cas13 protein and the crRNA [29]. For effective CRISPR-based antimicrobials, RNA–protein interactions between crRNAs and Cas proteins should be optimal. Previously, it was shown that some off-target effects of genome-editing tools in cells occur when there is a competition between several crRNAs to bind the Cas protein [30]. As CRISPR-based antimicrobials have to operate in bacterial cells which often have several CRISPR arrays, it is imperative that these antibiotic tools have the optimal affinity between the target crRNA and the Cas13 protein to prevent competition with endogenous crRNAs. Here, we optimize RNA–protein interactions by curating crRNA datasets from CRISPR-Cas13 genomes and predicting 3-D crRNA structures for in silico docking with the Cas13 protein (Fig. 2). First, we compare the accuracy performance of several RNA secondary and tertiary structure prediction programs using the experimental data of crRNA and Cas13 structures. Next, we validate in silico docking of crRNAs on the Cas13 protein of interest using the experimental structures and the predicted structures of crRNAs. This comparison study optimizes the computational pipeline required for in silico docking experiments to assess RNA–protein interactions. Finally, we conduct in silico docking of candidate crRNAs on the Cas13 protein of interest to compare with the experimental data of the crRNA-Cas13 complexes. This candidate study contributes to the investigation of effective CRISPR-based antimicrobials by generating a list of candidate crRNAs that dock optimally with the Cas13 proteins. Furthermore, we aim to provide an optimized and automatized computational pipeline for in silico docking experiments to model the receptor-ligand binding of experimental or predicted structures. Such in silico studies offer an efficient preliminary step to scan for candidate crRNAs predicted to bind optimally with the Cas13 proteins to be validated and optimized further with in vitro and in vivo studies.
From the literature search, we found eight RNA 2-D structure prediction programs that were available and maintained for performance comparison (Additional file 1: Table S1). As RNA 2-D structures are an intermediate step, no macromolecular structures are available to be directly compared with. Thus, the predicted RNA 2-D structures were first compared between different prediction programs in this section, after which the RNA 3-D structures resulting from this intermediate step were compared with experimental RNA 3-D structures in the next section (see “Results” below). The predicted 2-D structures of the crRNAs in the validation dataset were summarized in Additional file 1: Table S2. None of the crRNAs were predicted to have the same 2-D structure by all eight prediction programs. For most cases, the number of different 2-D structures predicted per CRISPR repeat sequence was between three different structures (5WLH, 6VRB, 6IV8_B, 6IV8_D, 6IV9) and four different structures (5W1H, 5W1I_B, 5W1I_D, 7OS0_D, 7OS0_I, 6DTD, 6E9E). Some crRNAs had more variability in the predicted 2-D structures. For the crRNA of 6AAY, only CentroidFold and CONTRAfold predicted the same RNA 2-D structure. RNAfold and MXfold2 also formed a separate group, as well as RNAstructure and RNAshapes. IPknot and ContextFold each predicted a unique 2-D structure that was different from all the other predictions. Consequently, five different 2-D structures were predicted for this crRNA. For the other crRNAs, the predicted 2-D structures had less variability. For the crRNAs of 5WTK, 5XWY and 6VRC, all the programs predicted the same 2-D structure for each CRISPR repeat sequence except ContextFold. In overall, ContextFold and CONTRAfold mostly predicted 2-D structures that were more complex with a higher number of paired bases than the rest of the programs. RNAfold, RNAstructure, MXfold2 and RNAshapes predicted the same 2-D structure in most cases. However, there were no consistent patterns to how the eight programs predicted the crRNAs; thus, it is important to evaluate the 2-D structure prediction from multiple programs when predicting the structure of an RNA sequence.
To evaluate the accuracy of RNA 2-D structure prediction, we fixed the RNA 3-D structure prediction program constant and compared the predicted 3-D structures in combination with the different RNA 2-D structure programs against the experimental RNA 3-D structures (Additional file 1: Tables S3–S4). The predicted crRNA 3-D structures from RNAComposer and Rosetta were superimposed with the corresponding experimental 3-D structure (referred to as ‘ground truth’ or ‘GT’) using the evaluation programs (PyMOL align, PyMOL super and SETTER) to obtain the RMSD values (see Tables 1, Additional file 1: S5–S8). For each superimposition of two 3-D structures, the mean and the SD from the three replicate runs were calculated. For SETTER, the RMSD values varied while those of PyMOL align and PyMOL super stayed constant. The RMSD values across all the crRNAs are visualized as a heatmap for each evaluation program (Figs. 3, Additional file 1: S1–S4). The lower the RMSD value, the smaller the average distance between the atoms of the superimposed structures, and the darker the colour in the heatmap. We observed that there is a correlation between the accuracy of RNA structure prediction with the quality of the experimental resolution. For example, the crRNA of 6E9E with the lowest experimental resolution of 3.4 Å was predicted poorly by all combinations of the RNA structure software (Fig. 3). For RNAComposer, the evaluation programs of the superimposition between the predicted 3-D structures and the GT structures varied vastly according to the 2-D structure prediction program used in combination. With the evaluation program of PyMOL align, CONTRAfold gave the lowest RMSD value on average (Table 1), while CentroidFold and IPknot mostly showed lighter shades in the heatmap rows (Fig. 3). Interestingly, ContextFold gave both the highest RMSD value and the lowest RMSD value (6AAY and 6IV8_B, respectively). Regarding the performance consistency, ContextFold had the highest SD value. In this setting, MXfold2 had the lowest SD value and the second lowest average RMSD value (Table 1). For Rosetta, the performance of the 3-D structure prediction program also varied vastly according to the 2-D structure prediction program used in combination. With the evaluation program of PyMOL align, IPknot gave the lowest RMSD value on average (Table 1), while ContextFold and RNAstructure mostly showed lighter shades in the heatmap rows (Fig. 3). Interestingly, RNAstructure both gave the highest RMSD value and the lowest RMSD value (6IV8_B and 6DTD, respectively). Regarding the performance consistency, RNAstructure had the highest SD value. In this setting, IPknot had the lowest SD value and also the lowest average RMSD value (Table 1).
The in silico docking experiments of the validation dataset using HADDOCK showed low performance when the docked model was compared to the GT structure with the CAPRI docking scores (Additional file 1: Figure S5). PyDockDNA showed better performance by correctly docking one receptor-ligand pair for every 3–5 pairs. Surprisingly, HDOCK was able to dock all the pairs with high accuracy, regardless of the random rotations. In terms of the iRMSD values, HADDOCK, PyDockDNA and HDOCK achieved on average 28.05, 12.73, and 0.11, with the standard deviations of 5.03, 7.30, and 0.05, respectively, across all the crRNAs in the validation dataset. From the validation study, HDOCK was found to be the best performing in silico docking software for the Cas13 proteins and crRNAs. Due to the exceptional performance, further in silico docking experiments were conducted only with HDOCK. Next, we used the predicted 3-D structures of the crRNAs in the validation dataset to perform in silico docking with the Cas13a proteins and Cas13b/d proteins (Additional file 1: Figures S6 and S7, respectively). Subsequently, the accuracy of the docked model using the predicted crRNA structures was analysed using the CAPRI docking scores (Additional file 1: Table S9). For all the crRNAs, the docking scores of iRMSD were above the acceptable threshold (4 Å) when the RNA 3-D structures were predicted with different combinations of the 2-D and 3-D structure prediction programs (Additional file 1: Figures S6-S7). This result was surprising as the previous in silico docking experiments using the GT crRNA structures had resulted in the near-perfect docking score of iRMS (~ 0 Å). However, four crRNAs (5WLH, 5W1H, 5W1I_AB, and 5W1I_CD) gave better docking scores than the others, and it was notable that these crRNAs also had better experimental metrics (Additional file 1: Table S10). As the quality of the GT crRNA structures depended on the experimental condition, we decided to only keep these four crRNAs with the best experimental metrics in further studies [49]. Another adjustment was to consider the 10 best models generated from the in silico docking experiments rather than retaining the best model only. Additionally, the CRISPR repeat sequences for these crRNAs were shortened to match the visible part of the GT structures before predicting the 3-D structures. In the subsequent experiments, some of the docking scores reached an acceptable threshold in terms of the iRMSD scores (Table 2). From visualization by superimposing with the GT structure, the best model selected by the minimal docking score and the human experts were compared. As shown in Fig. 4, the best model from the in silico experiments between these two methods coincided, except for 5W1H. Furthermore, the best model of the crRNA associated with 5WLH superimposed almost perfectly with the GT structure. Finally, we performed the in silico docking experiments with both template-free and template-based settings, which resulted in no significant improvement in the docking performance when the template-based setting was used (Figs. 4, Additional file 1: S8–S9). Thus, all the subsequent in silico docking experiments with the candidate dataset with HDOCK were conducted template-free.
The predicted 3-D structures of the candidate crRNAs from the software combinations with consistent performance were docked in silico with the corresponding Cas13 protein using the optimized pipeline. As the 10 best models were retained for each docking experiment, there were many docked models to be evaluated by the human experts in the absence of the GT structures. Thus, we first summarized each docking result as the centre of mass in the spatial coordinates calculated from all atoms of the docked macromolecular structure model (Fig. 5). This step enabled a visual summary of the in silico docking experiments, and calculation of the closest clusters or individuals to the GT crRNA in the spatial coordinates. As the coordinates of the Cas13 protein remained constant, the docked models of each candidate crRNAs near the GT crRNA had the potential to interact optimally with the binding domains. For example, the N-terminal domain (NTD) and the Helical-1 domain were previously found to form the crRNA-recognition (REC) lobe of Cas13a [49], and we only considered the candidate crRNAs which docked near these domains by selecting the closest clusters or individuals to the GT crRNA. We ranked the best candidate crRNAs for each Cas13 protein from the candidate dataset by calculating the Euclidean distance of each docked model to the GT, which determined the best cluster of the candidate crRNAs (containing 10–50 docked models for each Cas13) and the best individual candidate crRNAs (containing 10–50 docked models for each Cas13). The average distance between each GT crRNA and the closest cluster was 17.15 ± 7.09 Å, and the average distance between each GT crRNA and the closest individual candidate crRNAs was 16.69 ± 5.26 Å. Using a two-sided Student's t test, we found that the difference between the average individual and the average cluster distances was not significant (p = 0.54, Additional file 1: Table S11). The docking results of the selected candidate crRNAs were further evaluated through visual inspection by the human experts (Additional file 1: Figures S10–12). From the visualization analysis, the docking results of the best individual crRNAs were found to show better docking than those of the best cluster crRNAs, in terms of both position and direction. Among the 321 docked pairs of the closest clusters, only 8 of them received the best docking score from the human experts, while 77 from the 370 closest individuals received the best docking score (Additional file 1: Table S12–S14). It is notable that not all candidate crRNAs with the best docking result came from the best model generated by the in silico docking software. For example, the 8th best model of the candidate crRNA of CP002345_2_11 was evaluated to dock very well with the corresponding Cas protein of 5WTK (Table 3). This result shows the importance of retaining at least the 10 best models from the in silico docking experiments to be analysed further by the human experts, to ensure that the best docking model of the ligand reflects the biological information on the receptor. RNA–protein binding affinities between the crRNA and the Cas protein of the experimental GT complexes and the predicted complexes are shown in Table 3. The Gibbs free energy (ΔG) in RNA–protein binding affinity varies between − 11.68 kcal/mol and − 14.06 kcal/mol for the experimental GT complexes, which is within the range of RNA–protein binding affinities seen in other types of single-stranded RNAs. The RNA–protein binding affinity values of the predicted docking models of the crRNA-Cas complexes also fall within the range of − 13 kcal/mol and − 15 kcal/mol. Notably, some predicted docking models had stronger binding affinity values than the experimental GT complex. For example, one of the candidate crRNAs from Rosetta (CP002345_2_6_1) had a binding affinity of − 15.16 kcal/mol with the Cas protein 5W1H, compared to − 14.06 kcal/mol of the experimental GT complex. This candidate crRNA also received the highest docking evaluation score from the human experts. The multiple sequence alignment (MSA) results showed that some candidate crRNAs in the closest individuals to the GT crRNA had very different sequences when compared to the sequence of the GT crRNA (Fig. 5). When these crRNAs were visualized, they had the in silico docking models as optimal as the GT crRNA without necessarily having similar sequences. For example, the crRNA of CP018618_1_1 fits perfectly into the docking region of 5W1H, but its sequence has almost no similarity to the sequence of the GT crRNA. Therefore, a selected list of candidate crRNAs is provided as novel CRISPR repeats that have the potential to interact as optimally as the GT crRNAs for each Cas13 protein. These candidate crRNAs have been assessed through in silico docking experiments worthwhile to be further validated through in vitro or in vivo experiments (Table 3).
Conducting in silico experiments that accurately predict the results of laborious and expensive laboratory experiments is a long-standing goal of many computational biologists. The recent advances in computational methods such as machine learning in 3-D protein structure prediction [19, 50] and in genomics [51, 52] bring the possibility of achieving such challenging tasks closer to reality. In this study, a series of in silico docking experiments were conducted to model the RNA–protein interactions between a Cas protein and a CRISPR repeat. We predicted the RNA 3-D structures of these CRISPR repeats to perform in silico docking with the corresponding Cas13 protein, with the first goal of optimizing the in silico docking pipeline and the second goal of generating a list of potential CRISPR repeats that may interact optimally with the Cas13-based antimicrobial tools. The first part of the study used the validation dataset of the crRNA-Cas complexes with the experimentally validated structures to optimize the computational pipeline of in silico docking, given a CRISPR repeat sequence and a Cas protein structure as the input data. This optimization followed the iterative process of selecting the best combination of the 2-D and 3-D structure prediction programs through evaluating the predicted RNA structure against the GT RNA structure. Subsequently, the GT structures of the crRNA-Cas complexes were utilized to select the best in silico docking software with Cas proteins as the receptor and crRNAs as the ligand. This optimized pipeline was further tested using the predicted 3-D structures of crRNAs to assess the impact of structure prediction on the performance of in silico docking, as compared to the GT crRNA 3-D structures. We quantified the impact of inaccuracy arising from the two-step process of the 2-D and 3-D structure prediction, and optimized the subsequent in silico docking experiments. For this optimization, we achieved satisfactory results according to the evaluation metrics utilized in the CAPRI community-wide experiment that aims at modelling interactions based on the 3-D structure of macromolecules [53]. The second part of this study aimed at finding candidate crRNAs that are predicted to have better or equivalent interactions with the Cas13 proteins as the original crRNAs in the validation dataset. This candidate dataset was generated by curating a set of CRISPR repeat sequences that are colocalized with the Cas13 system, as the previous studies demonstrated that the proximal colocalization of CRISPR arrays is an indication of association to the Cas system [54]. Using the previously optimized pipeline, we conducted in silico docking experiments by first predicting the 3-D structure of these candidate crRNAs, which were subsequently docked with the corresponding Cas13 protein. The in silico docking experiments were evaluated by comparing the spatial coordinates of the docked RNA models with those of the GT crRNA, relative to the corresponding Cas13 protein. This evaluation step enabled the best docked model to be selected efficiently by ranking hundreds of docked models in terms of the closest Euclidean distance to the GT crRNA, thus to the crRNA-recognition domains of the Cas13 protein. The final step of the candidate study was the intervention of human expertise by visualizing these docked models to evaluate the receptor-ligand binding as compared to the interaction of the GT crRNA-protein complexes. Remarkably, we found a number of candidate crRNAs that showed in silico docking comparable to the GT crRNA-protein complexes, despite the dissimilarity in genetic sequence. Furthermore, some of these candidate crRNAs were predicted to have RNA–protein binding affinity stronger than the experimental GT crRNA-protein complexes. Given that the 3-D structures of these candidate crRNAs were predicted, this result indicates the potential of these RNA–protein interactions to be more stable than those of the GT crRNA-protein complexes.
The in silico docking experiments with the predicted crRNA structures and the associated Cas13 proteins conducted in this study are significant for the following reasons. With the increasing availability of metagenomic sequencing, CRISPR-Cas systems in nature are discovered to be more diverse, complex and disordered than previously expected, and the associations between CRISPR arrays and Cas proteins are enigmatic in some prokaryotic genomes. Particularly, the recently discovered Cas13 systems that degrade RNAs are found to be different architecture-wise from the previous CRISPR-Cas systems, as indicated by the absence of CRISPR arrays and cas1/cas2 genes in vicinity [26, 27]. However, the exact mechanism of how Cas13-based systems can function without the adaptation module and colocalized CRISPR arrays is still an ongoing investigation. Given that the Cas13-based systems have been proposed as alternative antimicrobial tools, it is imperative to investigate the characteristics of these novel CRISPR-Cas systems. This preliminary study is an important step towards designing more effective CRISPR-Cas13-based antimicrobial tools, which may be susceptible to off-targeting events in the presence of crRNAs with higher binding affinity. This problem is even more evident in pathogenic bacteria whose genomes are known to contain several endogenous CRISPR-Cas systems [23]. As future prospects, the selected candidate crRNAs in this study should be tested with experimental methods such as structure reactivity of crRNAs and X-ray crystallography or electron microscopy of candidate crRNA-Cas13 complexes to validate the outcome of these in silico docking experiments. This experimental validation will elucidate the potential off-target effects of the CRISPR-Cas13-based antimicrobial tools, which would be an important step towards optimizing the crRNA-Cas13 complex to be stable and effective in targeting multidrug-resistant bacteria within the complex environment of human microbiota. Finally, this study reveals a number of aspects of in silico docking that could be improved with further investigations to incorporate recent computational and biological advances. We suggest that predicting receptor-ligand interactions is another biological field where deep-learning applications may become extremely valuable.
Two distinct components are necessary for a functional CRISPR-Cas system: a CRISPR array and a cluster of cas genes arranged in one or more operons (Fig. 1). The CRISPR array consists of almost identical and mostly palindromic repeats, which are separated by unique spacers that contain foreign DNA from past infections. The cas genes are divided into four functional modules: the adaptation module of spacer acquisition, the expression module of pre-crRNA processing, the interference module of target recognition, binding and cleavage, and the signal transduction module of CRISPR-linked accessory genes. Currently, CRISPR-Cas systems are assigned to a class and type based on the composition of functional modules. In Class 1 (types I, III and IV), the effector module (part of the interference module) consists of multiple Cas proteins, whereas in Class 2 (types II, V and VI), a single and large Cas protein is responsible for the effector module [11]. CRISPR-Cas13 systems belong to Class 2 and type VI with several subtypes of effector proteins, including Cas13a, Cas13b, and Cas13d [26]. The Cas13 effector proteins contain two higher eukaryotes and prokaryotes nucleotide-binding (HEPN) domains that confer RNase activity (Fig. 1). The Cas13 protein complexes with the crRNA via the CRISPR repeat sequence of ~ 30 nucleotides, and the CRISPR spacer encodes a sequence that is complementary to the target sequence. In Class 2, CRISPR-Cas systems mostly involve Cas1, Cas2 and Cas4 for adaptation, but the Cas13b subtype lacks the adaptation module (Fig. 1). Interestingly, the Cas13 family often has no colocalized CRISPR arrays within ± 10,000 base pairs (Additional file 1: Table S15). Compared to the Cas9 family with a high occurrence of colocalized CRISPR arrays (80%), the Cas13 family has lower occurrences of colocalized CRISPR arrays, particularly the subtypes Cas13a (19%) and Cas13d (0%).
To conduct in silico docking experiments, the first step was to curate a validation dataset of Cas13 proteins and associated CRISPR repeats that could be used for performance evaluation (Fig. 2). An experimental dataset of the Cas13 family was retrieved from the Protein Data Bank (PDB), whose 3-D structure has been resolved by experimental techniques such as X-ray crystallography, NMR spectroscopy, or cryo-electron microscopy (Additional file 1: Table S2). The repeat sequences of the crRNAs in the CRISPR-Cas complex were retrieved from the PDB in the FASTA format (Additional file 1: Table S16). The CRISPR repeat sequences of all Cas13a-associated complexes were later shortened to match the visible part in the PDB, as their 3-D structures were only partially modelled. Some CRISPR-Cas13 systems contained multimeric proteins, and the crRNA chains (5W1I, 7OS0, 6IV8) were considered separately for the validation studies. Another dataset of candidate CRISPR repeats was curated to identify crRNAs that interact optimally with the Cas13 proteins. As shown previously, the Cas13 family often has no colocalized CRISPR arrays, which makes the association between the Cas13 proteins and the crRNAs difficult to determine (Additional file 1: Figure S13). Thus, this candidate dataset is a collection of CRISPR repeat sequences from the CRISPR arrays that are within ± 10,000 base pairs of the Cas13 proteins by querying the prokaryotic genomes from the CRISPRCasdb [31]. As these crRNAs have no experimental structures, the first step to in silico docking experiments is to predict the RNA structures of these candidate crRNAs.
As the RNA 2-D structure prediction precedes the 3-D structure prediction, the 3-D structure prediction programs base their prediction on the 2-D structure (Additional file 1: Figure S14). With a selection of eight RNA 2-D structure prediction programs and two RNA 3-D structure prediction programs, 16 different combinations, including both machine learning-based and model-based methods, were evaluated using the validation dataset (Additional file 1: Table S4). The 2-D structure of each CRISPR repeat sequence was predicted as the dot-bracket notation through the web servers of all the RNA 2-D structure prediction programs with the default parameters (Additional file 1: Table S1). RNAComposer receives genetic sequence and 2-D structure as input to predict the 3-D structure of an RNA molecule. If only the genetic sequence is given as an input, RNAComposer creates the 2-D structure itself through the built-in algorithm [32, 33]. For Rosetta, the fragment assembly of RNA with full-atom refinement (FARFAR2) protocol was applied followingly [34]. The CRISPR repeat sequences of the validation dataset and the dot-bracket notation of the predicted 2-D structure were given as an input. Subsequently, the predicted RNA 3-D models were subjected to minimization in an all-atom scoring function used by the FARFAR2 protocol. The FARFAR2 protocol selected the best model in terms of minimum free energy (MFE) and root-mean-square deviation (RMSD) from the ensemble of predicted 3-D structure models. First, the models were sorted by total energy, and the top 500 models were selected. Then, these top 500 models were sorted by the RMSD value to extract the best 3-D model based on the RMSD and MFE values. The final output of the validation dataset resulted in 256 predicted crRNA 3-D structures in PDB files, given 16 crRNA sequences and 16 different RNA programs.
To assess the performance of each program combination, the predicted 3-D structures of the crRNAs in the validation dataset were compared with the experimental 3-D structures. The RMSD measuring the average distance between the atoms of superimposed structures was used as the performance metric. The RMSD values were obtained using three different evaluation programs: the PyMOL align function, the PyMOL super function and the secondary structure-based tertiary structure similarity algorithm (SETTER) [35, 36]. The PyMOL align function superimposes 3-D structures based on sequence, while the PyMOL super function and the SETTER superimpose 3-D structures based on structure. Each of the 256 predicted 3-D structures was superimposed with the corresponding GT structure, and this performance analysis was conducted with three replicates to account for the stochasticity of each evaluation program. The mean and standard deviation (SD) of the RMSD values across all predicted structures and all replicate runs were calculated as summary statistics. By keeping the RNA 3-D structure prediction program constant and changing the 2-D program, the prediction accuracy of each combination could be assessed. The best-performing combination with the lowest mean RMSD and SD value was chosen for further in silico docking experiments with the candidate dataset.
The validation dataset contained three subtypes of Cas13: Cas13a, Cas13b, and Cas13d. These experimentally validated structures from the PDB contained CRISPR-Cas complexes with both the Cas protein and crRNA. The PDB files of the validation dataset were first cleaned to remove all unwanted residues such as water and magnesium molecules in PyMOL. For the PDB files containing dimeric Cas proteins and two crRNAs (5W1I, 6IV8, 7OS0), the two chains and RNAs were separated and named with their chain ID (5W1I_AB, 5W1I_CD; 6IV8_AB, 6IV8_CD; 7OS0_AF, 7OS0_CD). Each of the cleaned PDB files were separated into the receptor (Cas protein) and ligand (crRNA). Next, the receptor and ligand pairs were randomly rotated to ensure that the docking is not influenced by their initial coordinates. For example, PyDockDNA without random rotation led to perfect docking of the ligand and the receptor. Each receptor and ligand pair was rotated separately in 3-D around the centre of mass using random angles between 40° and 320°, to ensure sufficient rotation from the initial coordinates. Three different angles were chosen for the Cas proteins and for each crRNA. To optimize in silico docking using the validation dataset, five in silico docking programs were considered: HADDOCK [37, 38], HDOCK [39], PyDockDNA [40], RNP-denovo [41], and Swarmdock [42]. However, two of these were eliminated in the preliminary steps due to software incompatibility and thus, only three programs (HADDOCK, HDOCK, and PyDockDNA) were considered for the in silico docking validation study (Additional file 1: Table S17). We automatized the use of the web servers for in silico docking experiments. HADDOCK was run with the parameters recommended for RNA–protein docking. Some experimental structures with intrinsically disordered proteins were processed prior to using HADDOCK, as the dynamic conformations of the proteins intervened with in silico docking [43]. All other parameters were kept as default, except for the parameter defining randomly ambiguous interaction restraints from accessible residues, which allows docking without specifying the binding sites. PyDockDNA was run with the default parameters and the PyDock scoring function was used. HDOCK was run with the template-free option, and all other parameters were kept as default. For evaluation of the results, only the best docking model, as given by the internal docking score based on a relative ranking of different binding models for the receptor-ligand pair, was considered in the validation study. In the following steps of the validation study, the predicted crRNA structures were used as ligands. These RNA 3-D structures were predicted with the shortened sequences containing only the CRISPR repeat. The RNA 3-D structures were generated from all combinations of the 2-D and 3-D structure prediction programs (Additional file 1: Table S4). The subsequent in silico docking of the receptor (Cas13a proteins) and the ligand (predicted crRNA structures) was conducted template-free and template-based runs of HDOCK. We used the interface RMSD (iRMSD) to assess the performance of each in silico docking experiment, which is one of the docking scores used in Critical Assessment of PRediction of Interactions (CAPRI) experiments [44, 45] that calculates the docking distance overlap between the GT ligand and the model ligand at the interface of all atoms within a distance of 8 Å from the point where the receptor and ligand meet (see Additional file 1: Figure S15 for details). The CAPRI-based performance calculation was adapted for RNA–protein interactions by retaining alpha carbon (Cα) and phosphate as the backbone of the protein receptor and the RNA ligand, respectively [46]. Finally, we used DockQ [47] for calculating iRMSD values by setting the backbone atom as Cα and phosphate.
The candidate crRNAs structures of Cas13a, Cas13b, and Cas13d were predicted with the two combinations of 2-D structure prediction and 3-D structure prediction programs (MXfold2 with Rosetta or RNAComposer). Subsequently, the candidate crRNA structures were docked in silico with the corresponding Cas13 protein using HDOCK, which showed the best performance in the validation study. The template-free parameter was used and the 10 best models were retained from the in silico experiments for evaluation. Since the candidate dataset has no experimentally validated structures, the in silico docking experiments of the candidate crRNA structures were evaluated by comparing with the GT crRNA-Cas13 structures as well as by visual analysis of the human experts. First, we applied K-means clustering of the 10 best models obtained from the in silico docking experiments of each candidate crRNA structure [48]. We used the centre of mass of each crRNA as a representative position of the crRNA in the 3-D space. The Euclidean distance of each candidate crRNA model to the GT crRNA model was calculated, and the number of clusters was determined in proportion to the number of candidate crRNAs for each Cas13 protein, which was 20, 80, and 10 for Cas13a, Cas13b, and Cas13d, respectively. From the distance calculations, the closest cluster to the GT crRNA was found for each Cas13 protein, and multiple sequence alignments (MSAs) were performed on the closest cluster for each docking result. Next, the individual candidate crRNAs with the closest docking position to the GT crRNA were found, with the number of individuals also determined proportionally to the size of the candidate dataset for each protein. Followingly, the human experts used the 3-D visualization to validate the candidate crRNA docking results in comparison to the GT results. We calculated the RNA–protein binding affinity for the experiment GT complexes and the candidate crRNA docking models with PredPRBA, which predicts RNA–protein binding affinity using gradient boosted regression trees trained on the experimental RNA–protein binding affinity dataset [55]. We modified the PDB format of the candidate crRNA docking models by adding 1 as the occupancy and 50 as the B-factor, as these missing values of the docking program are necessary for the binding affinity program to run despite having no effect on the outcome of the calculation. For the RNA–protein complex category, we selected the single-stranded RNA category for crRNAs. The method was previously shown to perform the best with this category due to the largest size of the training dataset.
Additional file 1. Supplementary Figures S1–S15 and Supplementary Tables S1–S17. | true | true | true |
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PMC9547585 | Wei Zhao,Jianguo Cheng,Yan Luo,Wenlong Fu,Lei Zhou,Xiang Wang,Yin Wang,Zexiao Yang,Xueping Yao,Meishen Ren,Zhijun Zhong,Xi Wu,Ziwei Ren,Yimeng Li | MicroRNA let-7f-5p regulates PI3K/AKT/COX2 signaling pathway in bacteria-induced pulmonary fibrosis via targeting of PIK3CA in forest musk deer | 05-10-2022 | Bacteria-induced pulmonary fibrosis,Forest musk deer,Let-7f-5p,PIK3CA gene,PI3K/AKT/COX2 signaling pathway | Background Recent studies have characterized that microRNA (miRNA) is a suitable candidate for the study of bleomycin/LPS-induced pulmonary fibrosis, but the knowledge on miRNA in bacteria-induced pulmonary fibrosis (BIPF) is limited. Forest musk deer (Moschus berezovskii, FMD) is an important endangered species that has been seriously affected by BIPF. We sought to determine whether miRNA exist that modulates the pathogenesis of BIPF in FMD. Methods High-throughput sequencing and RT-qPCR were used to determine the differentially expressed miRNAs (DEmiRNAs) in the blood of BIPF FMD. The DEmiRNAs were further detected in the blood and lung of BIPF model rat by RT-qPCR, and the targeting relationship between candidate miRNA and its potential target gene was verified by dual-luciferase reporter activity assay. Furthermore, the function of the candidate miRNA was verified in the FMD lung fibroblast cells (FMD-C1). Results Here we found that five dead FMD were suffered from BIPF, and six circulating miRNAs (miR-30g, let-7f-5p, miR-27-3p, miR-25-3p, miR-9-5p and miR-652) were differentially expressed in the blood of the BIPF FMD. Of these, let-7f-5p showed reproducibly lower level in the blood and lung of the BIPF model rat, and the expression levels of PI3K/AKT/COX2 signaling pathway genes (PIK3CA, PDK1, Akt1, IKBKA, NF-κB1 and COX2) were increased in the lung of BIPF model rats, suggesting that there is a potential correlation between BIPF and the PI3K/AKT/COX2 signaling pathway. Notably, using bioinformatic prediction and experimental verification, we demonstrated that let-7f-5p is conserved across mammals, and the seed sequence of let-7f-5p displays perfect complementarity with the 3’ UTR of PIK3CA gene and the expression of the PIK3CA gene was regulated by let-7f-5p. In order to determine the regulatory relationship between let-7f-5p and the PI3K/AKT/COX2 signaling pathway in FMD, we successfully cultured FMD-C1, and found that let-7f-5p could act as a negative regulator for the PI3K/Akt/COX2 signaling pathway in FMD-C1. Collectively, this study not only provided a study strategy for non-invasive research in pulmonary disease in rare animals, but also laid a foundation for further research in BIPF. | MicroRNA let-7f-5p regulates PI3K/AKT/COX2 signaling pathway in bacteria-induced pulmonary fibrosis via targeting of PIK3CA in forest musk deer
Recent studies have characterized that microRNA (miRNA) is a suitable candidate for the study of bleomycin/LPS-induced pulmonary fibrosis, but the knowledge on miRNA in bacteria-induced pulmonary fibrosis (BIPF) is limited. Forest musk deer (Moschus berezovskii, FMD) is an important endangered species that has been seriously affected by BIPF. We sought to determine whether miRNA exist that modulates the pathogenesis of BIPF in FMD.
High-throughput sequencing and RT-qPCR were used to determine the differentially expressed miRNAs (DEmiRNAs) in the blood of BIPF FMD. The DEmiRNAs were further detected in the blood and lung of BIPF model rat by RT-qPCR, and the targeting relationship between candidate miRNA and its potential target gene was verified by dual-luciferase reporter activity assay. Furthermore, the function of the candidate miRNA was verified in the FMD lung fibroblast cells (FMD-C1).
Here we found that five dead FMD were suffered from BIPF, and six circulating miRNAs (miR-30g, let-7f-5p, miR-27-3p, miR-25-3p, miR-9-5p and miR-652) were differentially expressed in the blood of the BIPF FMD. Of these, let-7f-5p showed reproducibly lower level in the blood and lung of the BIPF model rat, and the expression levels of PI3K/AKT/COX2 signaling pathway genes (PIK3CA, PDK1, Akt1, IKBKA, NF-κB1 and COX2) were increased in the lung of BIPF model rats, suggesting that there is a potential correlation between BIPF and the PI3K/AKT/COX2 signaling pathway. Notably, using bioinformatic prediction and experimental verification, we demonstrated that let-7f-5p is conserved across mammals, and the seed sequence of let-7f-5p displays perfect complementarity with the 3’ UTR of PIK3CA gene and the expression of the PIK3CA gene was regulated by let-7f-5p. In order to determine the regulatory relationship between let-7f-5p and the PI3K/AKT/COX2 signaling pathway in FMD, we successfully cultured FMD-C1, and found that let-7f-5p could act as a negative regulator for the PI3K/Akt/COX2 signaling pathway in FMD-C1. Collectively, this study not only provided a study strategy for non-invasive research in pulmonary disease in rare animals, but also laid a foundation for further research in BIPF.
Forest musk deer (FMD) is listed as endangered by the International Union of the Conservation of Nature. The adult male FMD could secrete musk, which play an important economic value in traditional Asian medicine and international perfume industries. The population of captive FMD has been hampered by bacterial pneumonia, which accounts for 50% of all deaths. Specifically, pulmonary fibrosis has been presented in almost all of the bacterial pneumonia FMD (Zhang, Wang & Lin, 1997; Zhao et al., 2020). Pulmonary fibrosis is one of the respiratory refractory diseases affecting human and animal health (Williams, 2014), which is a progressive fatal disease accompanied by the inflammatory response, excessive proliferation of fibroblast cell, and deposition of extracellular matrix (ECM) (Williams, 2014; Hsu et al., 2017; Wang et al., 2021a). Many reasons can contribute to the shaping of pulmonary fibrosis, including virus infection, aberrant wound healing, irradiation, and environmental agents (Chioma & Drake, 2017). Of note, accumulating evidence suggests that infectious bacterial, such as Pseudomonas aeruginosa, Streptococcus pneumoniae, and Staphylococcus aureus, also play a role in pulmonary fibrosis (Chioma & Drake, 2017). The earliest evidence of bacterial involvement in pulmonary fibrosis showed that Mycobacteria can induce pulmonary lesions by the activator of T lymphocytes (Seggev, Goren & Kirkpatrick, 1984). By using the pulmonary fibrosis model, Knippenberg et al. (2015) uncover a novel mechanism that Streptococcus pneumoniae causes progression of established pulmonary fibrosis in mice through releasing pneumolysin. In addition, the correlation between lung microbiome and pulmonary fibrosis was analyzed by 454 pyrosequencing, and the results showed that the pulmonary fibrosis progression is associated with the presence of Streptococcus genera (Han et al., 2014). Currently, the mechanism of bleomycin/LPS-mediated pulmonary fibrosis has been widely studied in recent years, much less data is available in BIPF (Chioma & Drake, 2017). MiRNAs are non-coding small RNAs that play vital roles in the posttranscriptional regulation of gene expression (Chen et al., 2008). In recent years, studies have shown that miRNAs have been widely used in the study of the pathogenic mechanisms of many diseases, including infectious diseases (Bhaskaran & Mohan, 2014). Most importantly, Chen et al. (2008) reported that a barrage of miRNAs are present in body fluids (blood, saliva, tears, urine, milk and seminal fluid), termed circulating miRNAs, which might play a role in information transfer from organs/tissue to the body fluid. Thus, the specific expression profiles of circulating miRNAs can reflect changes in expression in organs/tissue. Slota et al. (2019) study in Père David’s deer chronic wasting disease found that the expression profile of circulating miRNAs were changed in prion disease individual, of note, miR-148a-3p, miR-186-5p, and miR-30e−3p were proved to have a strong correlation with prion disease. The follow-up studies have characterized that circulating miRNAs are suitable candidates to serve as a study strategy for pulmonary fibrosis (Liu et al., 2021). Huang et al. (2012) reported that miR-125b-5p, miR-128, miR-30e, and miR-20b were significantly changed in lung tissue and in plasma of fibrosis mice. Chouri et al. (2018) demonstrated that circulating miR-483-5p could regulate the expression of fibrosis-related genes in fibroblast and endothelial cells by screening and functional study of miRNA in mice serum. At present, the mechanism of bleomycin/LPS-mediated pulmonary fibrosis has been widely studied in recent years, but the pathogenesis of BIPF is limited (Liu et al., 2018; Chioma & Drake, 2017). Herein, we sought to determine whether miRNAs exist that modulates the pathogenesis of BIPF in FMD. Using high-throughput sequencing and experimental verification, we have confirmed that circulating let-7f-5p is differentially expressed in blood of BIPF FMD and rats compared to the healthy control. Furthermore, the role of let-7f-5p in regulating the PI3K/AKT/COX2 signaling pathway was validated in the lung of BIPF-infected rat and FMD-C1, which implied that let-7f-5p could regulate the PI3K/AKT/COX2 signaling pathway in BIPF. Collectively, our results uncover a novel role for let-7f-5p in BIPF, which provided promising knowledge for further BIPF researches.
Blood samples were collected from five healthy (H1-H5; three male and two female, n = 5) and five dead (P1-P5; three male and two female, n = 5) FMD (Sichuan Institute of Musk Deer Breeding) and stored at −80 °C in the blood RNA Shield tube (Tianmo, Beijing, China). The sick FMD were looked after by us throughout the day. When the condition worsened, we monitored their breathing, heartbeat, pulse, and reflexes. With the disappearance of the above indicators, we determined that the FMD died, and performed an autopsy on the FMD, it was observed that the lungs were surrounded by peptone-like exudate. To meet the required standards of blood sample for testing, the cause of death of FMD was detected by pathogen detection and histopathological observation, molecular identification based on 16S rDNA sequences was conducted using general primers 27F and 1492R as previously described (Zhao et al., 2017). Besides, to examine the degree of fibrosis, the lung specimens were harvested and fixed with 4% paraformaldehyde solution for histological analysis with Masson’s trichrome and Picrosirius red staining. The animal study protocol was approved by the Ethics Committee of Sichuan Agricultural University (protocol code No. SYXK2019-187).
The RNA was extracted from six mL blood from each individual healthy (n = 5) and dead (n = 5) FMD using a Total RNA extraction kit (Tianmo, Beijing, China) following the manufacturer’s instructions. The statistical power of this experimental design, calculated in G*Power software (3.1.9.7, http://www.gpower.hhu.de/) (Kang, 2021) is 0.42. The integrity of RNA was assessed using electrophoresis with 1.0% denatured agarose gel and Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The RNA concentration was determined by a NanoDrop ND1000 system (Thermo Fisher Scientific, Waltham, MA, USA). The RNA meeting the following requirements was used for library construction: (a) The total RNA concentration is greater than 200 ng/µL; (b) RNA integrity number ≥ 8; (c) 28S/18S ratio ≥ 1.8. The small RNA libraries were generated using NEBNext® Multiplex Small RNA Library Preparation kit (New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s instructions. The RNA was reverse transcribed into cDNA immediately using Super Script II Reverse Transcriptase (Invitrogen, Waltham, MA, USA). Fragmented libraries were enriched by PCR amplification, and added with universal PCR primers and an index (X) primer. Prior to sequencing, the quality and quantity RNA libraries were evaluated by Agilent 2100 Bioanalyzer with Agilent High Sensitivity DNA Kit and Quant-iT PicoGreen dsDNA Assay Kit, respectively. Finally, qualified libraries were sequenced on Illumina NextSeq 500 sequencing platform producing 75-bp single end reads (>23 million for each sample) at Personal Biotechnology Co., Ltd (Shanghai, China).
After getting the raw data (5 healthy and 5 dead FMD blood samples), the ligated adapter sequences were removed by Cutadapt software (https://cutadapt.readthedocs.io/), the sequence data of low quality reads (average quality score <20; read lengths <18 and >32 nt) were discarded (Sun et al., 2019a). Next, the Rfam database (http://rfam.janelia.org/) was used to extract the reads of rRNAs, tRNAs, snRNAs, and snoRNAs. The rest of reads were aligned to the miRBase 21 databases (http://www.mirbase.org/), and achieved the conservative miRNA (each miRNA was allowed ≤ 2 base mismatches). The expression level of the known miRNA was quantified as Transcripts Per Million values. The DESeq2 package (http://www.bioconductor.org/packages/release/bioc/html/ DESeq2.html) was used to analyze DEmiRNAs with p < 0.05 and —log2fold change— >1. Subsequently, miRanda v3.3a (http://cbio.mskcc.org/microrna_data/manual.html) and TargetScan 7.2 (http://www.targetscan.org/vert_72/) were used to predict the target genes of DEmiRNAs. DEmiRNAs-target gene network was visualized using the Cytoscape software (ver. 3.6.1; http://www.cytoscape.org). Functions and metabolic pathways of these target genes were classified by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and KEGG pathways were screened at p-value <0.05 and false discovery rate (FDR) <0.05.
In this study, 1.5 µL of 20 pmol/µL synthetic C. elegans miRNA (cel-miR-39: 5′-UCACCGGGUGUAAAUCAGCUUG-3′) was added to the blood, which was used for sample-to-sample normalization (Kroh et al., 2010; Hromadnikova et al., 2017). Then, the total RNA of each individual healthy (n = 5) and dead (n = 4) (All the blood sample of a dead FMD (P4) was used to miRNA-seq) FMD blood was extracted using Total RNA extraction kit (Tianmo, Beijing, China) following the manufacturer’s instructions. The RNA was reverse transcribed into miRNA cDNA immediately using miRcute Plus miRNA First-Strand cDNA synthesis Kit (TianGen, Beijing, China). The DEmiRNAs were detected using miRcute Plus miRNA qPCR Kit (SYBR Green) (TianGen, Beijing, China). The PCR conditions were as follows: initial denaturation at 95 °C for 15 min, 5 thermal cycles (94 °C for 20 s, 64 °C for 30 s, 72 °C for 34 s) to enrichment of target miRNAs, 45 cycles of 94 °C for 20 s and 60 °C for 34 s. The DEmiRNAs forward primers were designed based on mature miRNA sequences and reverse primers were provided by the miRcute Plus miRNA qPCR Kit (SYBR Green) (TianGen, Beijing, China). The target miRNAs in the blood were normalized using the synthetic C. elegans cel-miR-39 (Kroh et al., 2010). The sequences of the DEmiRNAs primers used are listed in Table S1. The relative DEmiRNAs expression levels were calculated using the 2−ΔΔCT method.
In order to establish BIPF model, we carried out a pilot study and found that the pathogenic bacteria isolated from FMD lung, including Klebsiella pneumoniae strain DJY-1, Pseudomonas aeruginosa strain YW1 and Streptococcus equinus strain FMD1, which could cause bacterial pneumonia in rodents (Zhao et al., 2021). A total of 20 adult female Wistar rats (8-week-old; specific-pathogen-free) (Chengdu Dossy Experimental Animals Co, Ltd, Chengdu, 610000, China) were randomly divided into four groups, which received sterile physiologic saline as control group (CG group, n = 5), Klebsiella pneumoniae (KG group, n = 5), Pseudomonas aeruginosa (PG group, n = 5) and Streptococcus equinus (SG group, n = 5) by nasal drip under anesthesia as described in Chen et al. (2017). For group KG, PG and SG, the three pathogens were administered at a dose of 108∼109 CFU per rat. In order to prevent cross-contamination of pathogens, each group rats were housed in a separate cage with enough distance. The rats had free access to food and water ad libitum with a 12 h light/dark cycle. On day 21, the rats were weighed and sacrificed after anesthesia, and the blood was collected into blood RNA Shield tube (Tianmo, Beijing, China). The lung samples were weighed and collected, and then one part of the lung tissue was collected into RNALater™ RNA Stabilization Reagent (Beyotime, Shanghai, China). The blood and lung specimens were stored at liquid nitrogen until total RNA extraction. Immediately afterward, the other part was fixed with 4% paraformaldehyde solution and stained with hematoxylin-eosin (HE), masson’s trichrome and picrosirius red staining.
The method of DEmiRNAs in rat blood and lung determination was the same as above. There is a slight difference in the lung miRNA detection that the target miRNAs in the lung were normalized using U6 snRNA (Wang et al., 2017). The sequences of the DEmiRNAs primers used are listed in Table S1. The relative DEmiRNAs expression levels were calculated using the 2−ΔΔCT method.
We evaluate the expression level of pulmonary fibrosis-related genes, including transforming growth factor-β1 (TGF-β1), tumor necrosis factor- α (TNF-α), and PI3K/AKT/COX2 signaling pathway genes: phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA), phosphoinositide-dependent protein kinase 1 (PDK1), serine/threonine kinase 1 (Akt1), inhibitor of nuclear factor kappa-B kinase subunit alpha (IKBKA), nuclear factor kappa B subunit 1 (NF-κB1) and cyclooxygenase-2 (COX2), in the rat lung tissue using RT-qPCR analysis. The total RNA was extracted from the rat lung using Total RNA extraction kit (Tianmo, Beijing, China), and reversed transcribed using HiScript III 1st Strand cDNA Synthesis Kit (+gDNA wiper) (Vazyme Biotech Co., Ltd, Nanjing, China). The β-actin was used as reference gene. The sequences of the gene primers used are listed in Table S2. The relative gene expression level was calculated using the 2−ΔΔCT method.
Total protein was extracted from rat lung tissue using Tissue or Cell Total Protein Extraction Kit (Sangon Biotech Co., Ltd, Shanghai, China) and protein concentration was determined by bicinchonininc acid (BCA) Protein Assay Kit (TianGen, Beijing, China). The PI3K/AKT/COX2 signaling pathway related proteins (PI3K, AKT1, and COX2) were analyzed by western blot. Equal amounts of 50 µg total proteins were separated on 10% SDS-PAGE gels and then transferred onto polyvinylidene fluoride (PVDF) blotting membranes. After being blocked with 5% bovine serum albumin (BSA) in phosphate buffer, the membranes were incubated with primary antibodies at 4 °C for the night. The primary antibodies used were PIK3CA rabbit polyclonal antibody (diluted 1:2,000), phospho-AKT1 (Ser473) rabbit polyclonal antibody (diluted 1:800), anti-COX2 antibody (diluted 1:1,000), and β-Actin rabbit monoclonal antibody (diluted 1:1,000). Following incubation with goat anti-rabbit secondary antibody (diluted 1:1,000) for 2 h at room temperature, the protein bands were visualized using an enhanced chemiluminescence detection system. The β-actin was used as an internal control for assessing equal loading of total protein among wells. In this study, the primary and secondary antibodies were purchased from Beyotime biological technology Co., Ltd (China) and Boster biological technology Co., Ltd (America).
The PIK3CA was predicted as target gene of let-7f-5p. For experimental validation of the PIK3CA 3′ UTR (untranslated region) as a target of let-7f-5p, the luciferase reporter plasmid was constructed, and a 200-bp fragment of the PIK3CA mRNA 3′ UTR containing the predicted let-7f-5p binding site (seed sequence) (PIK3CA mRNA 3′ UTR-WT) and its mutant sequence (PIK3CA mRNA 3′ UTR-MUT) were synthesized by Sangon and cloned into psiCHECKTM-2 vector (Sangon Biotech Co., Ltd., Shanghai, China) based on the Xho I and Not I restriction sites. The recombinant plasmids were confirmed by double digest and PCR amplification, the primers used are listed in Table S3. The FAM-labeled let-7f-5p mimics (5′-UGAGGUAGUAGAUUGUGUAGU-3′), let-7f-5p inhibitor (5′-ACUAUACAAUCUACUAC CUCA-3′) and mimics NC (5′-UUGUACUACACAAAAGUACUG-3′) were synthesized by Sangon. For transient transfections, the optimum concentration of let-7f-5p mimics, let-7f-5p inhibitor and mimics NC were carried out in HEK293T cells with the luciferase reporter constructs using Lipo8000™ Transfection Reagent (Beyotime Biotechnology, Co., Ltd., Shanghai, China). After 24 h of transfection, HEK293T cells were lysed by TransDetect® Double-Luciferase Reporter Assay Kit (TransGen Biotech Co., Ltd. Beijing, China) and the luciferase activity was measured by a Full wavelength scanning, multifunction reading instrument (Thermofisher, USA). The Renilla luciferase activities were normalized by that of firefly luciferase.
The pAAV-CMV-eGFP and helper plasmids were obtained from Prof Zhao, Huazhong Agricultural University, China (Huang et al., 2021). The FMD pri-let-7f-5p sequence (SPDX01004329: 114203-114718) was cloned into pAAV-CMV-eGFP plasmids based on the Hind restriction sites and homologous arm. The recombinant plasmids (rpAAV-pri-let-7f-5p) were confirmed by double digest and PCR amplification. Primers were designed based on the pAAV-CMV-eGFP sequence information (F: TGCTGCCCGACAACCA; R: CCCTTGCTCCATACC AC). Then, a packaging approach, which have been previously reported (Huang et al., 2021), was used to produce the rAAV, and the AAV was set as the blank control. Subsequently, the rAAV and AAV copy number was assessed by RT-qPCR and transduction assay according to the methods of Meng, Zhang & Zhang (2013). Finally, we successfully packaged the rAAV virus, which can be applied for let-7f-5p overexpressing in FMD-C1 cells (Fig. S1).
To provide further evidence that the PI3K/AKT/COX2 signaling pathway was regulated by let-7f-5p in FMD lung, we successfully isolated and cultured primary FMD-C1 cell, a detailed procedure of the methods of cell separation can be found in a previous study (Liu et al., 2012). FMD-C1 cells were transfected with let-7f-5p mimics and mimics NC using Lipo8000™ Transfection Reagent. Subsequently, FMD-C1 cells were infected with rAAVs and AAVs at a multiplicity of infection of 200 and incubated at 37 °C for 8 days. Finally, the expression level of PI3K/AKT/COX2 signaling pathway genes (PIK3CA, PDK1, Akt1, IKBKA, NF-κB1 and COX2) were detected by RT-qPCR. The total RNA was extracted from the rat lung and FMD-C1 using Total RNA extraction kit (Tianmo, Beijing, China), which was reversed transcribed using HiScript III 1st Strand cDNA Synthesis Kit (+gDNA wiper) (Vazyme Biotech Co., Ltd, Nanjing, China), the β-actin was used as reference gene. The sequences of the gene primers used in this study are listed in Table S2. The relative gene expression level was calculated using the 2−ΔΔCT method.
Statistical analyses were performed using GraphPad Prism 7.00 software. Data have been expressed as means ± Standard Error of Mean. Two-tailed student’s t test was performed to test for differences between the two groups, *p-value <0.05; **p-value <0.01.
The five FMD individuals died of bacterial pneumonia, and a pathogen was isolated from the lung of each of the dead FMD, namely Pseudomonas aeruginosa strain YW1 (Genbank NO. MN027911.1), Pseudomonas aeruginosa strain FMDP002 (Genbank NO. MN904450.1), Klebsiella pneumoniae strain DJY-1 (Genbank NO. OK036428), Streptococcus equinus strain FMD1 (Genbank NO. MK652875.1) and Trueperella pyogenes strain ZW1 (Genbank NO. MN027909.1), respectively (Fig. S2). In the five FMD lungs, histopathological examination showed some similar pathological changes in each individual, mainly including the normal structure of alveolus was lost, fibrous tissue was increased, and the lung interstitium was filled with a large number of fibroblast cells, neutrophils and lymphocytes. Picrosirius red and Masson’s trichrome staining showed increased fibrin and collagen in lung tissue of FMD (Fig. 1), implying that the five dead FMD were suffered from BIPF.
In the rat model, the ratio of the wet lung to body weight was calculated at 21 days post infection. Compared with the control group CG, the test group KG and PG exhibited significantly higher wet lung to body weight ratio (p < 0.01), but no significant change in test group SG (Fig. 2A). The results of the histological analysis are as follows: in the CG group, the normal structure of the rat lung was complete and clear, and no hyperplasia or thickening of connective tissue was found. The bronchial structure at all levels was complete and clear, and the alveolar epithelial cells were normal in shape without obvious degeneration, necrosis or exfoliation. Additionally, no obvious inflammatory cell infiltration and fibrous hyperplasia were observed in the interstitium. In three test group rats, the alveolar wall was collapsed in the rat lung tissue. The collagen fibers were proliferated in the lung interstitium. Besides, a large amount of fibroblast cells, inflammatory cells (mainly neutrophils and lymphocytes) were infiltrated in the lung interstitium (Fig. 2B). Picrosirius red and Masson’s trichrome staining showed that the lung tissues of three test groups (KG, PG and SG) exhibited severe fibrin and collagen secretion compared with that of the control group (Figs. 2B and 2C). Of note, the expression levels of TGF-β1 and TNF-α were both upregulated in the lung of test group rats compared with that of the control group (Fig. 2D). These results indicate that the lung of rat in three test groups had developed fibrosis.
As there is no available miRNA annotation information in miRBase21 for FMD, the known miRNAs were identified by blast searches against all animal reference sequences in miRBase21. Between 25 and 42 million raw reads were obtained for each sample (Table S4). After being trimmed, a total of 313 million clean reads (>18 nt) were obtained. Among these clean reads, small RNA with the length of 18–24 nt was most abundant in FMD blood samples. The miRNAs profiles of each blood samples were identified based on the miRBase21 database after the annotated and unconcerned reads were removed such as rRNA, tRNA, snRNA and snoRNA. A total of 10,088 known miRNAs were identified from 10 blood samples. Among these known miRNAs in the study, nine DEmiRNAs, namely, miR-30g, let-7f-5p, miR-25-3p, miR-27d-3p, miR-451-3p, miR-142-5p, miR-652, miR-9-5p and miR-206-3p, satisfied the screening criteria of p < 0.05, —log2fold change—>1 between the healthy and dead group FMD. Expression of miR-451-3p, miR-142-5p, miR-652, miR-9-5p and miR-206-3p expression were upregulated in the dead group. Four miRNAs, miR-30g, let-7f-5p, miR-25-3p and miR-27d-3p, were downregulated in the dead group (Table 1). We selected the nine DEmiRNAs to determine their expression patterns using RT-qPCR detection in FMD and rat blood. In the FMD blood, the results of RT-qPCR showed that the trend of 5 DEmiRNAs (miR-30g, let-7f-5p, miR-27-3p, miR-25-3p and miR-652) expression was consistent with the high-throughput sequencing data (Fig. 3A), indicating significant differences in the 6 DEmiRNAs expression between the healthy and dead FMD. In rat model, of the nine miRNAs tested in FMD blood, the let-7f-5p and miR-27d-3p expression level were reduced in the blood of test rat, and the level of miR-652 increased in the three test groups compared with the control group (Fig. 3B). The same changes of let-7f-5p and miR-652 were also observed in the lung of BIPF rats (Fig. 3C).
Among the KEGG term, twelve KEGG pathways significantly enriched for target genes of the DEmiRNAs (p < 0.05; FDR < 0.05) (Table 2, Fig. 4A) based on KEGG analysis. Importantly, the pathway of ECM-receptor interaction and focal adhesion may be of particular importance in this study since these two pathways often associated with lung-related diseases, for example pulmonary fibrosis (Tian et al., 2019). As aforementioned in the target gene analysis, a total of 21 and 39 target genes of the let-7f-5p and miR-652 were involved in ECM-receptor interaction and focal adhesion pathways, respectively (Fig. 4B). It is worth noting that the whole and seed sequences of let-7f-5p are highly conserved across species, and the seed sequence is complementary with the binding site on the PIK3CA mRNA (Fig. 4C), suggesting that the let-7f-5p may participate in post-transcriptional regulation of PIK3CA gene. The luciferase reporter plasmid was constructed for experimental validation of the relationship between let-7f-5p and PIK3CA (Fig. S3). The luciferase reporting assay confirmed the direct target relationship between let-7f-5p and the PIK3CA gene (Fig. 4D). In addition, the PI3K/AKT/COX2 signaling pathway genes (PIK3CA, PDK1, Akt1, IKBKA, NF- κB1 and COX2) were examined in rat model. Compared to control group, three test groups of rats exhibited increased mRNA expression level of PIK3CA, PDK1, IKBKA, NF-κB1 and COX2 genes with significant difference (p < 0.05) (Fig. 5A). In addition, the mRNA expression level of Akt1 gene exhibited a trend of increase in three test group rats, and significantly increased in PG rats (p < 0.05) (Fig. 5A). Besides, compared with the control group, three test groups exhibited significantly higher protein expression levels of PI3K, AKT1, and COX2 (Fig. 5B). The high level of the PI3K/AKT/COX2 signaling pathway mRNA and protein expression found in three test group rats, suggesting that there is a potential correlation between BIPF and the PI3K/AKT/COX2 signaling pathway.
Overall, we hypothesized that the let-7f-5p may participate in the regulation of the PI3K/AKT/COX2 signaling pathway in BIPF FMD. After 24 h of transfection, the PIK3CA, PDK1, Akt1, IKBKA, NF- κB1 and COX2 expression decreased in let-7f-5p mimics group compared with let-7f-5p mimics NC group (Fig. 6). In addition, the PI3K/AKT/COX2 signaling pathway genes were decreased in rAAV infection FMD-C1 (Fig. 6). These results supported the hypothesis that the let-7f-5p could regulate the PI3K/AKT/COX2 signaling pathway in the FMD lung.
Pulmonary fibrosis is the final stage of many lung diseases in humans, which have also been described in dogs, cats, horses and FMD (Zhang, Wang & Lin, 1997; Zhao et al., 2020; Williams, 2014; Marenzoni et al., 2011). In this study, five FMD were found suffering from BIPF. FMD is an endangered and protected animal in China, just like other protected animals, it is forbidden to conduct animal regression experiments on FMD. However, it is not conducive to the study of BIPF of FMD without healthy control. Therefore, in this study, BIPF model in rat was established by FMD origin pathogens, including Klebsiella pneumoniae, Pseudomonas aeruginosa and Streptococcus equinus. These pathogens are isolated from the FMD lung and have been shown to cause the death of mice (Zhao et al., 2020; Zhao et al., 2021). HE, Picrosirius red and Masson’s trichrome staining showed increased inflammatory cells, fibrin and collagen in the lung of test group rats, demonstrating that these lung tissues are fibrosis. Hsu et al. (2017) have also measured the morphology of pulmonary fibrosis using HE, Picrosirius red and Masson’s trichrome staining. Meanwhile, the level of TGF-β1 and TNF-α were upregulated in the lung of the test group rats. Similar results have been reported in bleomycin/LPS-induced pulmonary fibrosis model (Hu et al., 2020; Elliot et al., 2019). Reportedly, TGF-β1 and TNF-α are important cytokines in mediating pulmonary fibrosis and have been demonstrated in many studies (Li et al., 2018). TGF- β1 promotes the growth of fibroblast cells and the accumulation of ECM, mainly collagen and fibronectin, and also could inhibit the degradation of ECM (Chioma & Drake, 2017). TNF-α has been widely accepted as an important inflammatory cytokine, and has also been reported to exacerbate the inflammatory response and promote TGF-β1 secretion in lung fibroblast cells (Wang et al., 2021b). Collectively, these results demonstrated that the origin of FMD pathogen could cause BIPF in rat. Establishment of the rat model of BIPF may lay a foundation for the study of pathogenesis of BIPF in FMD. In this study, nine DEmiRNAs were found in the blood between the healthy and dead group FMD. It was reported that circulating miRNA may provide information about the disease status of organ/tissue and contain fingerprints for a range of many diseases (Chen et al., 2008), and have been applied to the diagnosis and mechanism research of pulmonary disease in human (Liu et al., 2021). Besides, miRNAs are conserved between species that we can use the same sequence between different animals, and its function could be verified in animal model (Lin, Chang & Ying, 2006). Thus, we used RT-qPCR to analyze the transcript level of the nine FMD blood DEmiRNA in blood and lung of BIPF model rat, and found that let-7f-5p and miR-652 were differentially expressed simultaneously in the rat blood and lung, suggesting that the let-7f-5p and miR-652 might be new candidates for the mechanism study of BIPF. Previous researches in miR-652 analysis have tended to focus on tumor proliferation and metastasis (Sun et al., 2018). The let-7 family miRNAs have previously been shown to participate in regulation of the pulmonary fibrosis. For example, Li et al. (2018) reported that let-7 family miRNA was proved to be an inhibitor that could downregulate estrogen receptor which plays a pivotal role in male-predominant pulmonary fibrosis. Also, Zhu et al. (2011) reported that let-7 plays a significant regulatory role in modulating glucose metabolism via negatively regulating the activity of the insulin-PI3K-mTOR signaling pathway. At the same time, research suggests that the change in glucose metabolism is an important pathogenic process of pulmonary fibrosis, and the effects were linked to the TGF-β secretion, ECM synthesis, collagen production, glucose transporter, inflammatory response, and immune response (Selvarajah et al., 2021; Yin et al., 2021; Gopu et al., 2020). These studies reinforce our notion that the let-7 family and PI3K may play important roles in the pulmonary fibrosis. Let-7f-5p, a member of the let-7 family, has been reported to remit pulmonary fibrosis through regulating cellular reactive oxygen species, mitochondrial DNA damage and cell apoptosis (Sun et al., 2019b). In the bleomycin-induced lung fibrosis model, Xie et al. (2011) reported that the potential target genes of let-7f may contribute to the complex transcriptional program of pulmonary fibrosis. Herein, we continuously select let-7f-5p to explore the underlying molecular mechanism of BIPF. To the best of our knowledge, this is the first demonstration of circulating miRNA change in any animal suffering from BIPF. We know that miRNA play important roles in the regulation of target gene expression, which are often involved in some important pathway. In this study, the pathway-enriched analysis indicated that the target genes of the DEmiRNAs were highly associated with functions in the ECM-receptor interaction and focal adhesion pathways. In the pulmonary fibrosis patients, proteomic analysis of lung tissue showed that the altered proteins mainly belonged to ECM-receptor interaction and focal adhesion pathways (Tian et al., 2019). The abnormal ECM receptor interaction and focal adhesion pathways could lead to the accumulation of ECM, which has been identified as a major driving force for the development and persistence of fibrosis diseases (Liu et al., 2021). In addition, the target gene of let-7f-5p, including PIK3CA gene, was determined to be key gene that was reported to play an important role in the focal adhesion pathway (Margaria et al., 2022). It is worth noting that the PIK3CA gene is a key component in the PI3K/Akt pathway, which plays a critical role in the development pulmonary fibrosis (Hsu et al., 2017). With the in depth study of the PI3K/Akt pathway, studies reported that the activation of some factors, such as mammalian target of rapamycin, vascular endothelial growth factor and reactive oxygen species and COX2 in the downstream of the PI3K/AKT signaling pathway can participate in pulmonary fibrosis (Laddha & Kulkarni, 2019; Wu et al., 2018b). In the BIPF model, we found that the FMD pathogen promotes PI3K/AKT/COX2 signaling pathway related genes mRNA expression in rat lung. Recently, several studies have revealed that COX2 was highly induced by many different pathogens involved in pulmonary fibrosis, and COX2 can take part in the pathological process of alveolar inflammation and pulmonary fibrosis by inducing prostaglandin synthesis and microvascular hyperplasia (Wu et al., 2018b; Li, 2009). In pulmonary fibrosis model, Moore et al. (2000) found that compared with control mice, the expression level of COX2 was increased in the blood and lung of mice at 14 and 21 d after treated with bleomycin. Our results suggest that the PI3K/AKT/COX2 signaling pathway may contribute importantly to the pathogenesis of BIPF. Taken together, we hypothesized that let-7f-5p is a key regulator of BIPF in FMD via targeting of the PI3K/AKT/COX2 signaling pathway. Therefore, we further demonstrated the targeting relationship between let-7f-5p and PIK3CA using bioinformatics analysis and experimental verification in HEK293T and FMD-C1 cells. This is consistent with previous research (Gilles & Slack, 2018), which showed that both let-7f-5p and its seed sequence were conserved between different species. In addition, we successfully isolated fibroblast cells from the lung of FMD, this is the first reported of fibroblast cells from FMD. As a key cell type driving the fibrogenic process, fibroblast cells can trigger pulmonary fibrosis directly through abnormal proliferating and transforming, and promote the secretion of ECM, cytokine and inflammatory cell. Moreover, various fields of pulmonary fibrosis researches have retained in relation to fibroblast cells (Wu, Tang & Kapoor, 2021). Notably, we found that let-7f-5p is a negative regulator for the PI3K/AKT/COX2 signaling pathway in FMD-C1, confirming our hypothesis that let-7f-5p could regulate PI3K/AKT/COX2 signaling pathway in BIPF through suppression of PIK3CA expression (Fig. 7). It is worth noting that the activation of PI3K is directly contribute to collagen- and fibro-proliferative has been confirmed repeatedly in many laboratories. Hsu et al. (2017) reported that many PI3K inhibitors have been developed for the treatment of pulmonary fibrosis. Thus, as a PI3K inhibitor, let-7f-5p may be a potential therapeutic molecule for BIPF.
In conclusion, we successfully identified let-7f-5p related to BIPF in FMD by combining the analysis of circulating miRNA, establishment of BIPF rat model and culture of FMD lung fibroblast cells. Of note, let-7f-5p could regulate the PI3K/AKT/COX2 signaling pathway in BIPF through suppression of PIK3CA expression. In this article, we believe that our study particularly strengthens the design for the non-invasive research in pulmonary disease in rare animals, and also provides further insights into the molecular mechanisms of BIPF.
10.7717/peerj.14097/supp-1 Click here for additional data file. 10.7717/peerj.14097/supp-2 Click here for additional data file. 10.7717/peerj.14097/supp-3 Click here for additional data file. 10.7717/peerj.14097/supp-4 Click here for additional data file. 10.7717/peerj.14097/supp-5 Click here for additional data file. | true | true | true |
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PMC9548164 | Tongyan Liu,Chencheng Han,Panqi Fang,Zhifei Ma,Xiaoxiao Wang,Hao Chen,Siwei Wang,Fanchen Meng,Cheng Wang,Erbao Zhang,Guozhang Dong,Hongyu Zhu,Wenda Yin,Jie Wang,Xianglin Zuo,Mantang Qiu,Jinke Wang,Xu Qian,Hongbing Shen,Lin Xu,Zhibin Hu,Rong Yin | Cancer-associated fibroblast-specific lncRNA LINC01614 enhances glutamine uptake in lung adenocarcinoma | 08-10-2022 | Tumor microenvironment,Cancer-associated fibroblasts,Long noncoding RNA,Metabolic reprograming,Glutamine | Background Besides featured glucose consumption, recent studies reveal that cancer cells might prefer “addicting” specific energy substrates from the tumor microenvironment (TME); however, the underlying mechanisms remain unclear. Methods Fibroblast-specific long noncoding RNAs were screened using RNA-seq data of our NJLCC cohort, TCGA, and CCLE datasets. The expression and package of LINC01614 into exosomes were identified using flow cytometric sorting, fluorescence in situ hybridization (FISH), and quantitative reverse transcription polymerase chain reaction (RT-PCR). The transfer and functional role of LINC01614 in lung adenocarcinoma (LUAD) and CAFs were investigated using 4-thiouracil-labeled RNA transfer and gain- and loss-of-function approaches. RNA pull-down, RNA immunoprecipitation, dual-luciferase assay, gene expression microarray, and bioinformatics analysis were performed to investigate the underlying mechanisms involved. Results We demonstrate that cancer-associated fibroblasts (CAFs) in LUAD primarily enhance the glutamine metabolism of cancer cells. A CAF-specific long noncoding RNA, LINC01614, packaged by CAF-derived exosomes, mediates the enhancement of glutamine uptake in LUAD cells. Mechanistically, LINC01614 directly interacts with ANXA2 and p65 to facilitate the activation of NF-κB, which leads to the upregulation of the glutamine transporters SLC38A2 and SLC7A5 and eventually enhances the glutamine influx of cancer cells. Reciprocally, tumor-derived proinflammatory cytokines upregulate LINC01614 in CAFs, constituting a feedforward loop between CAFs and cancer cells. Blocking exosome-transmitted LINC01614 inhibits glutamine addiction and LUAD growth in vivo. Clinically, LINC01614 expression in CAFs is associated with the glutamine influx and poor prognosis of patients with LUAD. Conclusion Our study highlights the therapeutic potential of targeting a CAF-specific lncRNA to inhibit glutamine utilization and cancer progression in LUAD. Supplementary Information The online version contains supplementary material available at 10.1186/s13045-022-01359-4. | Cancer-associated fibroblast-specific lncRNA LINC01614 enhances glutamine uptake in lung adenocarcinoma
Besides featured glucose consumption, recent studies reveal that cancer cells might prefer “addicting” specific energy substrates from the tumor microenvironment (TME); however, the underlying mechanisms remain unclear.
Fibroblast-specific long noncoding RNAs were screened using RNA-seq data of our NJLCC cohort, TCGA, and CCLE datasets. The expression and package of LINC01614 into exosomes were identified using flow cytometric sorting, fluorescence in situ hybridization (FISH), and quantitative reverse transcription polymerase chain reaction (RT-PCR). The transfer and functional role of LINC01614 in lung adenocarcinoma (LUAD) and CAFs were investigated using 4-thiouracil-labeled RNA transfer and gain- and loss-of-function approaches. RNA pull-down, RNA immunoprecipitation, dual-luciferase assay, gene expression microarray, and bioinformatics analysis were performed to investigate the underlying mechanisms involved.
We demonstrate that cancer-associated fibroblasts (CAFs) in LUAD primarily enhance the glutamine metabolism of cancer cells. A CAF-specific long noncoding RNA, LINC01614, packaged by CAF-derived exosomes, mediates the enhancement of glutamine uptake in LUAD cells. Mechanistically, LINC01614 directly interacts with ANXA2 and p65 to facilitate the activation of NF-κB, which leads to the upregulation of the glutamine transporters SLC38A2 and SLC7A5 and eventually enhances the glutamine influx of cancer cells. Reciprocally, tumor-derived proinflammatory cytokines upregulate LINC01614 in CAFs, constituting a feedforward loop between CAFs and cancer cells. Blocking exosome-transmitted LINC01614 inhibits glutamine addiction and LUAD growth in vivo. Clinically, LINC01614 expression in CAFs is associated with the glutamine influx and poor prognosis of patients with LUAD.
Our study highlights the therapeutic potential of targeting a CAF-specific lncRNA to inhibit glutamine utilization and cancer progression in LUAD.
The online version contains supplementary material available at 10.1186/s13045-022-01359-4.
Metabolic reprogramming is a hallmark of cancer, which endows cancer cells with growth and proliferative potential under nutrient-deprivation tumor microenvironment (TME) conditions [1]. The founding observation in cancer metabolism was the use of aerobic glycolysis, wherein glucose is mainly processed into lactate [2]. Beyond glycolysis, cancer cells also use glutaminolysis and fatty acid oxidation to support their biosynthetic demands [3]. Recently, studies have revealed that glucose is preferentially consumed by immune cells (than cancer cells), whereas cancer cells exhibited the highest glutamine uptake, highlighting the probability that cancer cells conditionally prefer specific “addicting” nutrients in the TME [4, 5]. However, little is known about intrinsic mechanisms that facilitate the addiction phenomenon of cancer cells. Recent studies have demonstrated that one of the abundant stromal components in the TME, i.e., cancer-associated fibroblasts (CAFs), is important in regulating cancer cell metabolism and acts as potential cancer therapeutic targets [6]. Previous findings have demonstrated that the metabolic intermediates and ATP produced by CAFs support the growth of adjacent cancer cells [7–9]. High FAK-expressing CAFs enhance glycolysis of breast and pancreatic cancer cell by increasing chemokine production [10]. However, whether and how CAFs facilitate a preference for specific “addicting” nutrients remain unclear in lung cancer. In the present study, transcriptomic and metabolomic analyses indicated that CAFs mainly regulate the amino acids of lung adenocarcinoma (LUAD) cells in an exosome-dependent manner. We also found that CAF-derived exosomes preferentially enhance glutamine uptake in LUAD cells. Mechanistically, exosome-packaged long noncoding RNAs (lncRNAs) are shown to play a critical role in mediating crosstalk between cancer cells and TME [11]. More importantly, because the expression of lncRNAs is remarkably tissue and cell type-specific [12–14], the discovery of lineage and TME-specific lncRNAs in exosomes mediating crosstalk between CAFs and LUAD cells may provide further insights regarding their roles in cancer progression. Because of the limitation of scRNA-seq with respect to identifying noncoding transcripts, we screened and validated non-tumor expressed lncRNAs in TME populations based on the Nanjing Lung Cancer Cohort (NJLCC) [15] and The Cancer Genome Atlas (TCGA)-LUAD dataset, and eventually examined their presence in CAF-derived exosomes. We identified LINC01614 as a CAF-specific lncRNA and demonstrated that CAF-exosome-packaged LINC01614 could regulate the glutamine metabolism of cancer cells. We further dissected the mechanisms underlying these actions.
Human primary fibroblasts were isolated from fresh LUAD tissues (CAFs) and adjacent non-tumor tissues (NFs). Samples were collected after surgical resection of the tissue storage buffer (Miltenyi) and washed in phosphate-buffered saline (PBS) containing 1% antibiotic–antimycotic (Gibco, Life Technologies). The tissues were minced into small (1–2 mm) pieces and digested with a Human Tumor Dissociation Kit using gentleMACS Octo Dissociator following the manufacturer’s instructions (Miltenyi). The digested samples were sequentially filtered through 70 μm cell strainers. The cells were then collected by centrifugation at 250 g for 5 min and grown in Dulbecco's Modified Eagle Medium (DMEM) (Gibco, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum (FBS) and 1% antibiotic–antimycotic at 37 °C. The medium was changed every 3 d. Fibroblasts were obtained using a differential time adherent method, as previously reported [16]. The purity of fibroblasts was evaluated with flow cytometry analysis and immunofluorescent staining. Primary CAFs were negative for EpCAM, CD45, and CD31 and positive for FAP and α-SMA. Cells were used up to 10 passages. The clinical information for patients whose tumors were used for CAF and NF isolation is listed in Additional file 1: Table S1. All samples were obtained from the donors with informed consent, and all related procedures were conducted with the approval of the Ethics Committee of Jiangsu Cancer Hospital. To knock down or overexpress specific genes, primary fibroblasts were transduced with the lentiviral vectors (multiplicity of infection [MOI] of 100) at 37 °C with 5 μg mL−1 polybrene (Sigma). The targeting sequences of each shRNA are provided in Additional file 1: Table S2.
All cell lines (A549, SPC-A1, H1975, H827, H2228, PC9, MRC5, and human bronchial epithelial (HBE) cells) were obtained from Shanghai Institutes for Biological Science (Shanghai, China). In a 6-well Transwell system, A549 or H1975 cells (1 × 106) were plated on the lower chamber, whereas CAFs (1 × 106) were added to the upper chamber; the pore size was 0.4 μm. All cells were grown in DMEM supplemented with 10% fetal bovine serum (FBS), 50 U mL−1 penicillin (Gibco), and 50 μg mL−1 streptomycin (Gibco). All cells were authenticated and tested routinely for their authenticity and free from mycoplasma contamination. Cell proliferation was detected using a Real-time xCELLigence analysis system (RTCA) according to the manufacturer’s protocol (ACEA Biosciences). Migration assay of LUAD cells was performed in an 8 μm 24-well Boyden chamber (Millipore). Corning BioCoat Matrigel Invasion Chambers with 8 μm PET membranes (Corning) were used for invasion assays. LUAD cells (2 × 104) suspended in 100 μL FBS-free DMEM were added to the upper chamber. 1 × 106 CAFs concentrated in 750 μL of DMEM containing 10% FBS were added to the bottom of a 24-well plate. LUAD cells were allowed to migrate or invade for 24 h and 48 h, respectively. Quantification was performed by counting the mean number of cells in three microscopy fields per chamber. For a specific signaling pathway study, cells were pretreated with the vehicle (DMSO) and 6 μM JSH-23 or 10 μM BMS-345541 for 1 h at 37 °C prior to the experiments.
All primary LUAD tissues and adjacent normal tissues were obtained from 154 patients who underwent surgery at the Affiliated Cancer Hospital of Nanjing Medical University (Jiangsu Cancer Hospital, Nanjing, China). Tissue samples were used to quantify LINC01614, α-SMA, SLC38A2, and SLC7A5 and Kaplan–Meier survival analysis. A total of 78 pairs of LUAD and adjacent normal tissues from the JSCH cohort were used to construct the TMA, as described previously [17]. All samples were reviewed by experienced pathologists and performed in accordance with the International Ethical Guidelines for Biomedical Research Involving Human Subjects. All samples were collected from patients with informed consent, and all related procedures were conducted with the approval of the Ethics Committee of Jiangsu Cancer Hospital (approval Number: No. 2018(83), 2018(107)).
LUAD cells were cultured to ~ 40% confluency and changed with the conditional medium. After 24 h, the cells were collected, and measurement of TCA metabolites (glutamate, succinate, and fumarate) was performed using kits from Biovision (catalogue nos. ab). An Enliten ATP assay system (Promega) was used to measure the ATP content of LUAD cells according to the manufacturer’s instructions.
The consumption rate of extracellular glutamine was measured with high-performance liquid chromatography (HPLC) after pre-column derivation with o-phthaldialdehyde (OPA) with an analytical column (C18; 4.6 mm × 15 cm, 3 μm, Sigma) and a guard column (C18; 4.6 mm × 5 cm, 15 μm, Waters). The glutamine in the medium was separated and quantified in the chromatogram. For the glutamine uptake assay, 1 × 105 cells were seeded in 24-well plates 24 h before the experiment. Cells were incubated in medium supplemented with radiolabeled 3H-glutamine (0.1 μM) and ice-cold glutamine (50 μM) or background medium containing 3H-glutamine (0.1 μM) and glutamine (10 mM) at 37 °C, with 5% CO2 for 10 min. The cell lysates were then analyzed by liquid scintillation with a scintillation counter, and the background medium counts were subtracted. CPM values were normalized using μg of protein.
LUAD cells were cultured until 50% of confluency and then changed to a fresh culture medium. After 24 h, the supernatants were harvested and used for glucose consumption and lactate production tests. Glucose and lactate detection kits were purchased from Biovision (catalog nos. ab136955 and ab65331, respectively). All experiments were conducted according to the manufacturer’s instructions. The values were normalized using μg of protein.
An XF24 Extracellular Flux Analyzer (Seahorse Bioscience) was applied to evaluate the OCR and ECAR. Cells were seeded in 96-well plates at a density of 8 × 103 cells per well in a growth medium overnight. For OCR analysis, cells were washed and incubated with a mito stress-test base medium containing 10 mM glucose, 2 mM L-glutamine, 1 mM pyruvate. After every three measurements at 8 min intervals, 1 μM oligomycin, 3 μM FCCP, or 0.5 μM rotenone was added to the wells at the indicated time points. For ECAR analysis, cells were added with base medium with 2 mM L-glutamine and monitored every 3 min following successive administration of 10 mM glucose, 1 μM oligomycin, and 50 mM 2-deoxyglucose.
Metabolite extraction from CM was conducted according to previously reported methods [18]. Briefly, precooled methanol was added to the samples to extract the metabolites. After rotating for 1 min and incubating at −20 ℃ for 2 h, the samples were centrifuged for 20 min at 4000 rpm, the supernatant was collected, and it was transferred to autosampler vials for LC–MS analysis.
Exosomes from CAFs culture medium were isolated through standard centrifugation steps or an Exosome Precipitation Solution. Briefly, the culture medium was centrifuged at 3000 rpm for 10 min at 4 °C, followed by centrifugation at 10,000×g for 30 min at 4 °C to remove cellular debris. The supernatant was then filtered using a 0.22 μm filter. Exosomes were isolated using an Exosome Precipitation Solution (ExoQuick-TC, System Biosciences) or centrifuged at 100,000×g for 90 min. Exosomes were examined by electron microscopy and quantified using a NanoSight NS300 instrument (Malvern Instruments) equipped with NTA 3.0 analytical software (Malvern Instruments). Antibodies against CD81 (1:200), CD63 (1:200), and CD9 (1:200) were used to identify the exosomes. Exosome-packaged RNA and protein extraction was performed using a Total Exosome RNA and Protein Isolation Kit (4478545, Invitrogen). For qRT-PCR, 1.8 × 108 λ poly A+ RNA was added to the exosome suspension, and exosomal lncRNAs were normalized against exogenous λ poly A [19] (External Standard Kit, 3789, Takara). For the visualization of exosome internalization, exosomes isolated from CAFs were labeled with DiO (V22886, Invitrogen) and washed through exosome spin columns (MW3000, Invitrogen) to remove excess dye. DiO-labeled exosomes were added to Dil-labeled LUAD cells and visualized by laser scanning confocal microscopy (LSM710, Zeiss) after 24 h. Exosome-packaged RNA labeling was performed using a Click-iT RNA Imaging Kit according to the manufacturer’s instructions (C10329, Invitrogen). Briefly, CAFs were labeled with 100 μM 5-EU for 24 h, and LUAD cells were labeled with Dil for 10 min. Both cells types were then washed and co-cultured for 8 or 24 h. EU was then visualized by Alexa Fluor 488 azide (Alexa Fluor 488 5-carboxamido-(6-azidohexanyl), bis(triethylammonium salt)). For 4sU RNA transfer, 4sU (4-thiouracil)-labeled CAFs were washed, left in mono-culture for 24 h, and conditioned medium collected from 4sU-labeled CAFs was added to LUAD cells. LUAD cells were then harvested 24 h later, followed by RNA extraction. 4sU-labeled RNA was biotinylated using EZ-Link HPDP-Biotin (Thermo Fisher) for 2.5 h at room temperature. Free biotin was depleted by phenol–chloroform RNA isolation, and CAF-derived 4sU-labeled RNA was enriched with Dynabeads MyOne Streptavidin C1 magnetic beads (Thermo Fisher) following the manufacturer’s instructions. CAF-derived 4sU-enriched RNA was then eluted with 1,4-dithiothreitol (Sigma) and extracted for qRT-PCR analysis. For exosome depletion, antibodies against CD81 (1:100; Novus) and mouse IgG (1:100) were labeled with biotin using a Zenon Biotin-XX Mouse IgG2b Labeling Kit (Z25252, Molecular Probes). CAF culture medium was incubated with the biotin-labeled antibody against CD81 or IgG overnight at 4 °C, and the medium was incubated with Dynabeads MyOne Streptavidin T1 (65601, Invitrogen) for 30 min at 25 °C. The exosome-antibody complex was obtained using a magnet. GW4869, an exosome inhibitor, was also used to block exosome secretion.
The quantification of LINC01614 in fibroblasts of clinical samples was determined by co-expression analysis of LINC01614 and α-SMA positive cells. Briefly, paraffin-embedded sections were deparaffinized and incubated with anti-α-SMA antibody (1:200, CST) and then incubated with Alexa Fluor 555-conjugated secondary antibody (1:10000, A32727, Thermo Fisher). The sections were dehydrated with ethanol and rehydrated in 50% formamide and then hybridized with a 20 nM 5′-digoxigenin-labeled LINC01614 probe (Ribobio) and anti-digoxigenin-FITC. DAPI was used for counterstaining the nuclei, and images were observed with laser scanning confocal microscopy (LSM710, Zeiss). The combination of FISH and immunofluorescence experiments were used to detect the expression of LINC01614 and the interaction of proteins in CAF exosome-treated LUAD cells. Briefly, cells were fixed with 4% paraformaldehyde for 10 min at room temperature, washed with PBS, and permeabilized with 0.2% Triton-X-100 for 15 min. Cells were then blocked with goat serum for 1 h at room temperature. Thereafter, cells were incubated with primary antibodies for anti-p65 (1:200) and anti-ANXA2 (1:100) overnight at 4 °C and incubated with Alexa Fluor-conjugated secondary antibodies (Thermo Fisher) for 1 h at room temperature. The cells were then hybridized with a 5’-digoxigenin-labeled LINC01614 probe (Ribobio) and anti-digoxigenin-FITC. DAPI was used for counterstaining the nuclei, and images were captured by laser scanning confocal microscopy (LSM710, Zeiss).
Paraffin-embedded tissues were sliced at 4 μm thickness. Antigen retrieval was applied using a pressure cooker for 3 min in 0.01 M citrate buffer (pH 6.0). The sections were incubated with antibodies specific for α-SMA (1:200; CST), SLC38A2 (1:200; CST), SLC7A5 (1:200; CST), and Ki67 (1:100; CST) overnight at 4 °C, and the immunodetection was conducted on the following day with DAB. For in situ hybridization, the samples were preincubated with a hybridization solution for 2 h at 50 °C. For hybridization, an anti-LINC01614 oligodeoxynucleotide probe conjugated with DIG (Exiqon) was used. After washing, the sections were incubated with hydrogen peroxide for 15 min at room temperature and HRP-conjugated secondary antibody for 1 h at room temperature and stained with DAB, mounted, and examined. LINC01614 was abundantly expressed in fibroblasts. The staining intensity was graded using the following scale: (0) negative; (1) low positive; (2) positive; (3) high positive. The proportion of positively stained cells in slides was determined as follows: (0) no positive cells; (1) < 25%; (2) 25–50%; (3) 50–70%; and (4) > 75%. The IHC scores were calculated by multiplying the staining intensity score and percentage of positive cells.
qRT-PCR was performed using ChamQ Universal SYBR qPCR Master Mix (Q711-02/03, Vazyme) according to the manufacturer’s instructions. The primer sequences are listed in Additional file 1: Table S3. Data were collected using an Applied Biosystem Prism 7500 Fast Sequence Detection System (Applied Biosystems).
The subcellular localization of LINC01614 was determined using the PARIS Kit (Ambion, Life Technologies, Carlsbad, CA, USA) according to the manufacturer’s instructions. Briefly, cells were incubated in cell fractionation buffer on ice for 5 min. After centrifugation at 500×g for 5 min, the supernatant was collected as the cytosolic fraction. The nuclear pellet was resuspended in a cell disruption buffer and incubated at 4 °C for 30 min. The nuclear fraction was obtained after removing insoluble membrane debris by centrifugation for 10 min at 12,000×g.
Protein extracted from the cells was electrophoresed by SDS–polyacrylamide gels and was transferred to polyvinylidene difluoride (PVDF) membranes. Primary antibodies against p65 (1:1000, CST), phospho-p65 (ser 536) (1:1000, CST), phospho-p65 (ser 276) (1:1000, CST), ANXA2 (1:1000, CST), SLC38A2, SLC7A5, IKKβ, phospho-IKKβ, IKBα, phospho-IKBα, Histone 3, CD81, CD9, CD63, GAPDH, and β-actin were used. Goat anti-rabbit IgG H&L (IRDye ®800CW) preadsorbed (1:10,000, ab216773, Abcam) or Goat anti-Mouse IgG H&L (IRDye ®680RD) preadsorbed (1:10,000, ab216776, Abcam) secondary antibodies were used, and the antigen–antibody reaction was visualized using an Odyssey infrared scanner (Li-Cor, Lincoln, NE, USA).
5′-RACE, 3′-RACE, and full-length amplification of LINC01614 were conducted using a SMART RACE cDNA Amplification Kit (Clontech) according to the manufacturer’s instructions.
For siRNA transfection, cells were transfected with specific siRNA duplexes using Lipofectamine 3000 (Invitrogen) following the manufacturer’s instructions. For transduction, tumor cells incubated in 24-well plates were transduced by lentiviral particles (MOI of 10) with 5 μg mL−1 polybrene. The oligonucleotide sequences of siRNAs and shRNAs are shown in Additional file 1: Table S2.
Cells were lysed in IP lysis buffer containing protease inhibitors. The lysates were collected and centrifuged at 13,000 × g for 10 min, and the supernatants were transferred into new tubes for immunoprecipitation. For immunoprecipitation, an antibody against p65 (1:100, 8242, CST) was added to the lysates and incubation overnight at 4 °C, rabbit IgG (1:100) was used as the control. Dynabeads Protein A/G (10002D/10003D, Invitrogen) was then added to the tubes and incubation for 1 h at 4 °C. After washing with the lysis buffer, the immunocomplexes were resuspended in protein loading buffer and used for immunoblotting.
RNA immunoprecipitation was conducted using the Magna RIP RNA-Binding Protein Immunoprecipitation Kit (17-700, Millipore) following the manufacturer’s instructions. RNA pull-down assays were performed as previously described [20]. Briefly, biotin-labeled RNAs were transcribed using a MEGAscript T7 High Yield Transcription Kit (Invitrogen) in vitro. Bio-16-UTP was used for the in vitro transcription. To form proper secondary structure, 1 μg biotinylated RNA incubated in RNA structure buffer (10 mM Tris (pH 7), 0.1 M KCl, 20 mM MgCl2) was heated to 95 °C for 2 min, cooled on ice for 3 min, and incubated for 30 min at room temperature. Cell lysates were prepared by ultrasonication in RIP buffer. In vitro-transcribed and folded RNA was mixed with cell lysates at room temperature for 1 h. A total of 50 μL of washed streptavidin magnetic beads (60,210, Invitrogen) was added to the binding reaction and then incubated at 4 °C for 4 h before washing with RIP buffer five times and elution in Laemmli sample buffer. SDS-PAGE then separated the retrieved proteins for MS or western blotting.
GST-conjugated p65 (ab114150, Abcam) and His-conjugated ANXA2 (ab93005, Abcam) were used. In vitro binding assays were conducted in IP lysis buffer. GST-conjugated p65, His-conjugated ANXA2, and folded LINC01614 were incubated at room temperature for 1 h. The interaction was determined by immunoprecipitation and western blotting.
Chromatin immunoprecipitation assays were conducted using an EZ-Magna ChIP chromatin immunoprecipitation kit (17-371RF, Millipore) according to the manufacturer’s instructions. Briefly, after fixation in 1% formaldehyde for 10 min at room temperature, 5 × 106 cells were collected, lysed, and sonicated. Antibodies against p65 (5 μL mg−1 protein) and rabbit IgG (2 μL mg−1 protein) were used for immunoprecipitation. Bound DNA fragments were subjected to real-time PCR. The primer sequences used in the ChIP assays are provided in Additional file 1: Table S3.
Luciferase reporter assays were conducted according to the manufacturer’s instructions (Promega). pGL3-based constructs containing the wild-type (WT) or MUT SLC38A2 and SLC7A5 promoters together with the Renilla luciferase plasmids were transfected into cells using Lipofectamine 3000 (Invitrogen). Luciferase activity was examined 48 h after transfection by the Dual-Luciferase Reporter Assay System, and firefly luciferase activity was normalized to Renilla activity.
Suspended cells were stained with Live/Dead Fixable Viability Dye (FVD-eFluor780, 65-0863-14, eBioscience) in PBS for 20 min to distinguish the live cells from dead cells. For cell surface marker analysis, cells resuspended in PBS containing 1% GBS were stained with fluorescent-conjugated antibodies against CD326 (EpCAM), CD140b (PDGFR-β), CD45, and fibroblast-specific protein (FSP) for 30 min at 4 °C according to the manufacturer’s instructions. The following monoclonal antibodies were used: human CD140b (323605, BioLegend), human fibroblast (130-100-133, Miltenyi), human CD326 (130–111-118, Miltenyi), and human CD45 (304019, BioLegend). Samples were analyzed using a BD Accuri C6 Flow Cytometer. For gating myofibroblasts (myCAF), inflammatory CAF (iCAF) and antigen-presenting CAF (apCAF), antibodies against I-A/I-E (BioLegend, MHC class II), Ly6C (BioLegend), IL-6 (BioLegend) and α-SMA were used: FSP+MHCII+ (apCAFs), FSP+MHCII−IL6+ (iCAFs), FSP+MHCII−α-SMA+ (myCAFs).
LUAD cells were cultured with DMEM containing 10% FBS until 80% of confluency. The cells were cultured in fresh serum-free media after washing with PBS. After 24 h, the supernatants were collected and used for ELISA assay. The IL-6, CXCL10, and CCL5 ELISA kits were purchased from Fcmacs. All assays were performed according to the manufacturer’s instructions.
First, we used TCGA datasets to identify LUAD upregulated lncRNAs. RNA sequencing (RNA-Seq) data from 585 LUAD cases were downloaded from the data portal (https://portal.gdc.cancer.gov), including 56 normal lung tissue samples. The R package DESeq was used to count data [21], and 7320 differentially expressed genes were detected (fold change > 2 and FDR < 0.05) among 60,483 genes. According to the "Gene_type" annotation by the Ensembl genes database (Hg38), 649 lncRNAs were screened from differentially expressed genes as upregulated lncRNAs. Second, to reveal potential non-tumor cell-expressed lncRNAs, we considered the expression levels of all 649 upregulated lncRNAs in 57 LUAD cell lines and the normal epithelial line SALE. We performed the DESeq method between every LUAD cell line and SALE, and we found that a total of 195 lncRNAs could not be detected as highly expressed in any LUAD cell lines (P-value < 0.1). Third, to assess the association between TME compositions and non-tumor cell-expressed lncRNAs, we applied the MCP-counter tool to calculate abundance scores of TME populations [22], and we performed correlation analysis using the Pearson’s correlation coefficient.
Total RNA of fibroblasts, LUAD cells, and educated LUAD cells was extracted with TRIzol. Exosome-packaged RNA extraction was performed using Total Exosome RNA and Protein Isolation Kit (4478545, Invitrogen). For RNA sequencing, libraries were prepared from purified RNA using a NEBNext Ultra Directional RNA Library Prep Kit to ensure the RNA was not fragmented prior to library preparation. Libraries were then sequenced on Illumina HiSeq 2500 with 100 base paired-end reads. HISAT, StringTie, and Ballgown analysis were used as previously described [23]. For Ballgown, we used transcript FPKM as the transcript expression measurement, upon which we performed GSEA between experimental groups [24].
For the subcutaneous tumorigenicity assay, 4-week-old female BALB/c nude mice were purchased from Vital River Laboratories and maintained under standard conditions according to protocols approved by the Nanjing Medical Experimental Animal Care Commission (approval number: IACUC-2101034). Tumor cells (5 × 106 A549 cells) were subcutaneously injected into one flank of each mouse in 0.1 mL of sterile PBS. After the inoculation, 100 μL of PBS containing exosomes obtained from CAFs with indicated treatment (0.5 μg kg−1) was injected peritumorally every 3 d. For the co-injection mouse model, 5 × 106 A549 cells and 5 × 106 transduced CAFs were co-injected into a single flank of each mouse in 0.1 mL of sterile PBS. For the tail vein injection assay, 5 × 106 luciferase-labeled A549 cells were intravenously injected into female NCG mice (NODprkdc−/−IL-2Rg−/−) through the tail vein (GemPharmatech, Nanjing, China). Two weeks after injection, mice were randomly divided into groups and intravenously injected with an equal number of exosomes obtained from transduced CAFs once a week for 4 weeks. After another week, lung metastasis was assessed and quantified by ex vivo bioluminescent imaging using IVIS Lumina Series III (PerkinElmer, USA).
Zebrafish embryos of the transgenic strain expressing enhanced GFP with the fli1 promoter (Fli1: EGFR) [25] were incubated at 28 °C under standard experimental conditions according to protocols approved by the Nanjing Medical Experimental Animal Care Commission. At 48 hpf, Fli1:EGFR zebrafish larvae were anesthetized with 0.04 mg mL−1 tricaine (MS-222, Sigma). Anesthetized larvae were subjected to microinjection. LUAD tumor cells and CAFs were labeled with 2 μg mL−1 DiD (V-22887, Chroma) or CM-Dil (V-22888, Chroma), respectively. A total of 500 labeled LUAD cells or a mixture containing 300 LUAD cells and 200 CAFs were resuspended in DMEM, and 5 nL of the cell solution was injected into the perivitelline space (PVS) of larvae [25]. For exosome treatment, CAF-derived exosomes (5 ng) were injected into the PVS of larvae 24 h after cells implantation [26]. After injection, the larvae were immediately transferred into the aquarium water supplemented with 0.2 mmol L−1 1-pheny-2-thio-urea (P7629, Sigma). Four days after injection, the zebrafish were fixed and analyzed for tumor invasion and metastasis using laser scanning confocal microscopy (LSM710, Zeiss).
Data were analyzed with GraphPad Prism, SPSS 20 software, or R programming language. For most in vitro and animal experiments, Student’s two-tailed t-tests were used for single comparisons (paired or unpaired), and a one-way ANOVA was performed for multiple comparisons. Spearman order correlation analysis was used to determine the relationship between different factors. Survival curves were plotted using the Kaplan–Meier method and assessed using log-rank tests. All experiments were repeated independently three times. Animal studies were repeated using five to eight independent mice per group. Data are shown as the mean ± standard deviation (s.d.) unless stated otherwise. The P-value < 0.05 was considered to be statistically significant.
Given the increasing evidence supporting the cancer-promoting effects of CAFs [27], we first confirmed the contribution of CAFs in LUAD. We studied the number of activated fibroblasts identified by α-SMA immunohistochemical (IHC) staining in a tissue microarray (TMA) of LUAD (Additional file 2: Fig. S1A). α-SMA is highly overexpressed in LUAD (compared with normal lung tissue) (Additional file 2: Fig. S1B). α-SMA+ CAF density is positively correlated with the T stage (Additional file 2: Fig. S1C). High expression of α-SMA is associated with poor overall survival (HR = 2.791, 95% CI 0.1839–0.6982; P = 0.0017) (Additional file 2: Fig. S1D). Functional experiments in vitro were performed using primary CAFs and paired normal fibroblasts (NFs) derived from human LUAD samples (Additional file 2: Fig. S1E-F). We established a co-culture Transwell system in a non-interacting manner, as previously reported [11]. We found that LUAD cell lines (glutamine-sensitive A549 and glutamine-insensitive H1975, respectively) co-cultured with CAFs exhibited higher proliferation, migration, and invasion abilities (Additional file 2: Fig. S1G-I) than those cultured alone or co-cultured with NFs. To further identify the molecular mechanisms underlying CAF-mediated progression in LUAD, we performed RNA-seq analysis to compare the RNA expression profiles in A549 cells cultured alone or co-cultured with three pairs of NFs and CAFs. (LUAD01, LUAD02 and LUAD03 patients-derived CAFs and NFs were used here.) Reactome pathway analysis and gene set enrichment analysis (GSEA) for transcriptomes showed that genes involved in the metabolism of amino acids and derivatives were remarkably upregulated in A549 cells co-cultured with CAFs (Fig. 1A, B). Moreover, GESA based on KEGG pathways revealed that amino acid metabolism—primarily alanine, aspartate, and glutamine—was elevated in A549 cells co-cultured with CAFs (Additional file 2: Fig. S1J). To investigate whether CAFs contribute to the metabolism of LUAD cells, we examined changes in the mitochondrial oxygen consumption rate (OCR) and extracellular acidification rate (ECAR), measures of mitochondrial activity and glycolysis, respectively, in A549 cultured alone or co-cultured with NFs and CAFs (Fig. 1C; Additional file 2: Fig. S1K). A549 cells showed few changes in ECARs, glucose consumption, or lactate production when co-cultured with NFs or CAFs (Additional file 2: Fig. S1K-L). In contrast, LUAD cells co-cultured with CAFs exhibited higher mitochondrial OCRs (Fig. 1C) and ATP synthesis (Fig. 1D). Given the metabolic changes in A549 cells following co-culture with CAFs, we hypothesized that mediators in the supernatants might be responsible. Because exosomes play important roles in the communication between cells [28], we next performed a series of metabolomic studies to identify the differentially expressed metabolites in the conditioned media (CM) of A549 treated with indicated exosomes (Fig. 1E). Notably, we observed that glutamine was the top metabolite under-represented in the CM of A549 cells co-cultured with CAF exosomes. Because glutamine is an energy source for cancer cells, we determined the cellular uptake of 3H-glutamine in A549 cells. A549 cells co-cultured with CAFs exhibited higher glutamine uptake than those cultured alone or co-cultured with NFs. Additionally, A549 cells co-cultured with CAFs had a higher content of TCA cycle intermediates (Additional file 2: Fig. S1M). Similarly, we observed enhanced glutamine consumption rate and ATP production in H1975 cells co-cultured with CAFs (Additional file 2: Fig. S1N). These data suggest that CAFs increase the uptake and utilization of glutamine in LUAD cells in vitro in a non-interacting manner. Next, we determined whether CAF-derived exosomes mediated the uptake of glutamine and the progression of LUAD cells. Exosomes in CAFs CM were isolated by ultracentrifugation. The morphology, diameter, and biomarkers of the exosomes were confirmed by electron microscopy, NanoSight analysis, and western blotting (Additional file 2: Fig. S2A-D), respectively. The internalization of CAF-derived exosome cargo by the tumor cells was visualized by confocal microscopy (Additional file 2: Fig. S2E). CAF-derived exosomes remarkably enhanced the mitochondrial OCR, glutamine consumption rate, glutamine influx, ATP synthesis, and abundance of TCA intermediates derived from glutamine catabolism (Fig. 1F–J; Additional file 2: Fig. S2F-G), and the proliferation, migration, and invasion of LUAD cells (Fig. 1K; Additional file 2: Fig. S2H). More importantly, depleting exosomes from CAFs CM using an anti-CD81 antibody significantly inhibited their roles in promoting glutamine metabolism and proliferation, migration, and invasion of LUAD cells (Fig. 1F–K; Additional file 2: Fig. S2F-H). Collectively, these results demonstrated that CAF-derived exosomes enhanced glutamine influx and promoted the progression of LUAD cells. Recent studies have shown that exosomal RNAs are critical in the cellular communication between tumor cells and the TME [11]. We next investigated whether CAF-derived exosomal RNAs mediated the enhancement of glutamine influx and LUAD progression. We observed that pretreated exosomes with RNase and Triton-X-100 abolished the effects of CAFs on LUAD cells (Fig. 1L–N). These data further confirmed that exosome-packaged RNAs from CAFs at least partially contribute to enhancing glutamine metabolism in LUAD.
lncRNAs have recently exhibited cell lineage- and developmental stage-dependent expression patterns [29]. Lineage-specific and cell-specific expressed lncRNAs control lineage-specific regulatory programs and regulate pathophysiological processes, including cancer [11, 29, 30]. To determine whether CAF-specific lncRNAs mediate the glutamine addiction of LUAD cells, we screened CAF-specific lncRNAs based on the NJLCC cohort (https://ega-archive.org/datasets/EGAD00001004071), who were recruited in Jiangsu Cancer Hospital. A total of 149 patients with non-small cell lung cancer were enrolled, and we examined TCGA data and their presence in exosomes. To screen CAF-associated lncRNAs, we first performed an analysis to identify overexpressed lncRNAs in LUAD tissues based on TCGA LUAD datasets. A total of 649 lncRNAs were upregulated in LUAD tissues (Fig. 2A; Additional file 2: Fig. S3A). To reveal potential non-tumor cell-expressed lncRNAs, we analyzed the expression levels of the 649 upregulated lncRNAs in 57 lung LUAD cell lines and the normal epithelial line SALE based on the Cancer Cell Line Encyclopedia (CCLE) database. Interestingly, 195 lncRNAs were not highly expressed in any LUAD cell lines, and they were identified as the TME-associated lncRNAs (Additional file 2: Fig. S3B). Furthermore, we performed correlation analysis to determine the correlation of the 195 lncRNAs with TME populations based on the NJLCC cohort and TCGA LUAD datasets. Among the 195 TME-associated lncRNAs, 20 lncRNAs were highly positively correlated with 20 types of LUAD stromal cells, including two highly positively CAFs-associated lncRNAs (LINC01614 (ENSG000000230838) and ENSG00000261327) (Fig. 2B). TCGA data showed that LINC01614 and ENSG00000261327 were highly upregulated in several cancers, including LUAD (Additional file 2: Fig. S3C). Moreover, the Genotype-Tissue Expression (GTEx) dataset showed that LINC01614 was specifically expressed in cell-cultured fibroblasts, whereas ENSG00000261327 was relatively upregulated in cell-cultured fibroblasts, (Additional file 2: Fig. S3D-E). Quantitative reverse transcription PCR (qRT-PCR) confirmed that LINC01614 rather than ENSG00000261327 was highly expressed in CAFs compared with LUAD cell lines, MRC5 cells (human embryonic lung fibroblasts), and paired NFs (Fig. 2C). Moreover, we isolated CAFs from LUAD tissues by fluorescence-activated cell sorting (FACS), and LINC01614—rather than ENSG00000261327—was primarily expressed in CAFs and not in non-CAF cells (Fig. 2D). Given that CAF exosomal RNA enhanced glutamine influx and the progression of LUAD, we investigated whether LINC01614 could be released from CAFs by exosomes. The expression of LINC01614 in CAF CM was unchanged upon RNase treatment but significantly decreased when simultaneously incubated with RNase and Triton-X-100 (Fig. 2E), suggesting that LINC01614 could be released from CAFs and the extracellular LINC01614 was primarily wrapped by membranes instead of being directly released. Furthermore, LINC01614 was increased more than fivefold in the exosomes from CAFs compared to NFs and by more than threefold in A549 cells co-cultured with CAF-derived exosomes (Fig. 2F). qRT-PCR results showed that LINC01614 was highly expressed in myofibroblasts (myCAF) as compared to inflammatory CAF (iCAF) and antigen-presenting CAF (apCAF). We proposed myCAF subpopulation was the main source of LINC01614-containing exosomes (Additional file 2: Fig. S3F). To confirm whether the increase in LINC01614 in CAF co-cultured A549 cells was caused by exosome transmission, we knocked down LINC01614 and RAB27, a key enzyme for exosome secretion in CAFs before co-culture, to abolish LINC01614 release and exosome secretion, respectively (Fig. 2G). Inhibition of exosome secretion also inhibited the upregulation of LINC01614 in A549 cells co-cultured with CAFs (Fig. 2G). Importantly, silencing LINC01614 in CAFs decreased the LINC01614 level in CAF exosomes, while overexpressing LINC01614 increased the LINC01614 level in CAF exosomes (Fig. 2G; Additional file 2: Fig. S3G). However, LINC01614 did not impact the general production of exosomes from CAFs (Additional file 2: Fig. S3H-I). Moreover, fluorescence in situ hybridization (FISH) and immunofluorescence (IF) analysis showed that LINC01614 was abundantly expressed in CAFs, and its expression was positively associated with the density of CAF infiltration as determined by α-SMA IF staining of LUAD tissues (Fig. 2H). To further confirm whether CAF-derived LINC01614 accompanies exosomes transfer, we metabolically labeled CAF RNA with 5-ethynyl uridine (EU) prior to co-culture with fluorescently labeled A549 cells. After 24 h, A549 cells significantly acquired CAF RNA as assessed by EU-modification with azide-linked fluorescein (Fig. 2I). Moreover, when CAFs were similarly labeled with 4-thiouridine (4sU), treatment with CAF CM led to LINC01614 transfer from CAFs to A549 cells, which was examined by a streptavidin pull-down of biotinylated 4sU-labeled CAF RNA. In contrast, LINC01614 failed to transfer to A549 cells when exosomes were depleted from the CM using the exosome inhibitor GW4869 (Fig. 2J), consistent with our findings LINC01614 transmission is exosome-dependent. Together, these data indicated that a CAF-specific lncRNA-LINC01614 could be released and transmitted from CAFs to LUAD cells by exosomes.
Either silencing LINC01614 with shLINC01614 in CAFs or inhibiting exosome secretion by knocking down RAB27 abrogated the CAF-induced glutamine influx and utilization in LUAD cells (Fig. 3A, B; Additional file 2: Fig. S4A-B). Ectopic LINC01614 expression enhanced glutamine utilization in LUAD cells (Fig. 3C, D; Additional file 2: Fig. S4C-D). When treating LUAD cells, exosomes from LINC01614-silencing CAFs suppressed the enhanced proliferation, migration, and invasion, whereas the exosomes from CAFs ectopically expressing LINC01614 promoted those abilities (Fig. 3E, F; Additional file 2: Fig. S4E-F). Moreover, ectopically expressing LINC01614 also remarkably promoted the malignant behavior of LUAD cells (Fig. 3G, H; Additional file 2: Fig. S4G-H). Next, we investigated whether LINC01614-related effect on LUAD cells progression is linked to specific glutamine-addiction of cancer cells. Our results showed that both A549 and H1975 cells were increasingly addicted to glutamine as supplemented glutamine concentration increased. And ectopic LINC01614 expression enhanced the proliferation, migration and invasion behaviors of LUAD cells, however failed to enhance the malignant behaviors of LUAD cells when glutamine was deprived (Fig. 3I–K; Additional file 2: Fig. S4I-K). Moreover, CAFs showed no difference in glutamine uptake with LINC01614 overexpression or knockdown (Additional file 2: Fig. S4L). With respect to the proliferation of CAF, we found that only LINC01614 overexpression slightly enhanced CAF proliferation, while silencing LINC01614 had no effects (Additional file 2: Fig. S4M). These data suggested that modulating LINC01614 in CAFs did not impact the glutamine uptake of CAFs, while slightly affected the CAF growth. Collectively, these data further confirmed that LINC01614 facilitated LUAD cells specifically addicted to glutamine for malignant progression. Subsequently, we hypothesized that amino acid transporters could contribute to LINC01614-mediated glutamine influx. Solute carrier families are important transporters for glutamine [31]. Therefore, we examined the transcriptional profiling of previously identified glutamine transporters in A549 cells by qRT-PCR. Only SLC38A2 and SLC7A5 were upregulated in A549 cells at mRNA and protein levels when treated with CAF exosomes. Silencing LINC01614 attenuated SLC38A2 and SLC7A5, whereas overexpressing LINC01614 enhanced their expressions in A549 cells treated with CAF exosomes (Fig. 3L, M). Moreover, ectopic LINC01614 expression in A549 cells enhanced the expressions of SLC38A2 and SLC7A5 (Fig. 3N). More importantly, both silencing SLC38A2 and SLC7A5 in A549 cells partially reversed enhanced glutamine uptake and utilization and the proliferation, migration, and invasion of ectopic LINC01614 expression in A549 cells (Additional file 2: Fig. S4N-S). Collectively, these data demonstrated that CAFs enhanced glutamine influx and utilization and the malignant behaviors of LUAD cells by transmitting a CAF-specific lncRNA-LINC01614 via exosomes.
To address how LINC01614 promotes glutamine uptake, we first performed nuclear mass separation and FISH assays in CAFs. Our results showed that LINC01614 was mainly distributed in the CAF cytoplasm (Additional file 2: Fig. S5A-C), consistent with the supposition that CAF-derived exosomes could package LINC01614. Next, we used an RNA pull-down in vitro-transcribed LINC01614 RNA with a biotin-labeled 3ʹ end in A549 cells and analyzed the protein products with mass spectrometry (MS). The p65 (Rela) and Annexin A2 (ANXA2) were associated with LINC01614 (Additional file 2: Fig. S5D-E). This was confirmed by immunoblotting and RNA immunoprecipitation (RIP) assays (Fig. 4A–C). Moreover, LINC01614 along with ANXA2 could be co-immunoprecipitated with p65 (Fig. 4D), suggesting that LINC0164, ANXA2, and p65 could form a ternary complex. To confirm this, we used an ex vivo system with recombinant proteins (p65 and ANXA2) and in vitro-transcribed LINC01614 as previously described [11]. The addition of LINC01614, but not antisense lncRNA, effectively enhanced the interaction between p65 and ANXA2 (Fig. 4E). To further investigate the segments of LINC01614 that associate with p65 and ANXA2, we generated a series of truncated versions of LINC01614. Nucleotides 973–1775 of LINC01614 interacted with p65 and ANXA2 (Fig. 4F). Moreover, a nucleotide mutation lacking the stem-loop structure of LINC01614 (973–1775) attenuated the LINC01614-enhanced interaction between p65 and ANXA2 (Fig. 4G). More importantly, the introduction of LINC01614973–1775 into the incubation system containing recombinant p65 and ANXA2 effectively enhanced their interaction (Fig. 4H). To unravel the mechanisms involved in LINC01614-mediated glutamine influx, we performed GSEA for the mRNA microarray data of A549 cells treated with CAF exosomes. A panel of nuclear factor kappa B (NF-κB) target genes were significantly co-expressed with LINC01614 in CAF-exosome-treated A549 cells, including IL-6, CCL5, and CXCL10 (Fig. 4I), which was further verified by qPCR and ELISA both in CAF-exosome-treated A549 and ectopic LINC01614 expression A549 cells (Additional file 2: Fig. S5F-G). Similarly, upregulated NF-κB transcription activities and increased p65 nuclear translocation were observed in A549 cells treated with CAF exosomes, whereas knocking down LINC01614 in CAFs failed to active NF-κB transcription and p65 nuclear translocation (Fig. 4J–L). Moreover, ectopic expression of LINC01614 increased NF-κB transcription activities and p65 nuclear translocation in A549 cells (Fig. 4M–O). Together, these results indicated that CAF-derived LINC01614 enhanced p65 and ANXA2 interaction and promoted NF-κB activation.
To study the mechanisms by which LINC01614 activates the NF-κB pathway, we assessed the effect of LINC01614 on the phosphorylation of IκBα and IκB kinase (IKK). However, phosphorylation of IKK and IκBα was not influenced in A549 cells by ectopic LINC01614 expression or treated with CAF exosomes (Fig. 5A, B). Consistently, either inhibiting NF-κB nuclear translocation (JSH-23) or silencing p65, but not inhibiting IKK (BAY 11-7082), could abolish the effects of LINC01614 on p65 nuclear translocation (Fig. 5C). Moreover, silencing p65 also abolished the production of IL-6, CCL5, and CXCL10 (Additional file 2: Fig. S6A), suggesting that p65 nuclear retention was independent of upstream IKK or IκB activities. Because the phosphorylation of IKK and IκBα retained at low levels following LINC01614 treatment, we speculated that the p65 nuclear retention was independent of upstream IKK or IκBα activities. To further explore the mechanisms responsible for NF-κB activation in tumor cells, we detected the phosphorylation of p65, which was previously reported to maintain p65 nuclear retention [32]. Western blotting showed that CAF-derived exosomes enhanced p65 phosphorylation at the Ser276 residue, but not at the Ser536 residue in A549 cells. However, exosomes extracted from sh-LINC01614 transduced CAFs attenuated the enhancement of p65 phosphorylation at Ser276 (Fig. 5D). Moreover, LINC01614 or ANXA2 overexpression in A549 cells significantly enhanced p65 phosphorylation at Ser276 (Fig. 5E). ANXA2 was previously reported to mediate the phosphorylation-related activation of p65 NF-κB [33, 34]. Therefore, we determined whether LINC01614-induced p65 phosphorylation depended on ANXA2. As revealed by western blotting, immunofluorescent staining, and luciferase reporter assays, silencing ANXA2 attenuated LINC01614-induced p65 phosphorylation at Ser276, nuclear retention of p65, and NF-κB activation in A549 cells (Fig. 5F–H). Interestingly, silencing p65 reduced the expressions of SLC38A2 and SLC7A5 in A549 cells (Fig. 5I). We next assessed whether NF-κB activation promoted the transcription of SCL38A2 and SLC7A5. Sequence analysis by JASPAR suggested canonical binding motifs for NF-κB at the promoters of both SCL38A2 and SLC7A5 (Fig. 5J). Importantly, the NF-κB binding sites at the promoters of SLC38A2 and SLC7A5 were confirmed, respectively, by immunoprecipitation (ChIP) analysis with the anti-p65 antibody and the luciferase reporter assay (Fig. 5K, L). Moreover, encoded ChIP-sequencing data confirmed the peaks of p65 at the promoters of SLC38A2 and SLC7A5 in the genomic positions as revealed by our ChIP-PCR analysis (Fig. 5M). Furthermore, inhibiting NF-κB nuclear translocation (JSH-23), but not inhibiting IKK (BAY 11-7082), could abolish the effects of LINC01614 on the expression of SLC38A2 and SLC7A5 (Additional file 2: Fig. S6B). Silencing ANXA2 in A549 cells attenuated LINC01614-induced SLC38A2 and SLC7A5 upregulation (Additional file 2: Fig. S6C-D) and partially reversed the enhanced oxidative phosphorylation and glutamine influx capacity of ectopic LINC01614 expression in A549 cells (Additional file 2: Fig. S6E-F). These data suggest that CAF-derived LINC01614 interacts with p65 and ANXA2 and promotes ANXA2-induced phosphorylation of p65 at Ser276, leading to NF-κB activation of the transcription of two glutamine transporters, SLC38A2 and SLC7A5, in LUAD cells.
We performed serial experiments to further investigate the upstream mechanisms by which LINC01614 is upregulated in CAFs. We determined the expression of LINC01614 in CAFs of different cell generations and found that the expression of LINC01614 in CAFs gradually decreased with culture generations (Additional file 2: Fig. S7A). However, the expression of LINC01614 in CAFs increased with time when co-cultured with A549 cells. Interestingly, A549 cells failed to upregulate LINC01614 expression in CAFs when silencing LINC01614 or inhibiting CAF exosome secretion (Additional file 2: Fig. S7B), suggesting the transmission of LINC01614 from CAFs to cancer cells may form regulatory positive feedforward loops for LINC01614 upregulation in CAFs. Because the production of NF-κB target genes IL-6, CCL5, and CXCL10 in A549 cells were upregulated by CAF-derived LINC01614, we evaluated whether IL-6, CCL5, or CXCL10 increased LINC01614 expression. We observed that treating A549 CM with neutralizing antibodies against IL-6 and CXCL10, but not against CCL5, strongly abrogated LINC01614 upregulation in CAFs (Additional file 2: Fig. S7C). Moreover, CM from LINC01614 overexpressed A549 cells upregulated the expression of LINC01614 in CAFs (Additional file 2: Fig. S7C). Furthermore, recombinant IL-6 and CXCL10 were sufficient to induce LINC01614 overexpression in CAFs (Additional file 2: Fig. S7D). These results suggest that IL-6 and CXCL10 produced by LUAD cells induce LINC01614 upregulation in CAFs. Given the specific cellular origin for LINC01614, we hypothesized that IL-6 and CXCL10 induced fibroblast lineage-specific factors that could be responsible for LINC01614 transcription in CAFs, which warrants further study. To investigate the potential competition relationship between CAFs and LUAD cells, we assessed glutamate and glutaminase content in CAFs. As shown in Additional file 2: Fig. S4L and Additional file 2: Fig. S7E, neither silencing/overexpressing LINC01614 nor IL-6 treatment had no effect on the glutamine uptake of CAFs. These results suggest that LINC01614 upregulating in CAFs did not result in increased glutamine uptake and potential ‘competition’ with LUAD cells.
To investigate the tumor-promoting roles of exosome-packaged LINC01614 in vivo, we inoculated A549 cells with or without a co-injection of CAFs into the single flank of nude mice. The xenograft tumor models showed that an intratumor injection of CAF exosomes or co-injection of CAFs promoted lung cancer growth (Fig. 6A–D, Additional file 2: Fig. S8A-D). IHC staining revealed that xenografts from the mice with the exosome injection exhibited more Ki67 and SLC38A2- and SLC7A5- positive cells. Conversely, exosomes from sh-LINC01614 transduced CAFs inhibited tumor growth in the xenografts, accompanied by a reduced expression of Ki67, SLC38A2, and SLC7A5 (Fig. 6E). Moreover, CAF exosome treatment promoted lung metastasis of LUAD cells in NCG (NODprkdc−/− IL-2Rg−/−) mice, which was partially reversed by silencing LINC01614 in CAFs (Fig. 6F). In addition, we used zebrafish tumor models to study tumor growth and metastasis, particularly to decipher the initial steps of the metastatic cascade regulated by exosome-packaged LINC01614. Co-implantation of LUAD cells with CAFs or CAF-derived exosomes sharply enhanced the number of proliferative and metastatic cancer cells. Interestingly, CAFs also exhibited “metastatic” capacity in the zebrafish body (Fig. 6G–J; Additional file 2: Fig. S8E-F). However, silencing LINC01614 in CAFs before co-injection or exosome extraction attenuated the number of metastatic cancer cells and CAFs (Fig. 6G–J; Additional file 2: Fig. S8E-F).
To determine whether our findings were clinically relevant, we analyzed the correlation of LINC01614 expression with CAF infiltration, as revealed by immunostaining for α-SMA in a TMA containing 78 pairs of LUAD and adjacent normal tissues. We observed that LINC01614 was abundantly expressed in CAFs. More importantly, 37 of 78 (47.4%) LUAD patients with abundant CAF infiltration exhibited enhanced hybridization signals of LINC01614 in the tumor cells (Fig. 7A). Moreover, CISH scores of LINC01614 in tumors were positively associated with the density of CAFs (Fig. 7B). High LINC01614 expression was correlated with tumor size, histological grading, and staging (Fig. 7C, D). Kaplan–Meier survival analysis revealed that high expression of LINC01614 was associated with poor overall survival of patients with LUAD (Fig. 7E). The Cox proportional hazards model indicated that LINC01614 was an independent prognostic factor for LUAD (Fig. 7F). Furthermore, we correlated LINC01614 expression with tumor glutamine transporters, as detected by immunostaining for SLC38A2 and SLC7A5 and CAF infiltration as denoted by α-SMA immunostaining in 10 cases of patients with LUAD. Consistently, LINC01614 was abundant in CAFs, and LINC01614 expression of tumor cells was positively correlated with the density of α-SMA+ CAFs and the expression of SLC38A2 and SLC7A5 in tumors (Fig. 7G). In addition, the levels of LINC01614 in primary CAFs positively associated with the mRNA levels of SLC38A2 and SLC7A5 in the paired LUAD tumor cells (Fig. 7H, I). Altogether, these clinical data are consistent with the experimental finding that LINC01614 is transmitted from CAFs to LUAD cells, thereby enhancing the glutamine uptake in LUAD. Next, we determined the correlation of LINC01614 expression with the clinicopathological status of patients with LUAD from TCGA dataset and Jiangsu Cancer Hospital (JSCH) cohort. LINC01614 was significantly upregulated in LUAD tissues in TCGA dataset and JSCH cohort. High LINC01614 expression in LUAD tissues was correlated with histological staging and lymph node metastasis. Furthermore, high expression of LINC01614 was associated with poor prognosis of patients with LUAD in TCGA cohort (Additional file 2: Fig. S9A-G). These results suggest that LINC01614 could be a potential biomarker and therapeutic target for LUAD.
Metabolic reprogramming allows cancer cells to maintain proliferation and overcome metabolic challenges related to oxygen and nutrient limitations [35]. Metabolic reprogramming of cancer cells has long been studied in regard to how cancer cells utilize glucose via aerobic glycolysis. Recently, cancer cells have been shown to utilize glutamine and other nutrient sources for survival [3], with some cancer cells even preferring the “addicting” glutamine over glucose [4]. However, how and why cancer cells preferentially utilize specific addicting nutrients remains unknown. In this study, we identified a CAF-specific lncRNA-LINC01614 that facilitates cancer cell addiction to glutamine in LUAD. Mechanistically, LINC01614 can be released and transmitted by exosomes to LUAD cells, enhancing glutamine uptake and the progression of LUAD cells. LINC01614 can induce NF-κB activation via p65 phosphorylation of LUAD cells, promoting the secretion of IL-6 from LUAD to upregulate LINC01614 in CAFs, constituting a feedforward loop between CAFs and LUAD cells. CAFs are one of the most abundant stromal components in the TME. An increasing number of studies have shown that CAFs play important roles in cancer pathogenesis, which has prominent clinical implications [6, 36]. Recent studies demonstrated that CAFs participate in TME metabolic remodeling through exosomes [37] and amino acid secretion [38, 39]. Here, we found that CAFs produce exosomes to transmit lncRNA and facilitate LUAD cells addiction to glutamine. More importantly, LINC01614 was selectively expressed in CAFs. LncRNAs are notably shown to exhibit cell lineage- and developmental stage-dependent expression patterns. Several cell lineage-specific lncRNAs were identified [30], and some controlled lineage-specific regulatory programs and regulated pathophysiological processes [11, 30, 40, 41]. Two of the latest studies demonstrated that IRENA and HISLA are specifically expressed in tumor-associated macrophages (TAMs) in breast cancer [11, 41]. However, LINC01614 has been reported as an oncogene and biomarker in several cancers, including gastric cancer [42], esophageal squamous cell carcinoma [43], breast cancer [44], and LUAD [45]. The specificity and spatial cellular expression patterns of LINC01614 were not addressed in these studies. Liu et al. mentioned that LINC01614 was upregulated in LUAD cells, whereas their results showed that LINC01614 was only upregulated by 1.7-fold in LUAD cells (H1395 and H1975) compared with human normal bronchial epithelium cells (BEAS-2B) [45]. However, our data showed that LINC01614 was significantly upregulated in CAFs (up to tenfold) but not in LUAD cell lines or other primary TME cells. We further confirmed the spatial cellular expression of LINC01614 by FISH staining and flow cytometry. Our data extended the understanding of this emerging field by demonstrating a CAF-specific lncRNA LINC01614 could be encapsulated in exosomes and shuttled from CAFs to drive the preferential uptake of glutamine over glucose in LUAD cells. Exosomes contain abundant noncoding RNAs, including microRNAs, lncRNAs, and ribosomal RNAs [28]. Several studies suggested that exosomal lncRNAs were involved in chemoresistance [19], metastasis [46], and glycolysis [11] in various cancers. We demonstrated that LINC01614 is released via exosomes from CAFs to LUAD cells. Mechanistically, LINC01614 directly interacts with ANXA2 and p65 in LUAD cells, for which LINC01614 serves as a scaffold to facilitate the phosphorylation and activation of NF-κB. Notably, NF-κB activation is not a result of IKK and IκB phosphorylation. Rather it relies on the post-translational modification of p65. ANXA2 was reported to promote p65 phosphorylation and NF-κB activation [33]. Here, we found that LINC01614 enhanced the interaction between p65 and ANXA2, and the LINC01614-induced p65 phosphorylation was ANXA2 dependent. We speculated that ANXA2 could lead to a conformational change in p65, enhancing its phosphorylation. Our study showed that exosomal lncRNA could mediate metabolic reprogramming between stromal and cancer cells. Moreover, primary tumor-released exosomes could circulate to distant organs to establish a premetastatic niche [47, 48]. In this scenario, CAF-produced exosomes may fuel metastasis and colonization of cancer cells to a distal metastatic niche, which warrants additional studies. Metabolic reprogramming of cancer cells could be exploited as a therapeutic target [49]. Our study demonstrated that targeting CAF-specific LINC01614 inhibits glutamine uptake and the progression of LUAD cells, highlighting that CAF-specific lncRNAs could serve as an attractive target in cancer treatment. Although small-molecule inhibitors that suppress glutamine transporters and glutaminase have exhibited synergistic effects with multiple anti-cancer agents in murine models [50–52], because of the intrinsic metabolic heterogeneity and flexibility within the TME, these efforts have met with limited success in the clinical setting [52–54]. Our data suggest that molecular therapy targeting LINC01614 could provide a more specific and feasible approach to inhibit glutamine metabolism in LUAD cells. Recent studies have shown that peptide-, lipid-, and nanoparticle-based siRNA delivery systems could be exploited to improve tumor targeting and safety [43, 44], providing promising opportunities to explore lncRNAs as therapeutic targets. The strategy of choosing a precise delivery system to mediate specific LINC01614 knockdown in CAFs for cancer treatment warrants further study. In summary, this study revealed that CAFs preferentially promote the addiction of cancer cells to glutamine via upregulation of amino acid transporters in LUAD. The CAF-specific lncRNA LINC01614 determines the effect of metabolic reprogramming and is an example of how an exosome-transmitted lncRNA promotes the activation of NF-κB signaling and forms a feedforward loop between CAFs and LUAD cells. Notably, our study has highlighted the therapeutic potential of targeting a CAF-specific lncRNA to inhibit glutamine utilization and reverse tumor-promoting activities of LUAD.
Additional file 1. Supplementary Tables.Additional file 2. Supplementary Figures. | true | true | true |
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PMC9548295 | Long Non-Coding RNA EGOT Promotes the Malignant Phenotypes of Hepatocellular Carcinoma Cells and Increases the Expression of HMGA2 via Down-Regulating miR-33a-5p [Retraction] Wu et al | 05-10-2022 | Long Non-Coding RNA EGOT Promotes the Malignant Phenotypes of Hepatocellular Carcinoma Cells and Increases the Expression of HMGA2 via Down-Regulating miR-33a-5p [Retraction] Wu et al
Wu S, Ai H, Zhang K, Yun H, Xie F. Onco Targets Ther. 2019;12:11623‒11635. The Editor and Publisher of OncoTargets and Therapy wish to retract the published article. Concerns were raised regarding the alleged duplication of images in Figures 2, 3 and 6. Specifically, Figure 2E, si-RNA-NC appears to have been duplicated with the same image for Figure 6G, EGOT/miR-33a-5p which has been rotated. Figure 2E, siRNA-EGOT-1 appears to have been duplicated with the same image for Figure 3F, EGOT which has been rotated. Figure 2F, si-RNA-NC appears to have been duplicated with the same image for Figure 3E, lncRNA-NC which has been rotated. Figure 2F, si-RNA-NC appears to have been duplicated with the same image for Figure 6G, NC which has been rotated. Figure 2F, siRNA-EGOT-1 appears to have been duplicated with the same image for Figure 3F, lncRNA-NC. Figure 2F, siRNA-EGOT-1 appears to have been duplicated with the same image for Figure 6H, EGOT/miR-33a-5p which has been rotated. Figure 3E, lncRNA-NC appears to have been duplicated with the same image for Figure 6G, NC which has been rotated. Figure 3F, lncRNA-NC appears to have been duplicated with the same image for Figure 6H, EGOT/miR-33a-5p. The authors did not respond to our queries and the Editor requested to retract the article and the authors were notified of this. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”. | true | true | true |
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PMC9548572 | 36226049 | Sha-Sha Wang,Fang Wang,Zhen Zeng,Fang Gao,Huan-Huan Liu,Hui-Na Wang,Yi Hu,Hai-Feng Qin | Case Report: A novel intergenic MIR4299/MIR8070-RET fusion with RET amplification and clinical response to pralsetinib in a lung adenocarcinoma patient | 26-09-2022 | RET intergenic fusion,pralsetinib,lung adenocarcinoma,novel intergenic,tyrosine kinase inhibitors | The identification of receptor-tyrosine kinase gene (RET) fusions in lung cancer has become crucial owing to actionable events that predict responsiveness to tyrosine kinase inhibitors (TKIs). However, RET fusions with distinct partner genes respond differently to TKIs. In this case, a 60-year-old man was diagnosed with advanced lung adenocarcinoma. A novel RET-MIR4299/MIR8070 fusion and RET amplification were identified using next-generation sequencing (NGS). The patient was then administered with pralsetinib. After 3 weeks of therapy, the patient had a partial response. At the time of reporting, the patient was on continuous pralsetinib. These findings broaden the range of RET fusion types and provide the basis for the hypothesis that RET intergenic fusion and amplification respond to pralsetinib treatment in lung adenocarcinoma. | Case Report: A novel intergenic MIR4299/MIR8070-RET fusion with RET amplification and clinical response to pralsetinib in a lung adenocarcinoma patient
The identification of receptor-tyrosine kinase gene (RET) fusions in lung cancer has become crucial owing to actionable events that predict responsiveness to tyrosine kinase inhibitors (TKIs). However, RET fusions with distinct partner genes respond differently to TKIs. In this case, a 60-year-old man was diagnosed with advanced lung adenocarcinoma. A novel RET-MIR4299/MIR8070 fusion and RET amplification were identified using next-generation sequencing (NGS). The patient was then administered with pralsetinib. After 3 weeks of therapy, the patient had a partial response. At the time of reporting, the patient was on continuous pralsetinib. These findings broaden the range of RET fusion types and provide the basis for the hypothesis that RET intergenic fusion and amplification respond to pralsetinib treatment in lung adenocarcinoma.
Receptor-tyrosine kinase gene (RET) fusion occurs in 1.4% of non-small cell lung cancer (NSCLC) and 1.7% of lung adenocarcinoma (1) in China. Patients harboring RET fusions have improved outcomes with the advent of RET inhibitors. It has been reported that the distinct type of RET fusion partner has a different response to the tyrosine kinase inhibitor (TKI) (2). The most common fusion partners of RET described are KIF5B and CCDC6 (3). In a recent study, 137 Chinese lung cancer patients with RET fusion were found, and most common partner genes were KIF5B (62%) and CCDC6 (21%), with the novel RET fusions accounting for 12.4% (4). It is necessary to investigate RET fusion partners and their qualifications for RET-based targeted therapy. Pralsetinib is a selective TKI with anticancer activity (5). However, the response of pralsetinib to novel RET fusions remains unknown. Here, we report a patient with lung adenocarcinoma who harbored a novel MIR4299/MIR8070-RET fusion with RET amplification and responded to pralsetinib.
A 60-year-old male nonsmoker was admitted with nausea, fatigue, and mulligrubs after meal. Nodules of liver were detected by ultrasonography. Computed tomography (CT) scan revealed two space-occupying lesions in the lower lobe of the right lung and diffuse hepatic metastases ( Figures 1A, G ). The pathological diagnosis was stage IV lung adenocarcinoma. The circulating tumor DNA (ctDNA) of the patient was analyzed using next-generation sequencing (NGS) to detect 808 tumor-associated genes (supplementary file), including all clinically relevant biomarkers for NSCLC. NGS identified a novel MIR4299/MIR8070-RET fusion with RET amplification. The abundance of fusion was 51.49%, and the copy number variation (CNV) number was 19.6 ( Figures 2A, B and Table 1 ). Fluorescence in situ hybridization (FISH) further confirmed the RET fusion and amplification ( Figure 2C ). The fusion encompassed MIR4299/MIR8070 intergenic region and exons 3 to 20 of RET, holding the whole RET kinase domain, which has never been reported before. RT-PCR was not performed since the tumor tissues were immersed in formalin, which caused serious degradation of RNA, but this degradation did not affect FISH results (6–8). NGS and immunohistochemistry (IHC) assay showed that TMB was 13.08 mut/Mb, and programmed death-ligand 1 (PD-L1) expression was less than 1%. He was subsequently treated with pralsetinib (400 mg orally once daily). After a month, the CT findings showed shrinkage of the lung lesions by 36.11% and 37.5% ( Figures 1A, B, D, E ) and reduction of the liver lesions by 18.68% ( Figures 1G, H ). Meanwhile, the levels of carcino-embryonic antigen (CEA) (from 23,385 to 8,664 ng/ml), progastrin-releasing peptide (from 41,206 to 7,482 pg/ml), and tissue polypeptide specific antigen (from 4,500 to 141.9 U/L) were markedly reduced. Therefore, he was considered to achieve a partial response (PR) according to RECIST 1.1 criteria and continued to receive pralsetinib (400 mg orally once daily). One month later, the decreases in tumor size of 13.04% and 6.7% in lung as well as 21.62% in liver were shown on CT ( Figures 1C, F, I ). At the time of reporting, the patient was still undergoing pralsetinib treatment.
As the technology for ctDNA has advanced, NGS detection of fusion using ctDNA has become feasible (9, 10). NGS displays greater strengths in identifying a fusion variant than IHC or FISH since it provides specific partner genes and fusion breakpoints. As a result of NGS and FISH analysis, we confirmed that the patient harbored a novel RET intergenic-breakpoint MIR4299/MIR8070 fusion (abundance of 51.49%), as well as coexisting RET amplification (CNV number of 19.6) and responded to pralsetinib treatment. To our knowledge, this is the first case harboring a novel RET intergenic-breakpoint MIR4299/MIR8070 fusion with coexisting RET amplification and responding to pralsetinib treatment. Pralsetinib is a selective tyrosine kinase inhibitor (TKI) approved for the treatment of NSCLC with RET fusion and the overall response rate (ORR) is 61% regardless of RET fusion partner (11). In the treatment of NSCLC, RET-target therapy has shown exceptional results. Noteworthily, distinct RET fusion variants’ reactions to TKIs were observed to be heterogeneous. Sun et al. found that a new MYH9-RET fusion developed resistance to simertinib therapy (12). In contrast, Montrone and colleagues reported that a patient with advanced lung adenocarcinoma with RET fusion was treated with pralsetinib and had an outstanding clinical and radiological response as well as good tolerability (13), which is similar with our patient. RET amplification showed similar response when treated with vandetanib and placebo in a phase III NSCLC clinical trial (14). However, Paratala et al. reported that RET amplification can induce transformation of non-tumorigenic cells, support xenograft tumor formation, and render sensitivity to RET inhibition in breast cancer (15). Based on these results, we hypothesized that the combination of RET fusion and amplification enhanced the response to TKIs. Since MIR4299 was highly expressed in normal cells (16), we speculated that MIR4299 expression and function in normal cells may drive RET gene amplification in tumor cells with the RET-MIR4299 fusion gene. There is a possibility that RET intergenic-breakpoint MIR4299/MIR8070 fusion genes within episomes integrate into chromosomes but then amplify. The proposed hypothesis for how this amplification occurs is that the integration occurs downstream of a strong promoter (16, 17). Future studies will be needed to see whether high RET amplification represents important association to sensitivity to RET fusion-targeted therapies. This patient had a novel intergenic RET fusion plus RET amplification and achieved PR within 1 month. RET activation may contribute to a series of oncogenic signaling pathways, resulting in tumorigenesis and metastasis (3). Only fusion variants that maintain the complete RET kinase domains are considered carcinogenic and the functional intergenic fusion has therapeutic advantages. This report indicated that the combination of RET intergenic-breakpoint fusion and RET amplification may improve the response to pralsetinib therapy.
The datasets for this article are not publicly available due to concerns regarding participant/patient anonymity. Requests to access the datasets should be directed to the corresponding author.
Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent was obtained from the patient for the publication of any potentially identifiable images or data included in this article.
S-SW collected the patient data. FW drafted the manuscript. H-FQ conceptualized the study and contributed to writing—reviewing and editing. YH: supervision. All authors contributed to the article and approved the submission.
Author H-HL and H-NW are employed by Acornmed Biotechnology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
PMC9549251 | Ruth A. Foley,Ruby A. Sims,Emily C. Duggan,Jessica K. Olmedo,Rachel Ma,Steven J. Jonas | Delivering the CRISPR/Cas9 system for engineering gene therapies: Recent cargo and delivery approaches for clinical translation 10.3389/fbioe.2022.973326 | 26-09-2022 | gene therapy,CRISPR/Cas9,genome editing,intracellular delivery,nano carriers | Clustered Regularly Interspaced Short Palindromic Repeats associated protein 9 (CRISPR/Cas9) has transformed our ability to edit the human genome selectively. This technology has quickly become the most standardized and reproducible gene editing tool available. Catalyzing rapid advances in biomedical research and genetic engineering, the CRISPR/Cas9 system offers great potential to provide diagnostic and therapeutic options for the prevention and treatment of currently incurable single-gene and more complex human diseases. However, significant barriers to the clinical application of CRISPR/Cas9 remain. While in vitro, ex vivo, and in vivo gene editing has been demonstrated extensively in a laboratory setting, the translation to clinical studies is currently limited by shortfalls in the precision, scalability, and efficiency of delivering CRISPR/Cas9-associated reagents to their intended therapeutic targets. To overcome these challenges, recent advancements manipulate both the delivery cargo and vehicles used to transport CRISPR/Cas9 reagents. With the choice of cargo informing the delivery vehicle, both must be optimized for precision and efficiency. This review aims to summarize current bioengineering approaches to applying CRISPR/Cas9 gene editing tools towards the development of emerging cellular therapeutics, focusing on its two main engineerable components: the delivery vehicle and the gene editing cargo it carries. The contemporary barriers to biomedical applications are discussed within the context of key considerations to be made in the optimization of CRISPR/Cas9 for widespread clinical translation. | Delivering the CRISPR/Cas9 system for engineering gene therapies: Recent cargo and delivery approaches for clinical translation 10.3389/fbioe.2022.973326
Clustered Regularly Interspaced Short Palindromic Repeats associated protein 9 (CRISPR/Cas9) has transformed our ability to edit the human genome selectively. This technology has quickly become the most standardized and reproducible gene editing tool available. Catalyzing rapid advances in biomedical research and genetic engineering, the CRISPR/Cas9 system offers great potential to provide diagnostic and therapeutic options for the prevention and treatment of currently incurable single-gene and more complex human diseases. However, significant barriers to the clinical application of CRISPR/Cas9 remain. While in vitro, ex vivo, and in vivo gene editing has been demonstrated extensively in a laboratory setting, the translation to clinical studies is currently limited by shortfalls in the precision, scalability, and efficiency of delivering CRISPR/Cas9-associated reagents to their intended therapeutic targets. To overcome these challenges, recent advancements manipulate both the delivery cargo and vehicles used to transport CRISPR/Cas9 reagents. With the choice of cargo informing the delivery vehicle, both must be optimized for precision and efficiency. This review aims to summarize current bioengineering approaches to applying CRISPR/Cas9 gene editing tools towards the development of emerging cellular therapeutics, focusing on its two main engineerable components: the delivery vehicle and the gene editing cargo it carries. The contemporary barriers to biomedical applications are discussed within the context of key considerations to be made in the optimization of CRISPR/Cas9 for widespread clinical translation.
The discovery of efficient genome-editing tools such as the Clustered Regularly Interspaced Short Palindromic Repeats-associated protein 9 (CRISPR/Cas9) nuclease system has revolutionized our ability to manipulate the human genome. The selective editing of targeted DNA sequences enabled by these genetic engineering tools facilitates the permanent correction of genomic mutations, paving the way for new potential treatments for many genetic diseases. Based on exploitation of the natural immune system of Streptococcus pyogenes and an understanding of the fundamental structural function of RNA enzymes present in bacteria, the coupling of CRISPR and Cas9 to create a powerful gene editing tool earned colleagues Emmanuelle Charpentier and Jennifer Doudna the 2020 Nobel Prize in Chemistry. The path to widespread adoption of CRISPR/Cas9 as a genome editing tool began with an investigation into the mechanism of adaptive bacterial immunity. Initial findings, published in 2012, showed that programmed CRISPR/Cas9 and guide RNA could effectively cut viral DNA at sequence-specific sites (Jinek et al., 2012). Elucidation of the role of RNA in bacterial immunity against viral modifications to genomic DNA led to the discovery of two types of RNA that guide Cas9 to the DNA cut site (Jinek et al., 2013), and allowed for the simplification of this natural system to require just two components: Cas9 and a programmable single guide RNA sequence (sgRNA) (Cornu et al., 2017). The CRISPR/Cas9 system utilizes the programmable sgRNA to locate and bind to specific regions of the genome, where the Cas9 nuclease induces double-strand breaks (DSBs) at the target locations indicated by the guide sequence. The correction of defective endogenous genes can then occur either by removing specified regions of the target gene or by inserting an exogenous strand of DNA, dependent upon the DSB repair mechanism. Knockouts can occur if the DSB is repaired by non-homologous end joining (NHEJ) using protein factor re-ligation, while homology-directed repair (HDR) uses a homologous repair template to repair the DSB precisely, introducing a donor DNA template sequence of choice (Komor et al., 2016; Cullot et al., 2019; Wei et al., 2020; Yip, 2020; Sharma et al., 2021). Given that CRISPR/Cas9 allows for targeted DNA editing and only requires the relatively simple design of a guide RNA, it remains the most cost effective, standardized, and reproducible gene editing tool currently available (Bhattacharya et al., 2015; Yang et al., 2017). The emergence of this robust method for coordinating the manipulation of the genome has not only increased mechanistic understanding of intrinsic DNA repair processes, but is accelerating the development of treatments for genetic diseases via gene silencing, insertion, or site-specific correction. Potentially curative gene editing efficiencies in the lab, such as CRISPR/Cas9-mediated editing to achieve over 20% efficiencies in human hematopoietic stem cell populations using a Cas9 ribonucleoprotein (RNP) complexed to a single-stranded DNA oligonucleotide donor (ssODN) (Magis et al., 2022), have paved the way for the first clinical trials that apply CRISPR based therapies. Recently announced phase I and II clinical trials that leverage CRISPR/Cas9-based strategies to treat transfusion-dependent β-thalassemia (NCT03655678), sickle cell disease (NCT03745287) (Frangoul et al., 2021), transthyretin amyloidosis (NCT04601051) (Gillmore et al., 2021) and Leber congenital amaurosis 10 (NCT03872479) (Mullard, 2019) demonstrate the potential to treat monogenetic disorders with a single, consistent base pair mutation. However, the clinical translation of CRISPR-based therapies becomes increasingly more complex as the number and heterogeneity of mutations increases. One solution to this issue involves the integration of a normal copy of the associated complementary DNA (cDNA) upstream of the known, disease-causing mutations. For example, Kuo et al. (2018) demonstrated the site-specific incorporation of a human codon-divergent CD40L cDNA at the 5′ UTR of the gene in both primary patient T lymphocytes and human CD34+ hematopoietic stem cells, resulting in expression of the therapeutic gene and effectively muting all downstream, disease-causing mutations (Kuo et al., 2018). Further studies into the mechanism of CRISPR/Cas9 function, including the kinetics of DNA recognition, the binding mechanism of the Cas9 protein that enables it to ‘read’ DNA (Redding et al., 2015), and the kinetics of Cas9 DNA interrogation (Cofsky et al., 2022), continue to be conducted with the aim of improving clinical translatability. However, the secrets behind the incredible efficiency of this protein interrogation system, the impact of target search speed, and the natural diversity in limiting this efficiency all remain poorly understood. Elucidating these phenomena may enable the manufacture of faster search speeds and increased CRISPR/Cas9 efficiency in future clinical settings. Other CRISPR/Cas9-based technologies such as base editing (BE) and prime editing (PE) are some of the newest evolutions of gene editing methods that can directly place point mutations in the DNA of cells without DSBs (Komor et al., 2016; Gaudelli et al., 2017). Base editors are comprised of a Cas enzyme and a single-stranded DNA modifying enzyme for targeted nucleotide alteration. Approximately 25% of human pathogenic single nucleotide polymorphisms (SNPs) can be corrected using BE. The PE system has further diversified CRISPR gene editing capabilities to include all of the twelve types of transition and transversion mutations, including small insertions and deletions. Similar to BE, PE does not rely on establishing a DSB and instead utilizes an engineered reverse transcriptase that is fused to Cas9 nickase and a prime-editing guide RNA (pegRNA). The pegRNA contains both complementary sequences to the target site, which directs Cas9 to its target sequence, and a sequence that spells the desired sequence changes. By and large, PE has the potential to correct up to 89% of known genetic variants associated with human disease and to edit large genes which are not addressable using viral vectors with limited packaging capacity. Though BE and PE hold great potential for gene therapies, further characterization of BE and PE is needed to assess their off-target effects. Additionally, further evaluation of both methodologies in in vivo models is required (Komor et al., 2016; Gaudelli et al., 2017). While the mechanism of the CRISPR/Cas9 system becomes increasingly better understood, the further development of safe and effective ways to package gene editing reagents as well as improved intracellular delivery methods are required to enable broader clinical applications (Yip, 2020; Zhang et al., 2021b). Delivery of biomolecular cargoes that encode for the transient expression of the Cas9 protein carry with them a number of barriers to clinical use, which current investigations seek to address. Specifically, the precise insertion or deletion of DNA can be directly related to the successful delivery of cargo to cells and the DSB repair mechanism utilized. With the % HDR, target DNA site selection, sgRNA design, Cas9 activity, and subsequent off-target effects significantly impacting the success rate of gene editing, optimization of these parameters remains the key to clinical viability of CRISPR/Cas9-mediated genome engineering (Liang et al., 2017). When approaching the existing challenges to clinical translation outlined above, there are two key, interconnected components to consider: the gene editing cargo to be delivered and the mechanism of delivery. Well-established types of gene editing cargoes include Cas9-encoding DNA plasmids or messenger RNA (mRNA) constructs and Cas9 ribonucleoprotein (RNP) complexes. Each of these presents its own advantages and challenges. A Cas9 RNP complex consists of the Cas9 protein and a sgRNA. mRNA-based cargoes encoding Cas9 only require delivery to the cytosol for translation, whereas plasmids tend to be larger, more difficult to encapsulate, and must be trafficked to the nucleus for transcription. In contrast, while plasmids are relatively stable, mRNA presents with stability issues in physiological conditions. Protein-based cargoes such as Cas9 RNPs do not require transcription or translation, but the complex distribution of surface charges can make integration with certain delivery systems challenging. The ability to deliver multiple gRNAs via expression plasmid templates enables multiplexed gene editing. Limitations to this approach include a lower average editing efficiency when the guides are delivered as separate gRNA transcripts (8.2%) as opposed to a single gRNA array linking several gRNA transcripts (25%) as well as increased cell death (Kurata et al., 2018). Additionally, transfection of these plasmid-based CRISPR/Cas9 cargoes requires complex guide preparation that can result in increased off target effects due to their persistent expression compared to the shorter, more transient activity of pre-complexed RNPs (Liang et al., 2015). Cargo encapsulation and cellular uptake mechanisms must both be considered in the design and selection of delivery systems. There are several approaches to temporarily porate the cell membrane, each with their own advantages and challenges. Methods to physically generate pores in the cell membrane via mechanoporation techniques, including microinjection (Crispo et al., 2015; Hruscha and Schmid, 2015; Martin-Martin et al., 2018), microfluidics/cell squeezing (Saung et al., 2016; Bridgen et al., 2017), and sonoporation (Helfield et al., 2016) are all currently under development. The most widespread delivery method is electroporation, whereby cells are exposed to an electrical field in order to create pores in the membrane that facilitate reproducible and efficient intracellular entry of biomolecules into cells (Deng et al., 2018; Kang et al., 2020). However, this method tends to stress cells considerably and is often associated with low post-transfection viability, potentially compromising its utility for some autologous cell therapies where limited numbers of donor cells can be harvested. Cells may also be porated by exploiting the thermoplasmonic properties of metal nanoparticles, which can cause localized heating and temporarily damage the cell membrane (Xiong et al., 2014). Other approaches to intracellular delivery do not require transient membrane poration. Specifically, non-plasmonic nanoparticles may be used to encapsulate and deliver intact CRISPR/Cas9 cargoes intracellularly. Supramolecular and lipid nanoparticle formulations are of particular interest as they can be engineered to bear positive surface charge and protect their cargo from degradation (Ping et al., 2011; Ashok et al., 2021). In addition, nanoparticles are scalable to synthesize and tunable in size, and are thus promising delivery vehicles for gene editing cargoes. These non-viral intracellular delivery approaches are not without their challenges. Currently, viral vectors, which harness a virus’ natural ability to enter cells and to modify DNA, remain the delivery vehicle of choice for most clinical gene therapies. While existing viral vectors are effective in laboratory settings, they do not translate easily for many clinical applications due to limitations in their cargo carrying capacity (Wu et al., 2010) as well potential issues with immunogenicity and insertional mutagenesis due to the semi-random gene insertion mediated by these viral carriers (Nault et al., 2015). Non-viral vectors, including several nanoparticle-based systems, have more recently been identified as viable alternatives to viral vectors. Indeed, non-viral vectors have been shown to deliver Cas9/sgRNA plasmids in vitro with one study reporting a 47% successful transfection of plasmid in A374 cells, resulting in >67% suppression of tumor growth in vivo (Zhang et al., 2017a). Recent design considerations for non-viral delivery vectors have emphasized increasing gene delivery and expression efficiencies (Li et al., 2018a). CRISPR/Cas9 has transformed the ease and precision of gene modification. While the rapid progress made in the efficiency and accuracy of CRISPR/Cas9 technology has provided new capabilities for establishing robust and durable therapeutic interventions, significant barriers to broader clinical adoption persist. This review aims to summarize current and emerging bioengineering approaches used to direct the transport of CRISPR/Cas9 gene editing tools into targeted cells. We focus on two engineerable components: the delivery vehicle and the gene editing cargo it carries. An understanding of these tools will help to provide an overview of the contemporary CRISPR/Cas9 clinical landscape, the challenges that lie ahead on the road to therapeutic gene editing using CRISPR/Cas9, and the considerations required when selecting both CRISPR/Cas9 cargo and the delivery vehicle to be used.
Successful clinical application of CRISPR/Cas9-based therapeutics requires both accurate binding to the targeted sequence in the host genome (Liang et al., 2017) and efficiency in the repair mechanism following the formation of Cas9 endonuclease-induced DSBs. There are an increasing number of CRISPR-based cargo options currently being optimized to address these challenges. The DSBs induced by the Cas9 protein are an essential feature of the CRISPR/Cas9 system as they enable the correction of defective endogenous genes. The repair mechanism subsequently applied to DSB sites primarily determines the mode of gene editing via either gene knockout, deletion, correction, or insertion. Repair of DSBs follows one of two mechanisms: NHEJ using protein factor re-ligation, or HDR by a homologous DNA repair template. NHEJ-mediated repair is less versatile and more prone to unwanted off-target deletions, whereas HDR precisely repairs the DSB but is cell cycle dependent (limited to the late S- or G2-phase). As a result, many attempts to create clinically applicable CRISPR/Cas9 cargo are focused on further increasing the efficiency and incidence of HDR (Chu et al., 2015; Maruyama et al., 2015; Liang et al., 2017; Li et al., 2018a). A deeper understanding of the factors that determine the ratio of HDR to NHEJ remain largely unknown, however, a study by Kato-Inui et al. (2018) has revealed that modified sgRNAs and Cas9 variants may be used to enhance HDR, suggesting that modifications to the traditional CRISPR/Cas9 system could optimize the HDR:NHEJ ratio. The modification of Cas9 has further provided an opportunity to overcome several significant HDR-related limitations of CRISPR/Cas9 in the site-specific correction of human hematopoietic stem cells, which exhibit lower HDR:NHEJ. For example, Kohn and colleagues found that a modified Cas9 with reduced nuclease activity transiently increased the number of cells in the HDR favored S/G2 phase, resulting in a four-fold increase in the HDR:NHEJ ratio. These insights ultimately inform the rational design of CRISPR/Cas9 gene therapies where HDR:NHEJ is critical (Lomova et al., 2018).
Recent research has been largely focused on optimizing guide RNAs that are delivered in conjunction with the Cas9 nuclease. Traditional guide RNA constructs can be divided into two separate RNA strands: Target-specific CRISPR RNA (crRNA) and target-nonspecific trans-activating CRISPR RNA (tracrRNA), which hybridize to bind the targeted DNA sequence for mutagenesis (Latorre et al., 2016). Jinek et al. (2012) first combined these transcripts into a programmable single guide RNA after elucidating the relationships between tracrRNA, crRNA and Cas9 through a series of electrophoretic mobility shift assays, which illustrated that tracrRNA must recognize the targeted DNA strand once correctly positioned by the crRNA. Furthermore, introduction of specific chemical modifications to this nucleic acid-based guide molecule has been shown to affect Cas9 activity (Jinek et al., 2012). Hairpin loops are common secondary structures within RNA molecules and can regulate gene expression in either a cis or trans manner. A cis-acting hairpin influences expression within the RNA molecule, while a trans-acting hairpin affects other RNA molecules and pathways (Svoboda and Di Cara, 2006). When comparing the editing efficiencies of linear versus hairpin-engineered sgRNAs of different lengths in MCF-7 cells, Liang et al. (2022) demonstrated that the hairpin structures had a higher selectivity for editing the mutant sequence of the KRAS gene target over the wildtype sequence (Figure 1A). Kocak et al. (2019) purposefully incorporated hairpins within the spacer sector of sgRNA (hp-sgRNA) and compared these modified constructs to non-structured sgRNA of the same size while monitoring the editing activity of the Cas9 protein at off-target sites in HEK 293T cells. They hypothesized that the hairpin structure would provide a steric barrier that only allowed editing for specific, on-target sites, and observed via sequencing analysis reduced off-target activity with hp-sgRNA. These data indicate that the addition of a secondary structure improved the specificity of the Cas9 RNP complex. The improved specificity of the hp-sgRNA for the Cas9 complex was confirmed when compared to sgRNAs with a truncated spacer sequence, and unmodified sgRNA). Despite the advantages of hp-sgRNAs, the possible cytotoxic effects have not yet been fully defined. The mechanism of hp-sgRNAs’ action on cell viability remains a critical barrier to their clinical use (Kocak et al., 2019; Moon et al., 2019; Hu et al., 2021). While molecular modifications to sgRNA aim to improve the specificity of gene editing and enhance the safety of these therapies, they do not address the problems with low efficacy conferred by the susceptibility of RNA to degradation. Strategies to increase the stability of RNA in the presence of degrading ribonucleases and enhance the degree of binding to complementary sequences have recently incorporated alterations to portions of the sgRNA sequence. Hendel et al. (2015) modified the final three nucleotides on both the 5′ and 3′ ends of three separate sgRNA molecules and compared their enzymatic activities in vitro for both primary human T cells and CD34+ hematopoietic stem and progenitor cells. The modifications tested included incorporating 2′-O-methyl (M), 2′-O-methyl 3′ phosphorothioate (MS) or 2′-O-methyl 3′thioPACE (MSP) into the nucleotides. These changes were not found to diminish endonuclease activity via T7 assay, but MS and MSP did increase the frequency of indels based on tracking of indels by decomposition (TIDE) analysis of polymerase chain reaction (PCR) amplicons from the different sgRNA target sites (Hendel et al., 2015). An increase in insertions and deletions without a decrease in level of activity demonstrates how these modifications improve the nuclease’s editing efficiency. Jing et al. (2021) included the same MS modification to their sgRNA and observed a 15% higher knock-in efficiency compared to unmodified sgRNA when attempting to knock-in predetermined template plasmids into primary human T cells. Ryan et al. (2022) similarly engineered the MS and MP nucleotide modifications to their synthesized sgRNA structures and observed increased indel editing for the HBB gene within human primary T cells. By incorporating these alternations within the internal structure of these molecules, they were able to decrease the percentage of off-target indels thus increasing the sgRNA selectively (Figure 1B) (Ryan et al., 2022). While these data are promising, such chemically modified nucleic acid sequences may induce unwanted and unpredictable immunological responses. Kim et al. (2018) reported that incorporation of a 5′-triphosphate group on sgRNA could promote innate type 1 interferon-mediated immune responses. The phosphatase-mediated removal of this nucleoside triphosphate group led to an increase in cell viability and reduction in the previously associated immune response (Figure 1C) (Kim et al., 2018).
Plasmid DNA (pDNA) is a well-established cargo for transfection and gene editing studies. Based on the method of adaptive immunity within prokaryotes, circular or linear DNA is delivered to a target cell and then trafficked into the nucleus for the expression of a gene of interest (Bower and Prather, 2009). Plasmids are advantageously stable within the cellular microenvironment and their potential for genomic integration when designed with cassettes encoding for transposon systems such as Sleeping Beauty or PiggyBAC may lead to longer lasting genomic changes (Cicek et al., 2019). However, pDNA has been shown to induce lower editing efficiency than RNPs when delivered via electroporation (Kim et al., 2014). Engineered modifications to pDNA constructs are under investigation to increase the overall rate of transfection and minimize cytotoxic effects. Zamolo et al. (2020) monitored green fluorescent protein (GFP) expression for a library of peptide dendrimers and discovered one (Z22) that combined a hydrophobic core with a highly branched configuration that helped transfect an ‘all-in-one’ CRISPR/Cas9 pDNA vector into 62.5% of HEK 293 cells and 47.3% of HeLa cells while also showing no reduction in cell viability (Zamolo et al., 2020). Similar supportive structures may enhance transfection in primary cell types. The relatively larger size (∼9.3 kb) and higher molecular weight of pDNA constructs represent major barriers to efficient delivery and intracellular trafficking (Wang et al., 2018a). Since transcription of pDNA requires localization to the nucleus, these cargoes are susceptible to off-target editing by the transcribed Cas9 endonuclease (Miller and Siegwart, 2018). These extraneous edits are often unpredictable and can be disastrous to targeted cells. Tissue- and cell-specific promoters and enhancers that overcome these issues are being investigated to enable clinical-scale gene editing (Cicek et al., 2019). One interesting analog to pDNA expression cargoes are minicircle DNA vectors (mcDNA). Similar to pDNA, this episomal DNA architecture is replicated in bacteria from a parental plasmid, but with the bacterial backbone and antibiotic resistance sequences removed to reduce the size of the vector (Kelly et al., 2021). The smaller size of mcDNA constructs makes them attractive for applications involving the delivery of larger gene expression cassettes. For example, Eusébio and colleagues observed that mcDNA encoding tumor suppressor gene p53 yielded more efficient transfection and sustained expression compared to pDNA vectors in HeLa cells (Eusébio et al., 2021). Kelly et al. (2021) utilized mcDNA both for the combined Cas9 and sgRNA-expressing vector as well as the donor templates designed for HDR or homology-independent targeted integration (HITI)-mediated insertion of a tdTomato reporter into the AAVS1 safe harbor locus of three human cell lines HEK 293T, HeLa, and PC3. Successful knock-in integration was measured through junctional PCR analysis and fluorescence microscopy. An added benefit to incorporating Cas9-encoding cargoes into smaller form factors is their higher resistance to degradation by hydrodynamic shearing forces relative to linear DNA when delivered via non-viral vectors. These potentially disruptive forces have the ability to affect the cargo as it is delivered to the target cells, and were modeled through nebulization processes to reflect clinical relevance (Catanese et al., 2012) While the effect that the removal of bacterial backbone sequences has on immunogenicity remains to be fully determined, there is evidence of a decrease in pulmonary inflammation when mcDNA is delivered to the lung in comparison to pDNA (Munye et al., 2016; Florian et al., 2021). To parse out the optimal mcDNA configuration for the CRISPR/Cas9 system, more studies are required that directly compare transfection efficiency and cytotoxicity across several types of nucleic acid-based cargoes.
To diversify possible payloads that do not require genomic integration, mRNA is often leveraged. Cas9-encoding mRNA transcripts are shorter (∼4.5 kb) than DNA plasmids and they are already spliced and ready for cytosolic translation (Kenjo et al., 2021). These cargos tend to display lower off-target activity and are well suited for clinical applications as indicated by their use in the recent COVID-19 vaccines. For example, Liang et al. (2015) observed a 2-fold lower rate of off-target cleavage when Cas9 was delivered to HEK 293FT cells as mRNA compared to cells transfected using pDNA (Liang et al., 2015). Various alterations to the mRNA construct are under investigation, including modifications that result in increased cell viability and transfection efficiency. One well-known and naturally occurring structural modification is to replace uridine with pseudouridine (Kariko et al., 2008). Modified mRNA was translated to a greater extent at each measured time point than unmodified mRNA in rabbit reticulocyte lysates, these results could not be replicated for wheat germ extracts and E. coli lysates (Kariko et al., 2008). This outcome postulates that the benefits of cargo manipulation are most likely cell type dependent. Vaidyanathan et al. (2018) built on these results and tested a combination of four additional modifications on a mRNA transcript for Cas9 specifically. A uridine-depleted transcript with 5-methoxyuridine (without HPLC purification) was selected as the preferred candidate for further in vitro and in vivo testing as it balanced a reduced innate immunogenic response with the feasibility for mass production (Vaidyanathan et al., 2018). Although these initial results are promising, continued optimization of mRNA constructs will likely be required to further reduce immunogenicity and increase molecular stability before widespread clinical translation is achievable. Importantly, when mRNA transcripts are used in CRISPR/Cas9 applications, the endonuclease is expressed transiently. This is advantageous even when multiple doses may be required to maintain a significant intracellular level of Cas9 in non-renewing cell populations, because prolonged presence of the protein is associated with cytotoxicity, off-target cutting, and immune responses (Knopp et al., 2018; Kowalski et al., 2019). Transient expression of Cas9 mitigates these undesired effects. The use of mRNA transcripts in ex vivo applications may therefore minimize patient immunogenicity by ensuring that corrected cells are cleared of Cas9 before they are administered to patients, and reduce the time immunosuppressants are required for in vivo treatments (Crudele and Chamberlain, 2018). While the transient expression of mRNA has thus far been considered favorable in developing CRISPR/Cas9 gene therapies, the need for further control over protein expression has pushed the creation of programmable, small-molecule-responsive RNA binding proteins to control expression of proteins from RNA-encoded genetic circuits (Wagner et al., 2018). External regulation of protein expression in BHK-21 cells and a mouse myoblast cell line, C2C12, was achieved by leveraging a small-molecule-regulated safety switch that cleaves the RNA circuit when a small molecule is introduced. While to the authors’ knowledge this technology has not yet been directly applied to the CRISPR/Cas9 system, controllable, self-replicating mRNA may provide additional control over transiently expressed mRNA (Wagner et al., 2018; Pandelakis et al., 2020). Other characteristics of mRNA constructs for CRISPR/Cas9 are its high molecular weight (>330 kDa), high degree of hydrophilicity and anionicity, and low stability (Miller and Siegwart, 2018). These factors collectively impair transport of mRNA molecules to across membranes and stability in different cellular microenvironments, thus contributing to the lower transfection efficiencies observed when delivery is attempted without the appropriate packaging.
Cas9 RNPs composed of the recombinant Cas9 protein complexed with a sgRNA, often referred to as protein-based Cas9, have been applied to accomplish both efficient and on-target genome editing. Like mRNA, protein-based cargoes like RNPs ensure transient endonuclease activity and reduced likelihood of off-target effects. However, the sgRNA-Cas9 complex exhibits a better stability profile compared to mRNA (Tang et al., 2021). Advantages of RNPs include lower off-target editing, fast action, and transience of the protein. However, the higher reagent costs associated with these protein-based cargoes often precludes large scale studies, and the size of the Cas9 protein (160 kDa) often limits delivery efficiency. However, recent advances in encapsulating Cas9 into polymer nanoparticles have begun to offer solutions for delivering Cas9 RNP for in vivo genome editing (Chen et al., 2019). Efforts to further increase the efficiency and precision of RNPs for clinical translational studies primarily target increasing the incidence of HDR. A recent study revealed two successful approaches for improvement across multiple genomic loci in diverse cell types (Nguyen et al., 2020). The first involved addition of truncated Cas9 target sequences to the ends of the HDR template, which then interact with RNPs to shuttle the template to the nucleus. This approach has been shown to enhance HDR efficiency fourfold. The second involved using polyglutamic acid nanoparticles to stabilize Cas9 RNPs to achieve a two-fold increase in editing efficiency. In addition to increased efficiency, these modifications also resulted in increased stability, reduced toxicity, and enabled lyophilized storage. The inclusion of modified donor DNA has also shown promise in further promoting HDR. The co-delivery of Cas9 RNPs with donor DNA exhibiting modifications close to the cleavage site showed improved integration efficiency in HEK 293T cells. Specifically, phosphorothioate modifications have been applied to protect the ends of the donor DNA and improve editing efficiency (Liang et al., 2017). In addition, incorporating targeting vectors with 3′ overhangs at both ends of the donor DNA was shown to increase HDR efficiency significantly in mouse embryonic stem cells using specific modulating targeting vectors (Hirotsune et al., 2020). Both methods increase the occurrence of HDR when delivering protein based Cas9 and efficiently improve editing precision. The CRISPR/Cas9 system has the ability to transform approaches to treating genetic diseases. The appropriate cargo must be selected for any particular goal or application. Each form of Cas9 endonuclease, be it a pDNA construct, mRNA construct, or protein, comes with its own benefits and limitations. Recent studies have balanced the optimization of these subtypes of cargo through various chemical manipulations to improve transfection and editing efficiencies and reduce immunological responses and off-target effects that hinder possible clinical applications. Improving mechanisms of delivery must go hand-in-hand with the optimization of CRISPR/Cas9 cargoes if the goal of clinical translation is to be achieved.
While the optimization of CRISPR/Cas9 cargoes is essential for successful gene editing, delivery of these optimized cargoes to target cells and tissues represents an enormous barrier to effective clinical gene therapies. In recent years, the toolkit of available methods for intracellular delivery has largely expanded, and the advantages and limitations of each have been better elucidated and addressed. The methods used to deliver the gene editing cargo can be classified into physical, energetic, and particle-based delivery. Common techniques for delivery include mechanoporation and micron/nanoscale structure-mediated membrane penetration, electroporation, and acoustoporation.
The physical disruption of the cell membrane is a very common method of permeabilizing cells to cargoes, which do not readily enter cells on their own. Membrane disruption can be achieved using a variety of micron and/or nanoscale structure-mediated approaches. Microinjection, as illustrated in Figure 2A a type of mechanical transfection that uses a micrometer-sized capillary to inject gene editing cargo into cells. It is favored for its practicality in single-cell applications and its precision in the mechanical delivery and retrieval of biomolecules to and from the cell nucleus to enable rapid gene editing (Wu et al., 2015). Using a microscope and a microneedle (0.5–5.0 μm diameter), plasmid DNA, mRNA, or Cas9 protein can be directly injected into the membrane of a cell of interest via microinjection. This technique has been used in recent years to generate genetically-modified animals including sand flies, sheep zygotes, and zebrafish (Crispo et al., 2015; Hruscha and Schmid, 2015; Martin-Martin et al., 2018) with specific-site mutations into embryos, but has often resulted in the generation of mutant embryos with several cells carrying mutations (Le et al., 2021). DNA and mRNA are the most commonly used cargoes for microinjection delivery, where DNA is able to freely transcribe and translate its components in the nucleus and mRNA is injected directly into the cytoplasm to be translated by the cell. For example, Chuang et al. (2017) utilized microinjection of DNA that encodes both Cas9 and sgRNA directly into the nucleus to eliminate the transcription reactions that occur in vitro. Raveux et al. (2017) used microinjection of CRISPR mRNA components into the cytoplasm to enable the sgRNA to bind to Cas9 and enter the nucleus of the cell. Li et al. (2021) investigated the effects of the timing of microinjection on embryo development and the gene targeting efficiency of the CRISPR/Cas9 system to disrupt the interleukin 2 receptor subunit gamma (IL2RG) locus using porcine in vitro fertilization (IVF) and somatic cellular nuclear transfer (SCNT) derived embryos. To evaluate the Cas9 mRNA translation time in the porcine embryos post-microinjection, Cas9 protein expression was detected at low levels after 1 h and expressed higher levels after 6 h, as illustrated in Figure 2A. Though highly effective at delivery to a cell of interest, microinjection requires a skilled technician to maintain cell viability, produces low throughput of the cargo, is labor intensive and time consuming, and is generally limited to small scale in vitro studies. Mechanoporation may also be achieved by directing cells to nanoscale cell-penetrating structures. Specifically, nanoneedle arrays have been used to transfect larger numbers of cells via direct penetration of the cell membrane to deliver biomacromolecules adsorbed to the nanoneedle surface. This method, leveraging RNP-adsorbed arrays of silicon nanoneedles 200 nm in diameter, was found to induce gene editing efficiencies of up to 32%, and allowed for the transfection of adherent cells while in monolayer rather than in suspension (Yamagishi et al., 2019). Melosh and colleagues recently demonstrated a magnetic nano-electro-injection (MagNEI) platform that is used to transfect primary human T cells efficiently (Tay and Melosh, 2021). This method involves the localization of electric fields generated from hollow nanochannels to open pores transiently on the membrane of cells, allowing DNA to enter. Once DNA is inside the cell, magnetic forces are applied via Dynabeads™ (ThermoFisher) to enhance nuclear transport, thus resulting in enhanced DNA transfection. These magnetic forces also accelerate the membrane repair and help to sustain cell proliferation and gene expression throughout the transfection process through the promotion of actin cytoskeletal remodeling (Tay and Melosh, 2021). Another method, deterministic mechanoporation, achieves single-cell delivery through the utilization of aspiratory flows and a sub-micrometer-scale needle within individual wells on a large array of captures sites. The concave wells are fabricated to be cell type size specific and the aspiratory flows are regulated to ensure that the tension on the plasma membranes facilitates needle penetration, yet does not deform the target cell. After a transient single poration site is created in the membrane, small to large cargo can be delivered to the target cells en masse. This approach has successfully transfected Jurkat (88%), K562 (49%), and primary human T cells (82%) with GFP plasmid while maintaining high cell viability. Although a high throughput approach, the requirement to treat cells ex vivo is not suitable for all cell types (Dixit et al., 2020). These nanostructure-mediated membrane penetration methods streamline injection-based CRISPR/Cas9 gene editing for adherent cells and increase throughput compared to microinjection for suspension-type cells tethered to a culture dish. These delivery strategies are still being investigated for clinical translation. Cell squeezing, another microfluidic-based biophysical mechanoporation technique, passes cells at high speeds through micrometer-sized constrictions, disrupting the plasma membrane and enabling the delivery of various cargoes through the cytosol of numerous cell types (Sharei et al., 2013), illustrated in Figure 2B. Saung et al. (2016) found that a 4 μm wide constriction is effective for delivery of cargo to primary human T-cells that have an average diameter of 6.7 μm, whereas a 6–7 μm wide constriction is better optimized for cell lines between 10.8 and 12.3 μm such as BxPc3 and PANC-1. In addition, Han et al. (2015) effectively delivered CRISPR into difficult-to-transfect SU-DHL-1 lymphoma cells via cell squeezing using a microfluidic device made of diamond-shaped polydimethylsiloxane (PDMS) pillars with a constriction width of 4 µm. According to the study, a sharp angle of deformation preserved cell viability better than a curved constriction. Using the same device, they managed to deliver an enhanced green fluorescent protein (EGFP) reporter plasmid to ∼30 and 50% of SU-DHL-1 lymphoma cells and AB 2.2 mouse embryonic stem cells, as well as knockout EGFP in MDA-MB-231 (human breast cancer) and SU-DHL-1 cell lines. Another study by Han et al. (2017) demonstrated delivery of a RNP cargo configured to knock out EGFP using a microfluidic device to mechanically transfect EGFP-expressing SK-BR-3 cells, MDA-MB-231 cells, SU-DHL-1 cells, and human primary T cells. The study found maximum knockout efficiency occurred at 2 µM RNP and demonstrated a mutation frequency for the MDA-MB-231 cells, SU-DHL-1 cells, and human primary T cells to be 43, 47, and 33%, respectively. The device achieved delivery efficiencies of roughly 40% for both RNPs and Cas9 plasmid constructs, with plasmids generating an off-target mutation rate of 4.7% compared to 0.8% for RNPs. Similarly, cell-squeezing devices with progressively narrow channels either 40–4 µm or 60–6 µm in diameter were shown to effectively deliver functional RNPs targeting the GFP gene in a stably-expressing GFP reporter U20S cell line, inducing ∼40% knockout of the GFP gene (Uvizl et al., 2021) (Figure 2B). Similarly, Bridgen et al. (2017) demonstated the ability to use cell squeezing in the delivery of Cas9 RNPs to primary human T cells and CD34+ hematopoietic stem and progenitor cells to edit the CCR5 and B2M loci with little detectable impact on cell differentiation, proliferation, and function, further establishing cell squeezing as a viable method for cell therapy manufacturing. Though cell squeezing via microfluidic devices demonstrates transfection efficiency to various cell types, it presents additional challenges. While delivery via cell squeezing is well documented, the repair mechanism of the plasma membrane must be understood as it may have detrimental effects on cell viability. Sharei et al. (2014) studied membrane recovery kinetics by examining rate of repair while varying buffer composition. They demonstrated that recovery is an active, calcium-mediated process as it cut recovery time of HeLa cells from over 3 min in phosphate buffered saline (PBS) alone to 15–30 s with the addition of calcium. By understanding the relationships behind the factors that affect membrane repair mechanisms, poration methods may be improved to retain high transfection while increasing cell viability. Various studies also encounter device clogging, inverse proportionality between cell viability and transfection efficiency over time, as well as the inability to deliver nucleic acids (Chakrabarty et al., 2021). Additionally, this method of delivery is optimized for in vitro work and cannot be easily adapted for in vivo applications. Another technique of microfluidic-based mechanoporation called hydrodynamic manipulation can deliver large macromolecules in vivo by injecting a liquid solution intravenously at extremely high volume and pressure. This sudden increase in volume induces the temporary generation of pores in the vasculature, allowing the large macromolecular payload to reach the target tissue. This technique is commonly paired with other delivery techniques as it excels in distribution of deliverables to in vivo tissues but does not necessarily have a method to bypass cellular membranes themselves. Hydrodynamic injections via the tail vein in mice have successfully delivered plasmids carrying Cas9 and gRNA into the heart, lungs, liver, and kidney tissue. Presently, this method is restricted to use with small animal models due to the large starting injection volume necessary (∼10% body weight of the mouse). As such, it is currently not appropriate for human applications, although research is ongoing to optimize this technique for larger animal use (Chakrabarty et al., 2021). Deng et al. (2018) investigated delivery of various cargos such as protein, siRNA, CRISPR/Cas9, plasmid DNA, and DNA nanomaterials to different cell types using a hydrodynamic delivery platform termed inertial microfluidic cell hydroporator (iMCH) (Deng et al., 2018; Kang et al., 2020). The iMCH focuses cells into a channel center, leading them into a T-junction where the membranes are rapidly deformed and rendered transiently porous to allow the uptake of the nanomaterials into the cytoplasm. This method of hydroporation was found to maintain high cell viability and achieved a COL11A1 gene knockdown efficiency of over 80% in A2780cis cells with the successful delivery of the CRISPR/Cas9 system (Deng et al., 2018) and delivers nanomaterials to the cell while overcoming some of the toxicity challenges of earlier nanocarrier or membrane disruption techniques (Deng et al., 2018; Kang et al., 2020). This system was further developed to establish mixing in conjunction with the transient deformation of the cell membrane by incorporating spiral vortex flows at the T-junction of the microfluidic device to facilitate both passive diffusion and convection-based rapid solution exchange across the membrane of processed cells (Hur et al., 2020). The successful delivery of gold and silica nanoparticles, dextran, and mRNA to MDA-MB-231 human epithelial breast cells at efficiencies of up to 96.5% with cell viability of up to 94.5% was demonstrated (Kang et al., 2020). Most recent updates to this system leverage droplet microfluidics in the channel, reducing cargo consumption, scaling throughput and reducing clogging to near-zero when treating primary human T cells (Joo et al., 2021). The continued scaling and development of this system has established hydroporation as a simple, efficient, high throughput, low-cost, and clinically applicable intracellular delivery system (Deng et al., 2018; Kang et al., 2020).
Electroporation applies a strong electric field across a cell membrane, which exceeds the membrane’s capacitance, to transiently open nanometer-sized pores as illustrated in Figure 3A. The increase in permeability allows large biomolecules that would otherwise be rejected to enter the cell (Gehl, 2003). Electroporation can readily deliver difficult-to-manipulate cargoes to a wide number of cell types, and is often most effective for immune cells and stem cells. Due to its simplicity and efficacy, electroporation is currently one of the most commercially available and attractive non-viral delivery methods for gene editing cargo (Qin and Wang, 2019). Electroporation has been shown to be successful in vitro and ex vivo applications, for the delivery of RNPs, DNA, and mRNA for both knock-in and knock-out of target sequences (Yang et al., 2018). Alghadban et al. (2020) reported improvements in mutagenesis efficiency for the generation of ssODN repair templates and a higher rate of embryo survival and development when delivering CRISPR/Cas9 systems as RNPs via zygote electroporation. Another group achieved viable embryos and high CRISPR/Cas9 entry into the cells using RNAs that were electroporated into zygotes (Hashimoto and Takemoto, 2015) via nucleofection, a specialized form of electroporation that does not necessitate breaking down the nuclear envelope, to mouse spermatogonial stem cells to correct a cataract-inducing mutation (Wu et al., 2015). Cas9 RNPs are the preferred cargo for delivery via electroporation because they are more stable than their pDNA and mRNA counterparts. Though the processes of applying an electric field to cells can effectively deliver cargo, some electroporated cells may be damaged due to excessive heat exposure, ionic imbalances, and changes in pH. Notably, large plasmids can cause a decrease in viability in comparison to smaller plasmids by increasing permeabilization levels and duration in cells resulting in the prevention of the cells from resealing; standard electroporation buffers can cause substantial cell death, and uneven electric field distribution can cause liquid/air interfaces inside cuvettes where cells are housed that lower transfection efficiency (Lesueur et al., 2016; Cao et al., 2019). In an effort to further characterize the impact of electroporation on cell viability for the successful application to cell-based therapies, DiTommaso et al. (2018) comparatively analyzed microfluidic cell squeezing against electroporation by investigating disruptions in the expression profiles of key functional transcripts of human T cells. The study found that though both methods efficiently edited the cells, microfluidic cell squeezing had minimal transcriptional responses, showed undiminished effector responses, and therapeutic potential in vivo in comparison to electroporation (DiTommaso et al., 2018). This study highlights the importance of understanding the effects of intracellular delivery methods and that further optimization of electroporation techniques may benefit research and clinical applications. To address some of the disadvantages of the electroporation method, Xu et al. (2018) developed a modified tube-shaped cuvette that is less prone to bubble formation. They applied this technique to knock-out β2-microglobulin (B2M), a component of major histocompatibility complex (MHC) class I molecules, in primary human messenchymal stem cells, reducing expression by 80.2% through the delivery of Cas9/gRNA RNP with an ssODN introducing a frameshift mutation through single base insertion (Xu et al., 2018), as well as reducing surface expression of the protein in mesenchymal stem cells from 95.6 to 59.9% (Figure 3A). Cao et al. (2018) developed a nanostraw electroporation platform to enhance the local electric field and decrease the operating voltage and bubble formation. This method of nanoelectroporation allows for spatial control of the cells in a smaller nanostructure interface that enhances the local electric field. The group reported 90% cell viability and 85% mRNA transfection efficacy (Cao et al., 2018). In an effort to overcome the challenges of electroporation outlined above, Ding et al. (2017) used a hybrid microfluidic electroporation device to create rapid mechanical deformation of the cell membrane by cell squeezing in combination with electric-field driven transport to efficiently increase DNA expression in HeLa cells within 1 h of treatment, demonstrating the power of combining and developing these delivery methods further. Additionally, Yang and colleagues leveraged nanopores present on commercially available polycoarbonate water filtration membranes to design an affordable nanopore electroporation (nanoEP) method. Optimization of these nanoEP devices resulted in the gene editing of the PPIB gene in about 25% HeLa and Jurkat cells using Cas9 RNPs and up to 95% viability after transfection (Cao et al., 2019). Similarly, Roth et al. (2018) investigated non-viral genome targeting methods by co-electroporating human primary T cells with CRISPR/Cas9 RNP complexes and linear double stranded DNA (dsDNA) HDR templates designed to introduce an N-terminal GFP fusion in the housekeeping gene RAB11A to reduce the toxicity associated with the dsDNA template (Roth et al., 2018). According to the study, this method of electroporation resulted in up to 50% GFP expression in human CD4+ and CD8+ T cells, is highly efficient, maintains high cell viability, and provides preclinical evidence of therapeutic engineering of primary human immune cells. Stadtmauer et al. (2020) reported a Phase I clinical trial assessing the safety and feasibility of CRISPR/Cas9 gene editing in patients using electroporation. T cells were isolated from the blood of patients with cancer and CRISPR/Cas9 RNP complexes loaded with three sgRNAs were electroporated into the normal T cells, resulting in the successful gene editing of the TRAC, TRBC1, TRBC2, and PDCD1 loci (Stadtmauer et al., 2020). While preliminary results from the trial demonstrated the safe and feasible use of the CRISPR/Cas9 system, these studies soley utilize in vitro and ex vivo methodology, respectively. Recent efforts to apply electroporation for delivery of Cas9-mediated systems in vivo have yielded successful gene editing in skin stem cells in mouse models. Through the application of electroporation on mouse tail skin, Wu et al. (2017) restored C7 function in Recessive Dystrophic Epidermolysis Bullosa (RDEB) mice and observed an increase in epidermal-dermal adhesion from 30 to 60% after 3–5 days following a single treatment. However, fluorescence-activated cell sorting (FACS) analysis of tdTomato+ epdidermal cells treated with this method revealed fluorescence in only 2% of cells (Wu et al., 2017). Additionally, the increased epidermal-dermal adhesion of the treated mice was not observed after 5 days, highlighting the unknown timeline on the permenance of these gene edits. Furthermore, the potential off-target effects of the RNPs when delivered through electroporation were not analyzed and any potential in vivo application will require a more thorough understanding of their RNPs immunogenicity. Though the success of this electroporation technique shows promise for CRISPR/Cas9 gene editing for in vivo applications in murine models, considerable limitations including the use of costly specialized instrumentation, pain, collateral damage to the area, and poor understanding of off-target effects must be considered and addressed before it can be deemed safe and effective for humans and appropriate for clinical use. The applied high voltages can cause irreversible changes to the membrane physiology that can adversely affect treated cells. To circumvent the impracticalities of using high voltages for ex vivo gene delivery, other methods of cellular poration are under development that preserve the appealing aspects of electroporation, including its scalability and ease of use.
Acoustoporation and sonoporation devices, which utilize ultrasound to induce pore formation in cellular membranes, have also been shown to facilitate the delivery of gene editing cargo. By inducing acoustic waves in a liquid medium, gas-filled microbubbles physically oscillate, often bursting at high pressure and allowing membrane perforation by macromolecules (Helfield et al., 2016). Oscillation facilitated by the negative and positive phases of the incident ultrasound pulses cause alternating expansion and shrinkage of microbubbles, inducing shock waves that disrupt the plasma membrane. At low pressures, the microbubbles undergo stable cavitation, where the magnitude of their oscillating size is inversely proportional to the localized acoustic pressure and disruption to the cell membrane, whereas at high pressures, bubbles undergo inertial cavitation, resulting in large, asymmetric bubble size oscillation and the formation of penetrating liquid jets, as illustrated in Figure 3B. The efficiency of sonoporation is dependent on cellular properties as well as acoustic excitation and microbubble parameters, the understanding of which can increase efficiency and controllability of the system (Tu and Yu, 2022). One such example where acoustoporation was applied to transfect pDNA encoding Cas9 and gRNA to human endometrial cancer (HEC)-1A cells is the work of Cai et al. (2019), who reported a 57% decrease of mRNA expression from the target knockout c-erbB2. Acoustoporation can be used without the aid of microbubbles, also known as ultrasound contrast-agent microbubbles (CA). These are known to enhance transient poration of cell membranes and are being explored for their in vitro and in vivo uses, and for their potential clinical applications in gene therapy and drug delivery (Carugo et al., 2011). However, at high pressure CAs can collapse and have the potential to cause capillary rupture and endothelial cell damage in vivo and cell rupture ex vivo and may reduce the effectiveness of delivered cargoes (Rich et al., 2022). Carugo et al. (2011) demonstrated acoustoporation of cardiac myoblasts in the absence of CAs using a cost-effective ultrasound-microfluidic device, which allowed for control over the position of the cells and the strength of the acoustofluidic forces. Results showed intracellular delivery of pharmaceutical agents (e.g., doxorubicin, luteolin, and apigenin) as well as the transmembrane transfer of fluorescent probes CMFDA and FITC-dextran. Additionally, it was found that cellular uptake of the pharmaceutical agents through acoustoporation in the absence of CAs increases cell cytotoxicity (Carugo et al., 2011). Similarly, Ankrett et al. (2013) investigated the effects of ultrasound-related stimuli without the use of CAs exposing H9c2 cardiac myoblasts to different ultrasonic fields within a glass micro-capillary (Ankrett et al., 2013). The microfluidic device was comprised of a square glass capillary coupled to a piezoelectric transducer (PZT) transducer that was mounted to a glass platform. An optimal injection flow rate of 2.6 ml/h allowed for a high viability of approximately 95% to be maintained (Ankrett et al., 2013). Surface acoustic waves create transient pores in cell membranes and enhance molecular uptake by causing strong streaming in the extracellular microenvironment, also without the use of microbubbles. For example, surface acoustic waves were used in the transfection of a small interfering RNA (siRNA)-liposome complex in HeLa cells and reported 40% transfection efficiency (Ramesan et al., 2018). In addition, hypersonic poration was generated using a nanoelectromechanical resonator to create 200 nm sized pores (Zhang et al., 2017b), and high-frequency bulk acoustic waves at 150 MHz frequency delivered CRISPR plasmid to HeLa and HEK 293 cells with efficiency of up to 40%, depending on size and concentration of the plasmid (Yoon et al., 2017). While typically reserved for in vitro applications, acoustoporation as a method of gene editing cargo delivery can in principle work via direct navigation by ultrasonic waves through microvasculature to a target tissue. This capability has the potential to offer a noninvasive, image-guided delivery method for the selective release and uptake of the cargo, though it will require extensive experimentation and planning before becoming an accepted method of in vivo gene editing (Helfield et al., 2016). When selecting a delivery vehicle, the viability of cells must be considered. Viability can be effectively optimized in devices which combine the use of ultrasound and microfluidic channels. Such acoustofluidic devices with the potential to create rapidly processing, point-of-care devices for bedside use can be tuned for high viability by adjusting both input voltage as well as flow rate (Belling et al., 2020). Towards this goal, a significant enhancement in the delivery of biomolecules to T cells has been achieved using a 3D printed acoustic device to deliver the fluorescent molecule calcein to human T cells (Centner et al., 2021). Issues of toxicity, cost and throughout have also been addressed via the development of an acoustofluidic sonoporation platform (Belling et al., 2020). The effectiveness of this device was demonstrated in the delivery of plasmids to primary human T lymphocytes and clinically relevant cell lines such as peripheral blood mononuclear cells, and CD34+ hematopoietic stem and progenitor cells. Acoustofluidic treatment has further been shown to be scalable, achieving throughputs of up to 200,000 cells/min by passing cells through a custom build system over a piezoelectric transducer that is scalable for future CRISPR/Ca9 clinical applications (Belling et al., 2020). Confocal imaging of treated cells revealed the presence of a fluorescent signal attributed to Cy3-labeled DNA at the cell membrane, cytosol, and nucleus for acoustic-treated cells, confirming the successful delivery of cargo using this high throughput method. Aghaamoo et al. (2022) also developed a microfluidic platform to deliver plasmid DNA and sgRNA into cells termed Acousto-Electric Shear Orbiting Poration (AESOP). The platform uses a high-throughput intracellular delivery method that relies on arrays of micro vortices formed by lateral cavity acoustic transducers (LCATs), which trap the cells and induce a controlled mechanical shear and electric field to facilitate the uniform poration on the membrane of a large number of cells simultaneously. AESOP demonstrated the uniform and precise transfection of a wide range of cargoes, including eGFP plasmid (6.1 kbp) and CRISPR/Cas9-mediated gene knockout using a 9.3 kbp plasmid DNA encoding Cas9 protein and sgRNA with viabilities over 80% in both suspension and adherent cell types. As a result, these technologies have the potential to be engineered for a wide variety of therapeutic applications which require large cargoes (Yoon et al., 2017; Wu et al., 2018; Castle et al., 2020). In addition to cell poration and cargo delivery, acoustofluidic tweezers (a form of acoustophoresis) enable the separation of microparticles and cells while facilitating the controlled and targeted delivery of genetic materials into the cytoplasm (Wu et al., 2018). This intracellular delivery technique has been used to transfect HEK 293 and HeLa cells with DNA plasmid and/or mRNA cargoes to achieve editing at single cell resolution using CRISPR/Cas9 (Yoon et al., 2017). While the use of acoustofluidic tweezers to deliver CRISPR/Cas9 is still limited to in vitro studies, acoustoporation has been applied clinically in the delivery of chemotherapeutic agents (Castle et al., 2020). A Phase I clinical trial showed that performing acoustoporation in combination with the chemotherapeutic agent gemcitabine on patients with pancreatic ductal adenocarcinoma demonstrated an increase in the median overall survival from 8.9 to 17.6 months in comparison to 63 historical controls and resulted in no additional adverse effects. The work is now moving forward to a larger Phase II clinical trial (Castle et al., 2020). While these preliminary efforts show great promise, there are still several obstacles that need to be optimized for acoustoporation to increase its clinical potential.
While promising for in vitro and ex vivo applications, the physical methods of delivery mentioned above do not offer feasible solutions to in vivo gene editing because they must be performed external to the patient. Particle carriers are better suited to such applications as they can be administered systemically. Viral particles have high transfection efficiencies, but have limited packaging capacities, are prone to immune activation and off-target effects, and may undergo recombination events, which can produce replication-competent viruses (Ashok et al., 2021). Synthetic carriers for CRISPR/Cas9 cargoes may offer a solution to these challenges. These synthetic carriers may be polymeric, lipid-based, or inorganic, and are appealing due to their tunability towards specific applications (Figure 4).
Cationic polymers such as chitosan and poly (ethyleneimine) (PEI) have long been used for the delivery of biomolecules, but confer particular challenges with delivery inefficiencies, problems with solubility, and toxicity (Ping et al., 2011; Ashok et al., 2021). These issues have been addressed, in part, by combining multiple constituents to obtain particles with superior efficacy to any one polymeric component alone. For example, Ma et al. (2021) compared genomic integration via delivery of plasmid encoding Cas9 using either particles comprised of polydopamine (PDA) and PEI alone, or functionalized with hyaluronic acid (HA), which is thought to target carbohydrate-specific endocytotic receptors, and dexamethasone (DEX), which acts as a nuclear localization signal, and reported higher rates of integration with functionalized particles. Further improvements to nanoparticle efficacy have been pursued through the development of custom-designed polymers as well as modifications to well-established polymers to improve their efficacy. Specifically, adamantane is used to modify nanoparticle components such as dendrimers, as its lipophilic properties support stable incorporation of functional components including transactivator of transcription (TAT) sequences and polyethylene glycol (PEG) moieties into self-assembled structures (Štimac et al., 2017). Similarly, biocompatible molecules are often grafted to PEI to improve its efficacy as a delivery agent. For example, in vitro gene editing efficiencies achieved via PEI-based nanoparticle delivery of CRISPR/Cas9 reagents are improved when PEI components are functionalized with HA or both HA and mannose (Francis et al., 2022). This enhancement is thought to be a result of the ability of these functionalities to target carbohydrate-specific endocytotic receptors on certain cell types (Francis et al., 2022). Further, modifying PEI with β-cyclodextrin to form CD-PEI has become common practice to generate nanoparticles with similar packaging and endosomal escape efficiency to PEI but much lower toxicity and, as a result, better transfection efficiencies (Ping et al., 2011). These grafting approaches are commonly utilized and effective for generating supramolecular polymeric nanocarriers. These modified compounds are leveraged as components of supramolecular nanoparticles (SMNPs), comprised of optimized ratios of adamantane-grafted polyamidoamine dendrimer (Ad-PAMAM), adamantane-grafted poly (ethylene glycol) (Ad-PEG), and CD-PEI, for the delivery of CRISPR/Cas9 reagents (Chou et al., 2020). In one study, SMNPs encapsulating plasmid encoding Cas9 and a guide targeting a safe-harbor locus and, separately, a plasmid encoding GFP plus a functional donor induced the correction of RS1 in vitro following intravitreal injection in a mouse model (Chou et al., 2020). Nanowire-grafted SMNPs were optimized to package and deliver RNPs as well, inducing successful disruption of the dystrophin gene and knock-in of the HBB gene (Yang et al., 2020; Ban et al., 2021). Similarly, Wan et al. (2020) used disulfide-bridged biguanidyl adamantane (Ad-SS-GD) with CD-PEI as components for supramolecular assembly for the packaging and delivery of Cas9 RNPs and successfully induced nearly 16% editing in SW-280 cells. Further decorating these Ad-SS-GD/CD-PEI nanoparticles with HA enabled in vivo tumor-specific editing at the KRAS gene in mice via intravenous (IV) administration (Wan et al., 2020). Other attempts at addressing the cytotoxicity issues that often accompany the use of polymeric nanoparticles include the use of materials that are degradable under physiological conditions. These materials generally include reducible functional groups, including disulfides, esters, and aminoesters. For example, Guo et al. (2021) rationally designed a series of poly (disulfide)s generated to form bioreducible materials with high cellular uptake efficiency, then explored their potential for nanoparticle delivery of Cas9-encoding plasmid, Cas9-encoding mRNA, sgRNA, and RNP complexes (Guo et al., 2021). The top-performing poly (disulfide) induced high rates of in vitro indel frequencies for all types of cargo, and these results were corroborated by slightly lower but still remarkable levels of indel frequencies in the liver after IV administration of the nanoparticles (Figure 5). This sort of rational design and experimentation is common in the development of new materials for nanoparticle delivery. For example, similar extensive investigations into poly (aminoesters) (PBAEs) as a key nanoparticle component for delivery of CRISPR/Cas9 genome editing reagents have been investigated (Rui et al., 2019a; Rui et al., 2019b; Rui et al., 2020). Indeed, 40% gene knockout was demonstrated in vitro by codelivery of plasmid encoding Cas9 as well as guide RNA targeting a fluorescent reporter gene via reducible branched ester-amine quadpolymer (rBEAQ)-based nanoparticles (Figure 5). Custom polymers under investigation are intended to resolve the challenge of packaging Cas9 RNPs by enabling covalent functionalization to amines on the endonuclease surface. For example, the work by Rui et al. (2019b) on PBAEs was extended to design carboxylated branched PBAEs nanoparticle carriers that are capable of RNP encapsulation (Rui et al., 2019a). These polymers are distinguished by their capability to react with the amines present at the surface of RNPs. Delivery of these particles induced over 75% gene knockout and 4% knock-in in vitro, and intracranial administration induced gene editing in vivo in mice bearing glioma tumors. In a similar approach, rather than modifying PAMAM with adamantane, Liu et al. (2019a) reports the use of boronic acid-functionalized PAMAM to successfully induce high indel rates in vitro. This moiety is intended to provide a functional group that enables conjugation with the amines present at the RNP surface. Finally, polymers are appealing for particle-mediated CRISPR/Cas9 delivery because their broad biochemical properties may not only facilitate delivery and packaging but confer some therapeutic benefit on their own. As a result, indirect approaches that synergistically complement the in vivo editing efficiencies of particle-based delivery, particularly for tumor therapies, include use of polymers sourced from non-CRISPR gene disrupting agents. Specifically, Zhang et al. (2021a) reports a cationic platinum (Pt (IV))-backboned polymer chain, derived from cisplatin, delivering a plasmid encoding both Cas9 and a guide sequence induced 32.2% gene disruption in vitro and 21.3% of tumor tissues in vivo.
While polymeric nanoparticles for CRISPR/Cas9 delivery have undergone significant advancements, they present with toxicity issues and tend to lack targeting specificity. Lipid nanoparticles (LNPs) offer a platform to overcome many of these challenges. Similarly to unmodified cationic polymers, cationic lipid constituents tend to confer issues with toxicity. This challenge has been largely overcome with the use of ionizable lipids that preserve electrostatic interactions with anionic cargoes. In addition, straightforward lipid self-assembly may be leveraged to be scalable and their modular composition has enabled some amenability to targeting specific tissues, even via systemic administration (Liu et al., 2021). For these reasons, LNPs are commonly used nanocarriers for in vivo delivery of nucleic acids and in particular, CRISPR/Cas9 therapies. Commercially available lipid-based transfection reagents such as Lipofectamine™ have long been used to deliver biomolecules to cells in vitro (Zangi et al., 2013; Lou et al., 2020), and these reagents have therefore been used as a standard against which next-generation LNP formulations are compared. This benchmarking has enabled the continual improvement and optimization of LNP formulations and novel ionizable lipids and lipid-like materials. Specifically, DLin-MC3-DMA has largely replaced commercial lipofection reagents as the preferred material for nucleic acid delivery and, in particular, siRNA (Jayaraman et al., 2012; Hou et al., 2021). This synthetic lipid not only serves as a standard delivery agent in vitro but has been used for in vivo delivery as well. For example, Onpattro®, comprising in key part Dlin-MC3-DMA, is the first siRNA drug approved by the United States Food and Drug Administration (FDA) (Akinc et al., 2019). While this lipid is considered the most reliable commercially available lipid carrier for nucleic acids, it is not optimized for mRNA or RNP delivery, and is limited in efficacy and tolerability by its non-degradability. As Dlin-MC3-DMA does not represent a perfect lipid carrier for CRISPR/Cas9-based cargoes, efforts have been made to engineer biodegradable lipids with improved pharmacokinetics (Maier et al., 2013). This research has resulted in clinically suitable mRNA delivery materials, including the lipid-like compounds SM-102 and ALC-0315 used in the mRNA-1273 and BNT162b vaccines against COVID-19 (Hassett et al., 2019; Hou et al., 2021). Several groups have generated combinatorial libraries of synthetic lipids and lipid-like materials using rational design techniques similar to those outlined in Figure 5. These libraries are summarized in Table 1. From these libraries, several novel ionizable lipids have been shown to deliver CRISPR/Cas9 reagents effectively. Several groups have demonstrated in vitro and in vivo gene editing using fluorescent reporter models, and some have extended their investigation to clinically-relevant genes, such as those overexpressed in tumor cells. These next generation lipids include branched-tail and bioreducible lipids to improve encapsulation, endosomal escape, editing efficiency and reduce toxicity when delivering Cas9-encoding mRNA as compared to DLin-DMA-MC3. The improvements outlined above demonstrate the advancing potential of LNPs for CRISPR/Cas9 therapies both in vitro and in vivo (Qiu et al., 2021). Most of these lipids, however, have not resolved the challenge of preferential particle accumulation in the liver, and other tissues remain difficult to target via systemic administration. This is advantageous only when the target tissue is the liver, and indeed there have been clinical examples of gene editing in the liver. Specifically, Gillmore et al. (2021) present clinical data showing therapeutic potential of an LNP composition containing the proprietary lipid NTLA-2001 to induce editing in the Ttr gene for patients with hereditary transthyretin amyloidosis (ATTR). Early clinical studies in humans have shown reductions from baseline serum levels of TTR protein up to 96%. Cheng et al. (2020) has taken combinatorial synthesis a step further and developed a combinatorial methodology of LNP composition to determine the impact of LNP constituents and their ratios on organ selectivity. With this methodology, LNP constituents were demonstrated to behave as selective organ targeting (SORT) molecules that influence the tissue-localization of gene editing after intravenous administration. When top-performing iPhos lipid (5A2-SC8) and dioleoyl-3-trimethylammonium propane (DOTAP) were used as model constituents, tissue-specific protein expression was tunable according to the ratio of the SORT molecule (in this case, DOTAP) in the LNP composition. Specifically, LNPs carrying Cas9 mRNA with 20% molar ratio of DOTAP induced gene editing exclusively in the liver, whereas LNPs with 50% DOTAP induced protein expression exclusively in the lung. The corresponding shift in editing distribution from liver to lung transgressed through the spleen at mid-range DOTAP percentages (Cheng et al., 2020). A similar trend was noted for the delivery of RNPs. This design strategy has larger implications for the clinical feasibility of systemically-administered nanoparticle-based gene therapy. Until this work, systemic administration for virtually all types of nanocarriers has resulted in preferential accumulation in the liver and limited application for targeting other tissues. Exceptions to this trend include LNPs functionalized with tumor-targeting moieties to enhance gene editing specifically in tumors, rather than other tissues. For example, a cationic lipid with a phenylboronic acid (PBA) moiety has been used to improve specificity of interaction of LNPs with the upregulated sialic acid expression at the surface of cancer cells (Tang et al., 2019). This lipid, called PBA-BADP, was used to deliver Cas9 mRNA and sgRNA targeting the GFP gene in GFP-expressing HeLa cells. PBA-functionalized LNPs induced GFP knockout of nearly 50%, as compared to less than 30% knockout induced by non-PBA functionalized LNPs (Tang et al., 2019). Tumor cells may alternatively be directly targeted using LNPs tagged with antibodies. Selective uptake of antibody-targeting LNPs administered intraperitoneally by disseminated tumors has demonstrated ∼80% gene editing in vivo (Finn et al., 2018). In an alternative approach, Liu et al. (2019b) report successful delivery using a bioreducible lipid/Cas9 mRNA nanoparticle, BAMEA-O16B (C56H111N3O6S6) in the treatment of human cervical cancer cells. The efficient delivery revealed genome editing present after just 24 h and knock-out of GFP with up to 90% efficiency. While these advancements have largely addressed issues with toxicity, encapsulation, and transfection efficiency for negatively-charged mRNA, the instability of RNPs in the acidic environment required for electrostatic complexation with ionizable lipid components presents a barrier to efficient complexation with cationic lipids to form LNPs (Walther et al., 2022). Notably, there has been limited success in delivering RNPs using LNP platforms, with a few exceptions, including those reported in Table 1. In addition, Walther et al. (2022) report the combination of a pH-neutral buffer and permanently cationic lipid components enabled successful encapsulation of RNPs with 19.2% HDR induced in vitro by RNPs encapsulated within LNPs composed of C12-200, 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), cholesterol, poly (ethylene glycol)-1,2-dimyristoyl-rac-glycerol (PEG-DMG), and DOTAP (Walther et al., 2022). This formulation method, along with those featured in Table 1, exemplify the ability to overcome challenges initially identified in the complexation of LNPs and provide a foundation upon which further strides can be made towards the broader clinical translation of LNP vehicles for gene therapies.
Despite the advances outlined above, challenges remain in designing nanocarriers that accommodate hard-to-package cargoes like Cas9 RNPs or that provide the stimulus-responsive control of tissue targeting, intracellular trafficking, and cargo release. Inorganic nanocarriers such as gold nanoparticles (AuNPs), mesoporous silica nanoparticles (MSNs), and metal-organic frameworks (MOFs) are appealing due to their versatility and ease of chemical functionalization. These attributes enable creative strategies to address these barriers to delivery. However, each of these types of particles presents with preferential accumulation in the liver and/or biocompatibility issues that limit their efficacy for systemically administered CRISPR/Cas9 therapies. Recent work in inorganic nanoparticle delivery has been largely focused on developing core-shell structures that incorporate organic components to circumvent these issues, and engineered stimulus-responsiveness or tissue-targeting strategies to control the localization of gene editing cargo (Figure 4). While MOFs are under rapid and intense investigation, this review will focus on AuNPs and MSNs due to their higher scalability.
The plasmonic properties of AuNPs confer a portfolio of targeting and release capabilities and are frequently leveraged in the design of complex nanocarriers for gene editing reagents. Mout et al. (2017) synthesized arginine-functionalized AuNPs, effectively generating positively-charged particles (Mout et al., 2017). By then tagging Cas9 with glutamate, forming a negatively-charged patch on the otherwise cationic protein, the group enabled complexation between Cas9 and the AuNPs to form nanoassemblies. The resulting nanoassemblies exhibited 90% delivery efficiency and indel efficiency in HeLa cells of 29–30% (Mout et al., 2017). Building on this work, Ray et al. (2018) demonstrated gene editing to knockout macrophage signal regulatory protein-α (SIRP-α) in macrophages to promote phagocytosis of cancer cells in vitro (Ray et al., 2018). Further, colloidal AuNPs have been developed for the codelivery of guide RNA and Cas9 with or without an ssODN. Guide RNAs were attached to the AuNP surface via oligo ethylene glycol (OEG) spacers with terminal thiol linkers, and Cas9 proteins were subsequently complexed to the tethered guide RNAs (Shahbazi et al., 2019). To enable further electrostatic complexation to an ssODN, the AuNP assembly was further coated with branched PEI. Treatment of hematopoietic stem/progenitor cells (HSPCs) with these nanoassemblies resulted in 17.6% total editing with 13.4% HDR at the CCR5 locus with minimal toxicity (Shahbazi et al., 2019). While these approaches work well in vitro, there are very few examples of AuNPs being applied for delivery and diagnostic applications in clinical trials as reviewed recently by Singh et al. (2018), and, to date no examples of the clinical translation of CRISPR-based gene editing using AuNP-based approaches have been reported (Singh et al., 2018). Common approaches to overcoming additional barriers to clinical in vivo stability, biocompatibility, and efficacy of AuNPs include the utilization of polymers or lipids to coat the AuNP, protect the cargo, and aid in endosomal escape. Lee et al. (2017) used an endosomal disruptive polymer, PAsp(DET), as a coating to accomplish these objectives. In this example, AuNPs were conjugated with glutathione linkers to DNA, which enabled the electrostatic complexation of Cas9 RNP and ssODN cargoes. After endosomal release promoted by the buffering effect of PAsp(DET), cytoplasmic conditions induced cleaving of the glutathione linker to release the cargo and enable gene editing, including HDR-mediated insertion of a ssODN template designed to convert blue fluorescent protein (BFP) to GFP in a BFP-expressing HEK reporter cell line (Lee et al., 2017). Lipids may also be used as coatings for AuNPs. Wang et al. (2018b) developed AuNPs functionalized with cationic TAT peptides to enable complexation with plasmid encoding Cas9 and gRNA-Plk-1 to form TAT peptide-modified gold nanoparticles (ACPs) (Wang et al. (2018b). These were subsequently encapsulated by a lipid composition including DOTAP, DOPE, cholesterol, and PEG anchored to 1,2-Distearoyl-sn-glycero-3-phosphoethanolamine (PEG2000-DSPE) to form lipid encapsulated-ACPs (LACPs). Apoptosis was induced in vitro, and in vivo mouse models showed tumor inhibition induced by treatment with LACPs. Compared to a PBS control, tumors injected with LACPs were reduced in size by 42% at the time of sacrifice. The LACPs outlined above induced much higher levels of gene editing and tumor inhibition when irradiated with near infrared (NIR) light, leveraging the plasmonic properties of AuNPs for the stimulus-responsive release of cargo, and importantly presenting a platform for controlling the location of gene editing even after systemic administration (Wang et al., 2018b). Chen et al. (2020) synthesized gold nanorods with a coating of polystyrene sulfonate (PSS) beneath an outer coating of β-cyclodextrin-polyethyleneimine (CD-PEI), which could then be complexed to a Cas9-encoding plasmid including a heat-inducible promoter (Chen et al., 2020). These particles, dubbed APCs, were used as an optogenetic switch for gene editing (Chen et al., 2020). Irradiating APC-treated tissue in the NIR induces plasmonic heating, thereby activating transcription of the plasmid. The group found that Cas9 expression was inducible via Western blot analysis as well as flow cytometry quantifying GFP knockout in GFP-expressing HEK 293Ts. In vivo mouse models showed peritumoral injection of APCs targeting the Plk1 locus to induce significant on-target mutation and reduction in tumor size only when the tumors were irradiated with NIR (Chen et al., 2020). This system enabled precise control of editing only at the sites of interest.
Silica nanoparticles are of interest for CRISPR/Cas9 gene therapies due to their tunability to respond to stimuli and their porosity, which enables high encapsulation efficiencies and co-delivery of small-molecule drugs (Xu et al., 2021). However, like AuNPs, in vivo administration of mesoporous silica nanoparticles (MSNs) presents challenges with stability of both carrier and cargo and poor control over release kinetics (Xu et al., 2021). To resolve these issues, more complex structures are being investigated for improving MSN efficacy. To date, while clinical trials are underway for MSN-based drug delivery, diagnostic, and theranostic applications as reviewed recently (Janjua et al., 2021), no CRISPR-based MSN therapies have reached this stage of clinical investigation. Similar to AuNPs, lipids and polymers are frequently used as coatings for mesoporous silica for the delivery of Cas9-encoding plasmids and RNPs. Noureddine et al. (2020) reports MSNs coated in DOTAP, DOPE, DSPE-PEG2000, and cholesterol for the delivery of RNPs to induce 10% gene editing both in vitro and locally in vivo after intracranial administration in mice (Noureddine et al., 2020). Lipids and polymers including PAMAM (Zhang et al., 2020), PDDA (Xu et al., 2021), and PEG (Wang et al., 2021) have been used to coat MSNs loaded with both a small molecule drug and RNPs. Liu used a similar lipid-coated MSN system to co-deliver a small molecule drug and RNPs (Liu et al., 2020). Tissue-targeting moieties may easily be conjugated to some of these coatings, including hepatocyte-targeting N-acetylgalactosamine (GalNAc) (Wang et al., 2021). For applications where target cells are not hepatocytes, chemical functionalization is one approach leveraged to avoid preferential accumulation in the liver. Liu et al. (2019b) reported coating RNP-loaded MSNs with PBA-modified PEI for tumor-targeting, then complexing the resulting polyplex with 2,3-dimethylmaleic anhydride (DMMA)-modified poly (ethylene glycol)-b-polylysine (mPEG113-b-PLys100/DMMA) to protect the cargo from degradation. With this system, in vitro and in vivo tumor-targeted gene editing was successfully induced. Alternatively, MSNs may be engineered to respond to stimuli for spatial and temporal control of gene editing after systemic administration. Silica-based up-conversion nanoparticles (UCNPs) are frequently leveraged to deliver gene editing reagents in a stimulus-responsive manner. Pan et al. (2019) synthesized lanthanide-doped UCNPs coated in SiO2 functionalized with UV-photocleavable 4-(hydroxymethyl)-3-nitrobenzoic acid (ONA) linkers directly to Cas9 RNPs and subsequently encapsulated within a PEI layer (Pan et al., 2019). The RNPs targeted Plk-1 to investigate the utility of these particles to inhibit tumor growth. These UCNPs upconvert incident biologically safe NIR to ultraviolet (UV) radiation, which subsequently results in cleavage of the linker to release the RNP from the UCNP (Pan et al., 2019). The group confirmed gene editing by knocking out GFP expression in GFP-transduced KB cells, and induced apoptosis by knocking out the Plk-1 gene in A549 cells. These results were corroborated in vivo mouse models, which displayed indels induced after intratumoral UCNP administration in tumor tissue and reduced tumor size compared to controls (Pan et al., 2019).
This review serves to summarize current approaches to optimizing the CRISPR/Cas9 system in both its cargo and methods of delivery, and the challenges those approaches aim to address. Recent advances in biotechnology developed for the safe and effective utility of CRISPR/Cas9 payloads have improved the outlook for clinical applications of gene editing. Modifications made to gene editing biomolecules to reduce their inherent toxicity and the risk of off-target effects operate synergistically with methods of delivery that have undergone significant technological improvements since their introduction. While broad clinical use of CRISPR/Cas9-based therapies is still on the horizon, many of the safety and scalability challenges that have formerly served as obstacles to clinical translation are actively being addressed. Ex vivo methods of gene delivery have undergone significant advancements and have demonstrated clinical applicability and effectiveness. Specifically, cell therapies involving CRISPR-based genetic modification of CAR T cells and hematopoietic stem cells are under clinical development and investigational trials for treating cancer, β-thalassemia, sickle cell anemia, HIV, and refractory B cell malignancies are underway (Hirakawa et al., 2020). Despite this rapid progress, barriers to efficient in vivo systemic delivery of CRISPR/Cas9 reagents and induction of therapeutic levels of gene editing in tissues of interest have not been completely overcome. CRISPR/Cas9 therapies undergoing interventional trials for direct use in vivo are extremely limited, including only an AAV-based application for Leber congenital amaurosis and a topical treatment for human papillomavirus (HPV)-related malignancies (Hirakawa et al., 2020). Creative and novel approaches to administering in vivo CRISPR/Cas9 therapies may be required to circumnavigate current barriers to systemic administration, achieving appropriate safety profiles, improving fiscal scalability, realizing delivery cargo and disease agnostic solutions that are robust and effective while being compliant with Good Manufacturing Practices remain of high concern to ensure equitable availability of emerging gene therapeutic interventions. While tools to improve gene editing are becoming standard practice in research laboratories, to achieve clinical translational goals for CRISPR/Cas9 gene therapies it is imperative that scientists in related fields of molecular biology, chemistry, medicine, and engineering continue to collaborate and stay up to date with recent advances. The reviewed literature indicates a fast-paced trajectory for CRISPR/Cas9-based therapeutics and technologies facilitated by multilevel and multifaceted approaches to reliably safe, scalable, and effective intracellular delivery. | true | true | true |
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PMC9549339 | Yuan Shen,Yuhao Chi,Shun Lu,Huijuan Lu,Lei Shi | Involvement of JMJ15 in the dynamic change of genome-wide H3K4me3 in response to salt stress | 26-09-2022 | jumonji demethylase,H3K4me3,JMJ15,WRKY46,WRKY70,salt stress | Post-translational histone modifications play important roles in regulating chromatin structure and transcriptional regulation. Histone 3 lysine 4 trimethylation (H3K4me3) is a prominent histone modification mainly associated with gene activation. Here we showed that a histone demethylase, JMJ15, belonging to KDM5/JARID group, is involved in salt stress response in Arabidopsis thaliana. Jmj15 loss-of-function mutants displayed increased sensitivity to salt stress. Moreover, knockout of JMJ15 impaired the salt responsive gene expression program and affected H3K4me3 levels of many stress-related genes under salt-stressed condition. Importantly, we demonstrated that JMJ15 regulated the expression level of two WRKY transcription factors, WRKY46 and WRKY70, which were negatively involved in abiotic stress tolerance. Furthermore, JMJ15 directly bound to and demethylated H3K4me3 mark in the promoter and coding regions of WRKY46 and WRKY70, thereby repressing these two WRKY gene expression under salt stress. Overall, our study revealed a novel molecular function of the histone demethylase JMJ15 under salt stress in plants. | Involvement of JMJ15 in the dynamic change of genome-wide H3K4me3 in response to salt stress
Post-translational histone modifications play important roles in regulating chromatin structure and transcriptional regulation. Histone 3 lysine 4 trimethylation (H3K4me3) is a prominent histone modification mainly associated with gene activation. Here we showed that a histone demethylase, JMJ15, belonging to KDM5/JARID group, is involved in salt stress response in Arabidopsis thaliana. Jmj15 loss-of-function mutants displayed increased sensitivity to salt stress. Moreover, knockout of JMJ15 impaired the salt responsive gene expression program and affected H3K4me3 levels of many stress-related genes under salt-stressed condition. Importantly, we demonstrated that JMJ15 regulated the expression level of two WRKY transcription factors, WRKY46 and WRKY70, which were negatively involved in abiotic stress tolerance. Furthermore, JMJ15 directly bound to and demethylated H3K4me3 mark in the promoter and coding regions of WRKY46 and WRKY70, thereby repressing these two WRKY gene expression under salt stress. Overall, our study revealed a novel molecular function of the histone demethylase JMJ15 under salt stress in plants.
Higher plants can adapt to changing environmental conditions in different ways via adjustments in gene expression. Epigenetic regulation of gene expression involving chromatin modification such as histone 3 lysine 4 trimethylation (H3K4me3) plays essential roles in plant response to environmental conditions (van Dijk et al., 2010; Foroozani et al., 2021). H3K4me3 has long been known as an active mark for gene transcription (Santos-Rosa et al., 2002; Li et al., 2007). Genome-wide analysis revealed that a large number of genes were marked by H3K4me3 which predominantly found at the promoter and 5′ end of genes in plants (Zhang et al., 2009). H3K4me3 was often associated with stress-induced gene expression by plant internal and external signals (Sokol et al., 2007; Kim et al., 2008; van Dijk et al., 2010), suggesting an active transcription role for H3K4me3. However, in some cases the increase of H3K4me3 was found to be lagged behind stressed gene activation (Kim et al., 2008; Hu et al., 2011), indicating that H3K4me3 might have a function to mark active gene status. In addition, H3K4me3 has also been found to play a role in transcriptional memory of stress-responsive genes in plants (Jaskiewicz et al., 2011; Ding et al., 2012; Kim et al., 2012, 2015). H3K4 methylation is mediated by the Trithorax group proteins (TRX), including five Trithorax-like (ATX) proteins and two ATX-related (ATXR) proteins in Arabidopsis (Ng et al., 2007). Arabidopsis ATX1, ATX4, and ATX5 were found to be necessary for abscisic acid (ABA) and dehydration stress responses (Ding et al., 2011; Liu et al., 2018). Histone methylation could be reversed by histone demethylases. Lysine Specific Demethylase 1 (LSD1) was the first identified histone demethylase to remove mono- and di-methyl groups from H3K4 (Shi et al., 2004). Jumonji C (jmjC) domain-containing proteins were the second known class of histone demethylases. JmjC proteins, conserved in plants, animals and fungi, catalyze histone lysine demethylation through a ferrous ion [Fe(II)] and a-ketoglutaric acid (a-KG)-dependent oxidative reaction (Tsukada et al., 2006). JmjC domain containing demethylases are divided into distinct groups including KDM2A/JHDM1A, KDM5/JARID, KDM4/JMJD2, KDM6/JMJD3, and KDM3/JMJD1/JHDM2, depending on their binding and catalytic specificities. In humans, the KDM5/JARID group demethylases specially catalyze H3K4me2/3 demethylation (Mosammaparast and Shi, 2010). The Arabidopsis genome encodes ∼20 jmjC domain-containing histone demethylases (JMJ11–JMJ31), among which six jmjC proteins (JMJ14, JMJ15, JMJ16, JMJ17, JMJ18, and JMJ19) belonging to KDM5/JARID group demethylate H3K4me1/2/3 (Lu et al., 2008; Sun and Zhou, 2008; Chen et al., 2011). JMJ14 demethylates H3K4me3 in vitro and represses floral integrator genes Flowering Locus T (FT) and Suppressor of overexpression of CO1 (SOC1) by removing H3K4me3 (Jeong et al., 2009; Lu et al., 2010; Yang et al., 2010, 2018). JMJ16 negatively regulates leaf senescence through repressing the positive regulators of WRKY53 and SAG201 by reducing H3K4me3 (Liu et al., 2019). JMJ15 and JMJ18 regulate flowering time by demethylating H3K4me3 at the locus of the floral repressor gene Flowering Locus C (FLC) (Yang et al., 2012a,b). In addition to the essential roles in plant development, JMJ15 and JMJ17 are also involved in stress response. The jmj17 loss-of-function mutants display dehydration stress tolerance and ABA hypersensitivity (Huang et al., 2019; Wang et al., 2021). In detail, JMJ17 regulates the stomatal closure and ABA response through modulating OPEN STOMATA1 (OST1) and ABI5 genes by demethylating H3K4me3 (Huang et al., 2019; Wang et al., 2021). Our previous results showed that JMJ15 participated in salinity stress response (Shen et al., 2014). Jmj15 gain-of-function mutants increased tolerance to salinity stress and down-regulated many genes encoding transcription regulators involved in stress responses (Shen et al., 2014). Although the overexpression of JMJ15 confers tolerance to salt stress, the molecular mechanism of JMJ15 mediated salt tolerance remains elusive. In the present study, we showed that two jmj15 loss-of-function mutant alleles (jmj15-3 and jmj15-4) revealed more sensitive phenotypes to salinity stress. Importantly, the jmj15 loss-of-function mutations led to up-regulation of many stress-related genes under salt condition rather than under normal condition. In addition, chromatin immunoprecipitation sequencing (ChIP-seq) showed that knockout of JMJ15 regulated H3K4me3 levels of many salt and water deprivation stress-related genes under salt-stressed condition. Furthermore, our results showed that JMJ15 directly bound to and repressed the genes of WRKY46 and WRKY70 that played negative roles in salt stress tolerance. Taken together, our data unravel a novel molecular function of JMJ15 in salt stress responsiveness, which is distinct from the function of other characterized jmjC genes in Arabidopsis.
In this study, Arabidopsis thaliana wild type Col-0 and mutant lines jmj15-1 (GABI_257F10), jmj15-2 (GABI_876B01), jmj15-3 (GABI-663C11), and jmj15-4 (GABI-229F03) in the Col-0 background were used. The insertional knock-out lines jmj15-3 (Shen et al., 2014) and jmj15-4 (Yang et al., 2012b) have been previously characterized. The gain-of-function T-DNA mutant lines jmj15-1, jmj15-2, and the over-expressing tagged line 35s-JMJ15-HA have been reported (Shen et al., 2014). The Arabidopsis seeds were surface-sterilized by 5% (w/v) sodium hypochlorite for 7 min, washed with 95% (v/v) ethanol twice, and then sown on 1/2 Murashige and Skoog (MS) medium. After stratification in darkness at 4°C for 2 days, seeds were transferred into a growth chamber (20°C) under white light (120 μmol m–2 s–1) in 16 h light photoperiods. Wild-type and mutant plants were grown together and their mature seeds were harvested at the same time to avoid differences in post-maturation that can affect seed germination. Seeds of each genotype were harvested as a single bulk consisted of at least five plants. Seeds were stored in open tubes inside a closed box and maintained in darkness with silica gel at 4°C until the experiments were performed.
For measuring seed germination, more than 100 seeds of each genotype (Col-0, jmj15-3, and jmj15-4) were sown on NaCl-infused media (1/2 MS medium with 0, 100, 150, and 200 mM NaCl, respectively). After stratification in darkness at 4°C for 2 days, the plates were transferred into a growth chamber under white light in 16 h light photoperiods. The germination (fully emerged radicle) rates were measured per day for a duration of 5 days. Each test was performed with more than three biological replicates.
Measure root elongation under salt stress mainly according to the previous protocol (Lee and Zhu, 2009). More than 50 seedlings of Col-0 and jmj15 mutation lines were sown on 1/2 MS medium. After stratification in darkness at 4°C for 2 days, the plates were moved to a vertical position in the growth chamber (16 h white light photoperiod, 20°C) for germination. The 4-day-old germinated seedlings were transferred onto vertical 1/2 MS agar plates supplemented with 0 m M NaCl, 50 m M NaCl, 100 mM NaCl and 150 mM NaCl, respectively. After 5 days with the salt treatment, the primary root length was measured and statistical significance was determined by two-sided t-test. Three replicates were performed for each line and treatment.
Ten-day-old wild type (Col-0) and jmj15-4 mutants Arabidopsis plants treated with NaCl (0 mM or 150 mM NaCl solution in 1/2 MS liquid medium) for 5 h were pooled for RNA extraction and transcriptomic analysis. Plants harvested from three independent cultures were used as the biological replicates. Total RNA was extracted with Trizol (Invitrogen, Carlsbad, CA, United States), and treated with DNase I (Promega, Madison, WI, United States) to remove the genomic DNA. Then the mRNA was enriched by using oligo(dT) magnetic beads and broken into short fragments (200 bp) using the fragmentation buffer. The first strand cDNA was synthesized by using a random primer. RNase H, DNA polymerase I and dNTPs were used to synthesize the second strand. The double-strand cDNA was purified with magnetic beads. cDNA ends were repaired and a nucleotide A (adenine) was added at the 3′-end. Finally, PCR amplification was performed with fragments ligated by sequencing adaptors. The Agilent 2100 Bioanalyzer and the ABI Step One Plus real-time PCR system were used to qualify and quantify the QC library. The library products were sequenced with the Illumina HiSeqX-ten platform, and the library construction and sequencing were completed at Novogene Corporation (Tianjin, China). Gene expression was defined by RSEM (Li and Dewey, 2011) and estimated by FPKM. Differential expression analysis between two conditions/groups was performed using DESeq R package. The resulting P-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate (Anders and Huber, 2010). The RNA-seq data were deposited to NCBI-SRA databases under the accession PEJNA822702.
Total RNA was extracted from plant seedlings using Trizol (Invitrogen, Carlsbad, CA, United States) according to the manufacturer’s instructions. RNA concentration was measured by using a Nanodrop. For RT-qPCR analysis, 2 μg of total RNA treated with DNaseI (RQ1, Promega, M6101, Madison, WI, United States) were used to synthesize first-strand cDNA with Oligo(dT)15 primers using ImPromII reverse transcriptase (M3104A, Promega, M3104A, Madison, WI, United States). RT-qPCR was performed with LightCycler 480 SYBR Green I Master mix on the LightCycler 480 (Roche, Mannheim, Germany). The reactions were performed in triplicate for each run and at least three biological replicates were carried out for each reaction. Transcript levels were calculated using the comparative Ct (threshold cycle) method and utilizing ACTIN2 as an internal control for data normalization. Primer sequences used in this study were summarized in Supplementary Table 1.
Chromatin immunoprecipitation (ChIP) experiments were carried out as described previously with minor modifications (Shen et al., 2015). Ten-day-old plants were treated with NaCl (0 mM or 150 mM NaCl solution in 1/2 MS liquid medium) for 5 h before harvest. About 4 g of plant seedlings were harvested, which were then cross-linked with 1% formaldehyde for 10 min under vacuum and ground into fine powder in liquid nitrogen. The chromatin DNA was isolated and sonicated in the 200–1000 bp range with Diagenode Bioruptor UCD-300. The sonicated chromatin was pre-cleared and incubated with anti-H3K4me3 (Millipore, 07-473, Darmstadt, Germany), anti-RNAPII (Abcam, ab5408, Cambridge, United Kingdom) or anti-HA (Sigma, H6908, St. Louis, MO, United States) antibodies loaded Dynabeads™ protein A (Invitrogen, #10002D, Carlsbad, CA, United States) at 4°C overnight. Subsequently, the immunoprecipitated DNA was decrosslinked and purified by using the MinElute PCR Purification Kit (Qiagen, #28004, Hilden, Germany) according to the manufacturer’s instruction. ChIP DNA was used for sequencing or qPCR. ChIP-qPCR was performed with three biological replicates, and results were calculated as the percentage of input DNA. Sequences of the primers used for ChIP-qPCR were listed in Supplementary Table 1.
At least 5 ng of each ChIP DNA was used to construct ChIP-seq library, and two biological replicates for each sample. The Illumina libraries were constructed using the ChIP-seq DNA Sample Prep Kit (Illumina) according to manufacturer’s protocol. The ChIP-seq library was sequenced by Novogene Corporation (Tianjin, China) on the Illumina HiSeq2500 sequencing system. Base calling and read quality control were performed following the standard Illumina protocol. Reads passing quality control were aligned to the Arabidopsis genome (TAIR10) using BWA (Burrows Wheeler Aligner) with default parameters and only uniquely mapped reads were kept (Li and Durbin, 2009). MACS2 (version 2.1.0) peak calling software was used to identify regions of enriched intervals over the background. A q-value threshold of 0.05 was used for all data sets. Differential enrichments were assessed by MACS2 (bdgdiff), with an FDR cutoff < 0.001. The differential histone modification regions were intersected with annotated genes to obtain the target genes using BED tools. The alignments were converted to wiggle (WIG) files. The data were then imported into the Integrated Genome Browser for visualization. The ChIP-seq data were deposited to NCBI-SRA databases under the accession PRJNA823378.
To explore the transcriptional level of genes involved in plant response to salt stress, we conducted RNA-seq analysis using wild type seedlings under normal or salt-stressed conditions (0 mM or 150 mM NaCl solution in 1/2 MS liquid medium for 5 h), each with three biological replicates. The RNA-seq results showed that the three biological replicates were all highly correlated (R = 0.91–0.99). Analysis of differentially expressed genes (DEGs) revealed that 5470 up-regulated genes (URGs) and 5393 down-regulated genes (DRGs) in wild type seedlings as a result of the salt stress (P < 0.05) (Figure 1A and Supplementary Table 2). Using the strict criteria (fold change > 4.0, P < 0.001), 619 URGs and 833 DRGs were found in salt treated versus normal growth seedlings (Figure 1A and Supplementary Table 2). Among the genes up-regulated by salt stress, inducible genes implicated in salt stress response in other studies were present, including COR15A (AT2G42540), COR15B (AT2G42530), RD20 (AT2G33380), RD29A (AT5G52310), RD29B (AT5G52300) (Figure 1B; Chen et al., 2010; Zheng et al., 2016; Yang et al., 2019). Increasing evidence has shown that transcriptional regulation directed by H3K4me3 is very important for environmental responses in plants (van Dijk et al., 2010; Huang et al., 2019; Foroozani et al., 2021). To reveal the possible regulatory role of H3K4me3 methylation in the plant response to salt stress, ChIP-seq was performed by using the wild type seedlings under normal and salt stress (the same conditions as the RNA-seq), each with two biological replicates. The results revealed that 21894 H3K4me3 methylation peaks in Col-0 samples under normal condition (Supplementary Table 3), while 24141 H3K4me3 peaks under salt stress treatment (Supplementary Table 4). The distribution of H3K4me3 was similar between normal and salt-treated seedlings, with the most enrichment occurring at the gene body (Figure 1C). In detail, most H3K4me3 amounts were found at exons (63–66%), followed by introns (16–19%) and 5′ untranslated regions (5′ UTR) (10%). Lower amounts of H3K4me3 were found at non-coding RNA (3.4%), intergenic region (3%) and 3′ UTR (1%) (Figure 1D), which was consistent with the previous data (Zhang et al., 2009; Huang et al., 2019). To determine whether/how salt stress-altered gene expression correlated with changes in H3K4me3, we examined the H3K4me3 changes for the 1452 genes with altered transcript abundance (|fold change| > 4.0, P < 0.001) (Supplementary Table 5). The plot analysis revealed a correlation between the H3K4me3 and transcript dynamic changes under salt stress (Pearson correlation coefficient R = 0.567, P < 0.01) (Figure 1E), indicating that H3K4me3 dynamics is associated with the transcript level of many genes involved in salt stress response. Totals of 2591 and 1905 genes were differentially hypermethylated and hypomethylated between salt and normal conditions (P < 0.05), respectively (Figure 1F and Supplementary Table 6). Gene ontology (GO) enrichment analysis revealed that the H3K4me3 changed genes under salt stress were categorized into ‘response to water deprivation,’ ‘response to abiotic stimulus,’ ‘response to abscisic acid,’ and ‘response to chemical’ (Figure 2A). In addition, the up-regulated salt-responsive genes (i.e., COR15A, COR15B, RD20, RD29A, RD29B) were found hypermethylated under salt stress condition by using the Integrated Genome Browser (Figure 2B). These results suggest that the H3K4me3 change is associated with the transcriptional change of the salt responsive genes during the stress process.
We have shown that gain-of-function mutants (jmj15-1 and jmj15-2) exhibited increased tolerance to salinity stress, whereas one allele of loss-of-function mutant (jmj15-3) exhibited increased sensitivity to salinity stress (Shen et al., 2014). To further confirm the response of jmj15 loss-of-function mutant to salt stress, we obtained another mutant allele jmj15-4. In jmj15-4, T-DNA was inserted in the 5th intron of JMJ15 (Figure 3A). RT-qPCR analysis revealed that the JMJ15 transcripts were abolished in both jmj15-3 and jmj15-4 alleles (Figure 3B). Both loss-of-function lines together with the wild type (Col-0) were tested for germination rates on normal MS media and MS supplemented with different salt concentrations. The germination rates were scored at different time points after 2 days. Seeds from three various harvests were tested. Under normal conditions, the germination rates of wild type and jmj15 loss-of-function mutants were more than 95%. When treated with salt, the germination rate of jmj15 loss-of-function mutants were lower than the wild type at different indicated salt concentration and time points (Figures 3C,D). Root elongation lengths were also measured to analyze the sensitivity of plants to the salt stress. The results revealed that after 5 days under normal condition, the root lengths of loss-of-function jmj15 and wild type plants were similar. However, the root lengths of jmj15 mutants were shorter than that of wild type after 5 days under various concentration of NaCl treatment (Figures 3E,F). Together, these results suggest that JMJ15 regulates the response to salt stress in Arabidopsis.
The developmental phenotype between jmj15-4 and wild type was highly significant different under salt stress (Figure 3). To explore the genome-wide transcriptional landscape directed by JMJ15, we conducted RNA-seq analysis of jmj15 loss-of-mutation (jmj15-4) and Col-0 under normal and salt stress conditions, each with three replicates. The total of 897 and 1852 DEGs were identified in jmj15-4 compared with Col-0 under normal and salt stress conditions, respectively (P < 0.05) (Figure 4A). Among 897 DEGs in jmj15-4 under normal condition, 393 were upregulated (URGs) and 504 were downregulated (DRGs) in jmj15-4 (Figure 4A and Supplementary Table 7), while among 1852 DEGs under salt stress, 1020 were URGs and 832 were DRGs in jmj15-4 (Figure 4A and Supplementary Table 8), suggesting that JMJ15 may mainly play a role as a transcriptional repressor during the salt responsive process. GO enrichment revealed that the URGs in jmj15/Col-0 under salt stress were enriched in response to stress, peptide metabolic process, flavonoid metabolic process, pigment synthetic process, and the DRGs were enriched in response to stress, response to organic substance, response to chemical stimulus, systematic acquired resistance (Figure 4B). URGs in jmj15/Col-0 under normal condition were enriched in response to stress, but no GO enrichment for DRGs (Figure 4B). These results suggest that loss of JMJ15 may mostly affect metabolism and the responsiveness to environmental stimuli of seedlings which is consistent with the previous result that overexpression of JMJ15 preferentially represses the stress regulatory genes (Shen et al., 2014). To investigate how the jmj15 mutation affects the salt responsive gene expression program, we compared DEGs in jmj15 mutation versus Col-0 under salt treatment (jmj15/Col-0 under salt) with that of Col-0 under salt versus normal condition (salt/normal in Col-0). Interestingly, we found that (507/1020, 49.7%) upregulated and (499/832, 55.6%) downregulated DEGs in jmj15/Col-0 under salt stress overlapped with the downregulated and upregulated DEGs in Col-0 under salt/normal respectively (Figure 4C red cycle and Supplementary Table 9). However, the overlap was much less between the upregulated (288/1020, 28.2%) and downregulated (142/832, 17.1%) DEGs in jmj15/Col-0 under salt stress with the upregulated and downregulated DEGs in Col-0 under salt/normal (Figure 4C green cycle). These data indicated that jmj15 mutation impaired the salt responsive gene expression program, that may explain the salt-stress-sensitive phenotype in jmj15 loss-of-function mutation. Further investigation of these 507 genes that were upregulated in jmj15/Col-0 under salt but downregulated in Col-0 under salt/normal found some key components of plant tolerance to stress, such as PRXIIF (AT3G06050), ERF73 (AT1G72360), PIP2B (AT2G37170), CAM1 (AT5G37780), LTP5 (AT3G51600), PDF1.2 (AT5G44420), PDF1.2B (AT2G26020), PDF1.3 (AT2G26010), LEA41/DI21 (AT4G15910), SAP18 (AT2G45640), ERD14 (AT1G76180), SESA (AT4G27170), EARLI1 (AT4G12480), GSTF9 (AT2G30860), GSTU26 (AT1G17190), GSTU20 (AT1G78370) (Figure 4D and Supplementary Table 9). The result suggested that loss of JMJ15 derepressed the expression of some stress-responsive genes, which was inhibited during the salt treatment. Similarly, we found some stress related genes such as CAT2 (AT1G58030), XTH6 (AT5G65730), XTH22/TCH4 (AT5G57560), HSFA2 (AT2G26150), NRT2.6 (AT3G45060), HSP70-2 (AT5G02490), COR15A (AT2G42540), COR15B (AT2G42530), NAC13 (AT1G32870), VSP2 (AT5G24770) that were upregulated in Col-0 under salt/normal but downregulated in jmj15/Col-0 under salt stress (Figure 4E and Supplementary Table 9). Together, the analysis suggested that JMJ15 was required for both gene activation and repression of the salt-responsive gene expression program.
To investigate whether JMJ15 is involved in the salt stress response by demethylating H3K4me3, we examined H3K4me3 patterns in the jmj15 loss-of-function mutants under normal and salt-stressed conditions by ChIP-seq. The result revealed that 21964 H3K4me3 methylation peaks in jmj15 mutation under normal condition (Supplementary Table 10), while 24273 H3K4me3 methylation peaks under salt stress treatment (Supplementary Table 11). The distribution pattern is similar in jmj15 to WT under both conditions (Figures 1D, 5A). However, totals of 722 and 1763 genes were differentially hypermethylated and hypomethylated in the jmj15 loss-of-function mutants under salt stress, respectively (P < 0.05) (Supplementary Table 12). Scatterplot analysis of increased expressed genes in jmj15/Col-0 under salt showed that most transcriptionally URGs were hypermethylated (Figure 5B and Supplementary Table 13). GO enrichment analysis of these hypermethylated and URGs in jmj15 under salt was the most enriched in response to stimulus (Figure 5C). By using Integrated Genome Browser, the H3K4me3 level was increased for some stimulus responsive genes such as EARLI (AT4G12480), DI21 (AT4G15910), ERD14 (AT1G76180) and LTP2 (AT2G38530) (Figure 5D and Supplementary Table 13), suggesting that the increased transcription of these stress related genes may be due to decreased demethylation activity of H3K4me3 in the jmj15 mutants. Of note, we found some transcriptional factors that both the transcription and H3K4me3 levels increased in jmj15 knockout mutations under salt condition such as some stress-responsive WRKY genes and ethylene-responsive-element binding factor genes (Supplementary Table 14), consisting with our previous data that overexpression of JMJ15 preferentially represses the stress regulatory genes, especially some transcription factors.
Interestingly, among these hypermethylated and URGs in jmj15 under salt stress, we found two known transcription factors, WRKY46 and WRKY70, that function as negative regulators in abiotic stress signaling in plants (Li et al., 2013; Ding et al., 2015; Chen et al., 2017). WRKY46 modulates the lateral root development in salt stress condition via regulation of ABA signaling and auxin homeostasis (Ding et al., 2015). WRKY70⋅modulates osmotic stress response by regulating stomatal aperture in Arabidopsis (Li et al., 2013). Meanwhile, WRKY70 was shown to be a direct target of ATX1 and positively regulated by ATX1-generated H3K4me3 (Alvarez-Venegas et al., 2007). Therefore, we hypothesized that JMJ15 might be involved in salt stress responses by modulating the H3K4me3 level of WRKY46 and WRKY70 genes. First, we examined the transcript level of these two WRKY genes in the jmj15 loss-of-function mutants (jmj15-3 and jmj15-4), jmj15 gain-of-function mutants (jmj15-1 and jmj15-2) and wild type (Col-0) under normal and salt-stressed conditions. The result showed that the transcript level of WRKY46 and WRKY70 was induced in wild type by salt stress. In jmj15 loss-of-function mutants, the transcript level of these two WRKY genes was enhanced compared to wild type under salt treatment, whereas the transcript level was obviously decreased in jmj15 gain-of-function mutations compared to wild type under salt treatment (Figure 6A). However, no discernible alterations were detected in jmj15 loss-of-function mutants under normal condition, but the transcript level of two WRKY genes were declined in jmj15 gain-of-function mutants under normal condition (Figure 6A), which was consistent with our previous result that overexpression of JMJ15 inhibited the expression of some transcription factors including some WRKY genes under normal condition (Shen et al., 2014). To confirm the role of JMJ15 in regulating chromatin status at the loci of WRKY46 and WRKY70 during the salt responsive process, we performed ChIP-qPCR analysis of the jmj15 loss-of-function mutants and jmj15 gain-of-function mutants (Figure 6B). The results showed that H3K4me3 level of WRKY46 and WRKY70 were obviously increased in jmj15-3 and jmj15-4 compared with wild type under salt stress, but decreased in jmj15-1 and jmj15-2 compared to wild type under normal and salt stress conditions (Figure 6C), suggesting that JMJ15 regulates the transcript levels of WRKY46 and WRKY70 genes by modulating their H3K4me3 levels. To investigate whether JMJ15 is directly associated with WRKY46 and WRKY70 genes, we analyzed the 35S-JMJ15-HA plants by ChIP-qPCR using anti-HA antibody (Shen et al., 2014). The analysis revealed that JMJ15-HA was enriched in WRKY46 and WRKY70 relative to the negative control (IgG), and JMJ15-HA binding levels were higher at the promoter and gene body under the salt stress compared to normal condition (Figure 6D). The results suggest that JMJ15 is recruited to the WRKY46 and WRKY70 genes and regulates their expression during the salt stress process. It has been established that H3K4me3 levels have a positive correlation with transcription rates and occupancy of activated RNA polymerase II (RNAPII) (Ardehali et al., 2011). We then tested whether the RNAPII occupancy at WRKY46 and WRKY70 was affected by JMJ15 following salt treatment. The results revealed that binding of RNAPII to WRKY46 and WRKY70 were increased in jmj15 loss-of-function mutants compared to wild type under salt stress (Figure 6E). Taken together, these results indicate that JMJ15 modulates H3K4me3 levels at the WRKY46 and WRKY70 loci and thus in turn affects RNAPII occupancy, which is essential for gene expression.
H3K4me3 has been implicated in the regulation of a number of environmental responses, such as drought stress, heat stress, submergence stress, and salt stress. For example, H3K4me3 abundance along with transcript levels of the inducible drought marker genes (RD29A, RD29B, RD20, and RAP2.4) were increased in response to drought (Kim et al., 2008). The genome-wide studies also showed that many genes up- or down-regulated by dehydration exhibited the similar increased or decreased H3K4me3 abundance, respectively (van Dijk et al., 2010; Zong et al., 2013). ATX1, H3K4me3 methyltransferase, was reported to involve in drought stress by affecting biosynthesis of ABA resulting from regulating H3K4me3 and transcript of NCED3 (Ding et al., 2011). Investigation of a number of stress-responsive genes in Arabidopsis has shown that several chromatin marks impact the responsiveness of salt-induced genes. For instance, salt stress led to enrichment of H3K4me3 and H3K9K14 acetylation, but decreased H3K9me2 at a subset of salt stress-responsive loci (Chen et al., 2010). Histone deacetylase 6 (HDA6) and HDA9 led to increased H3 acetylation at salt-inducible genes in hda6 mutants compared to wild type (Chen et al., 2010; Zheng et al., 2016). Interestingly, mutation of HDA6 also abolished H3K4me3 enrichment of ABA-induced loci (Chen et al., 2010). A recent study showed that salt stress altered the distribution of H3K4me3 in a tissue specific manner. In response to salt, rice seedlings exhibited H3K4me3 decreases and increases in exons and introns respectively, whereas only exons decrease of H3K4me3 in roots (Zheng et al., 2019). In our study, the distribution pattern of H3K4me3 was similar between normal and salt-treated seedlings. However, when compared the H3K4me3 level and transcript dynamic abundance for some transcript changed genes (| fold change| > 4.0), there was a correlation between the H3K4me3 and transcript dynamic changes under salt stress (Figure 1E). In addition, the H3K4me3 peak difference associated genes under salt stress were enriched in response to stress (Figure 2). These results indicate that H3K4me3 dynamics is associated with the transcript level of many genes involved in salt stress response.
In humans, KDM5/JARID group proteins are active histone H3K4me1/2/3 demethylases (Lu et al., 2008; Sun and Zhou, 2008). In Arabidopsis, six proteins (JMJ14-19) have been identified as members of this group based on phylogenetic analysis. Among these, JMJ14, JMJ15, JMJ16, JMJ18 harbor JmjN, JmjC, C5HC2, FY-rich N-terminus (FYRN), and FY-rich C-terminus (FYRC) domains. By contrast, JMJ19 harbors only JmjN, JmjC, and C5HC2 domains, whereas JMJ17 harbors JmjC, zf-C5HC2, PLU-1, and PHD domains (Lu et al., 2008). JMJ14, JMJ15, and JMJ18 play important roles in regulating flowering by reducing H3K4me3 abundance at various flowering regulatory genes. In addition to regulating the transition to flowering, Arabidopsis demethylases also play roles in RNA silencing (Searle et al., 2010); circadian clock (Song et al., 2019); defense (Li et al., 2020); senescence (Liu et al., 2019); de-etiolation process (Islam et al., 2021), and dehydration stress (Huang et al., 2019). JMJ17 played a role in dehydration stress by directly binding to OST1 and demethylating H3K4me3 levels (Huang et al., 2019). JMJ17 also regulates ABA responsive genes by interacting with WRKY40 (Wang et al., 2021). Our data showed that JMJ15 involved in salt stress by directly binding to the chromatin and regulating the expression of WRKY46 and WRKY70 genes. It seems that JMJ17 did not function in salt stress response as jmj17/jmj15 double mutations showed the similar salt stress response phenotype as jmj15 single mutant while jmj17 single mutant did not show discernible phenotype of salt stress response compared to wild type (Huang et al., 2019). These results indicate that these two KDM5/JARID histone demethylases function in different physiological processes without functional redundancy, which might be explained by their existing different domains and various target genes.
WRKY transcription factors, as a large family of plant transcription factors, participate in a variety of biological processes, including root growth, the quality of blossom clusters, senescence of leaf, fruit maturation, resistance to pathogens, abiotic stress response (Chen et al., 2017; Viana et al., 2018; Wang et al., 2020; de Bont et al., 2022; Goyal et al., 2022). WRKY gene family members were categorized into three groups (Rushton et al., 2010). WRKY46 and WRKY70 belonged to the group III with one WRKY domain and CCHC zinc finger motif, which played critical roles in the regulation of biotic stress response (Li et al., 2006; Hu et al., 2012). Furthermore, WRKY46 and WRKY70 acted as essential regulators in abiotic stress response which had also been demonstrated (Li et al., 2013; Ding et al., 2014; Chen et al., 2017). WRKY46 was found to negatively regulate plant responses to abiotic stress as the overexpression of WRKY46 resulted in hypersensitivity to drought and salt stress with a higher rate of water loss (Ding et al., 2014). Similarly, WRKY70 functions as negative regulator in drought stress and osmotic stress response by affecting water retention and stomatal conductance (Li et al., 2013; Chen et al., 2017). In our study, we found that the expression of WRKY46 and WRKY70 were negatively regulated by JMJ15 under salt stress (Figure 6A), which was consistent with the hypersensitivity of JMJ15 loss-of-function mutants to salt stress response. Furthermore, we found that JMJ15 bound to the chromatin of WRKY46 and WRKY70, and the enrichment was slightly induced under salt stress treatment (Figure 6D). Notably, overexpression of JMJ15 led to decrease the transcript levels of WRKY genes as well as H3K4me3 levels at these loci. According to publicly available microarray data (Winter et al., 2007), the expression of JMJ15 was low but rapidly induced by salt treatment (0.5–1 h), while WRKY46 and WRKY70 were induced at later time (3–6 h) (Supplementary Figure 1). These data suggest that JMJ15 may mainly repress the gene expression of WRKY46 and WRKY70 at the early stage of salt stress. Our results showed that H3K4me3 levels increased substantially at the WRKY46 and WRKY70 genes after 5 h salt treatment. This result suggests the existence of H3K4me3 methyltransferases and other chromatin remodelers that may also modulate the chromatin of WRKY46 and WRKY70 genes during the salt stress process. WRKY70 was previously reported as one target gene of H3K4me3 histone methyltransferase ATX1 (Ding et al., 2011, 2012). The SUMO E3 ligase, SIZ1 was found to modulate transcript and H3K4me3 level at the WRKY70 gene (Miura et al., 2020). However, it is not excluded other chromatin remodelers regulate H3K4me3 abundance and the transcript levels of WRKY46 and WRKY70 genes. Further studies should be conducted to understand how JMJ15 cooperates with other chromatin remodelers to regulate target genes.
The data presented in the study are deposited in the NCBI-SRA repository, accession number PRJNA822702 https://www.ncbi.nlm.nih.gov/bioproject/PRJNA822702 and PRJNA823378 https://www.ncbi.nlm.nih.gov/bioproject/PRJNA823378.
YS, YC, and LS designed the research and analyzed the data. YS, YC, SL, HL, and LS performed the experiments. YS and LS wrote the manuscript. All authors have read and approved the final manuscript. | true | true | true |
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PMC9549651 | Zhaoyi Liang,Lu Liu,Ruixia Gao,Chengchuan Che,Ge Yang | Downregulation of exosomal miR-7-5p promotes breast cancer migration and invasion by targeting RYK and participating in the atypical WNT signalling pathway | 09-10-2022 | Breast cancer,Exosome,miR-7-5p,RYK,EMT,Atypical WNT pathway | Background Current studies show that exosomal miRNAs become an important factor in cancer metastasis. Among the many miRNA studies, miR-7-5p has not been thoroughly investigated in breast cancer metastasis. Methods Bioinformatic screening was performed using extant data from the GEO database, and miR-7-5p expression levels in breast cancer cell lines and exosomes were further examined using real-time quantitative PCR (qRT-PCR). The extracted exosomes were characterised by transmission electron microscopy (TEM), particle size analysis and marker protein determination. Cell migration and invasion were then examined using wound healing assays and Transwell assays, respectively. Correlation between miR-7-5p and receptor-like tyrosine kinase (RYK) was analysed by luciferase reporter. The effect of miR-7-5p against RYK-related downstream factors was verified using western blot assays. Results In this study, we found that the expression of miR-7-5p was significantly different in exosomes secreted from breast cancer cell lines with different high and low invasiveness. Further experiments revealed that miR-7-5p has an important role in inhibiting the migration and invasion of breast cancer. In terms of mechanism of action, miR-7-5p was found to target the RYK, leading to its reduced expression, which in turn caused a reduction in the phosphorylation level of the downstream factor JNK. Reduced levels of phosphorylated JNK factors lead to reduced levels of phosphorylation of c-Jun protein, which in turn leads to increased expression of EMT transcription factors, thereby inhibiting the epithelial–mesenchymal transition (EMT) process to suppress the invasion of breast cancer. Conclusion Thus, we demonstrated that exosomes loaded with high levels of miR-7-5p emitted from less aggressive breast cancers can participate in the atypical WNT pathway by targeting the RYK gene and thus inhibit breast cancer metastasis. Supplementary Information The online version contains supplementary material available at 10.1186/s11658-022-00393-x. | Downregulation of exosomal miR-7-5p promotes breast cancer migration and invasion by targeting RYK and participating in the atypical WNT signalling pathway
Current studies show that exosomal miRNAs become an important factor in cancer metastasis. Among the many miRNA studies, miR-7-5p has not been thoroughly investigated in breast cancer metastasis.
Bioinformatic screening was performed using extant data from the GEO database, and miR-7-5p expression levels in breast cancer cell lines and exosomes were further examined using real-time quantitative PCR (qRT-PCR). The extracted exosomes were characterised by transmission electron microscopy (TEM), particle size analysis and marker protein determination. Cell migration and invasion were then examined using wound healing assays and Transwell assays, respectively. Correlation between miR-7-5p and receptor-like tyrosine kinase (RYK) was analysed by luciferase reporter. The effect of miR-7-5p against RYK-related downstream factors was verified using western blot assays.
In this study, we found that the expression of miR-7-5p was significantly different in exosomes secreted from breast cancer cell lines with different high and low invasiveness. Further experiments revealed that miR-7-5p has an important role in inhibiting the migration and invasion of breast cancer. In terms of mechanism of action, miR-7-5p was found to target the RYK, leading to its reduced expression, which in turn caused a reduction in the phosphorylation level of the downstream factor JNK. Reduced levels of phosphorylated JNK factors lead to reduced levels of phosphorylation of c-Jun protein, which in turn leads to increased expression of EMT transcription factors, thereby inhibiting the epithelial–mesenchymal transition (EMT) process to suppress the invasion of breast cancer.
Thus, we demonstrated that exosomes loaded with high levels of miR-7-5p emitted from less aggressive breast cancers can participate in the atypical WNT pathway by targeting the RYK gene and thus inhibit breast cancer metastasis.
The online version contains supplementary material available at 10.1186/s11658-022-00393-x.
In recent years, breast cancer has been increasing in incidence each year and has become the number one killer threatening women’s health [1, 2]. Breast cancer often results in death due to the uncontrollable spread of tumour cells, causing a decline, or even failure, in the function of other organs [3, 4]. Despite the current advances in the treatment of primary breast cancer, there is as yet no effective treatment for metastatic breast cancer. Since 90% of breast cancer-related deaths are caused by metastatic breast cancer, a clearer insight into the mechanisms of breast cancer metastasis is important for the development of effective treatments for metastatic breast cancer [5]. Exosomes are extracellular vesicles approximately 40–120 nm diameter that are separated from cells and are present in body fluids (serum, urine, etc.) [6, 7]. The exosome was thought to function primarily as an intracellular waste remover when it was first discovered [8], but as research has continued, more and more studies have revealed that its function is not so simple. Exosomes can be loaded with a large number of biologically active molecules (small non-coding RNA, mRNA, DNA, proteins, etc.) released by cells into body fluids, accompanying the flow of body fluids and binding to target cells membranes to release their contents into the target cells, acting as intercellular information transfer [8–10]. MicroRNAs (miRNAs) are non-coding single-stranded RNA molecules of up to 22 nucleotides, which are essential components of the exosome. It induces protein translation inhibition in an unknown manner, primarily by complementary binding to the 3′ non-coding region (3′ UTR) portion of the target mRNA target, which in turn inhibits protein synthesis and regulates intracellular processes by modulating the translation of a set of key mRNAs [11, 12]. Since the first miRNA was discovered in 1993, a steady stream of studies has shown that human miRNAs are instrumental in a variety of cancers [13]. Exosomal miRNAs also reflect to some extent the expression pattern of dysregulated miRNAs in cancer cells. Among these, those miRNAs that are delivered by exosome loading have also been found to be up or down regulated in expression in different tumours, involved in various regulatory mechanisms of cancer growth, apoptosis and metastasis [14, 15]. In the GSE114329 dataset, by analysing the differentially expressed miRNAs of MDA231 EXO and MCF7 EXO, we found that hsa-miR-7-5p was highly expressed in exosomes secreted by low-invasive breast cancer cells. Notably, hsa-miR-7-5p has been shown to be a potential oncogenic factor involved in regulating the biology of many cancer development processes, including colorectal [16], liver [17, 18], gastric [19] and lung cancers [20]. It has also been found in some studies to have a role in drug resistance in breast cancer [21, 22]. However, research on the role and molecular mechanisms of hsa-miR-7-5p in breast cancer metastasis is limited. Therefore, we chose to further investigate the specific molecular mechanisms of hsa-miR-7-5p in breast cancer metastasis. We validated a novel target of hsa-miR-7-5p, RYK, and demonstrated the ability to further influence the JNK-mediated atypical WNT signalling pathway. This offers new ideas for the treatment of metastatic breast cancer.
The GSE114329 dataset was searched in the GEO database, and two subsets of the MDA231 EXO and MCF7 EXO were selected for bioinformatic analysis. After downloading the raw data from the dataset, the raw data were filtered to remove splicing and decontamination to obtain clean reads which are compared with the reference genome for subsequent information analysis. Bioinformatics analysis was carried out by Shandong Unhelix Biotechnology Corporation.
The two human breast cancer cell lines used in this study, MDA-MB-231 (TCHu227) and MCF7 (TCHu74), were purchased from Dalian Meilun Biotechnology Corporation. These cells were assayed for mycoplasma, and no mycoplasma contamination was found in any of them. Both cells were cultured in high-sugar DMEM medium (Solarbio, Beijing, China) comprising 10% fetal bovine serum (Biological Industries, Kibbutz Hulda, Israel) in a cell culture incubator at 5% CO2 humidity and 37 °C. To obtain cancer-derived exosomes unaffected by fetal bovine serum exosomes, cells were also cultured in high-sugar DMEM medium containing 10% exosome-free fetal bovine serum (System Biosciences, CA, USA). The cells were cultured to the logarithmic stage of growth for the experiment.
The cell culture supernatant was collected during the cell culture process, and the cell culture supernatant was centrifuged (Sigma, Germany) at high speed: 300g at 4 °C for 10 min, the supernatant was continued at 2000g at 4 °C for 15 min and then the supernatant was centrifuged at 10,000g at 4 °C for 30 min. Ultracentrifugation (Beckman Coulter, USA) was then performed: the supernatant was centrifuged at 110,000g for 90 min at 4 °C, then the supernatant was discarded and the precipitate was resuspended in pre-cooled PBS and continued to be centrifuged at 110,000g for 90 min at 4 °C. The precipitate was resuspended in appropriate PBS and stored in a −80 °C refrigerator.
The extracted exosomes were observed for their morphological characteristics by transmission electron microscopy (TEM). The exosome suspension was suspended as droplets on a copper grid for 15 min, then the droplets were taken up by filter paper, followed by a drop of 4% phosphotungstic acid stain for 2 min. Afterwards, the staining solution was blotted away with filter paper. The copper grids were allowed to dry overnight and then observed using TEM (JEOL, Japan).
The granulometry of the extracted exosomes was analysed using a nanoparticle size and zeta potential analyser (Malvern Panalytical, UK). The exosome suspension was diluted and placed in a quartz cuvette to measure the particle size.
Cells were inoculated in six-well plates at 2 mL per well (5 × 105 cells/mL) and incubated for 24 h. Exosomes were labelled using Dio stain (Coolaber, Beijing, China). Following the instructions, the Dio staining solution was first diluted and then mixed with the exosome suspension and incubated at 37 °C for 30 min protected from light. To remove excess dye, the stained exosomes were centrifuged at 110,000g for 90 min at 4 °C. The precipitate was then resuspended in PBS and co-incubated with cells for 3 h, and cellular uptake was observed using two-photon confocal microscope (LSM 880 NLO, Germany).
The digested cells were inoculated in six-well plates (1 × 106 cells per well) and incubated until the cells had grown to about 80% in each well, then three monolayers of cells were scraped at medium distances in each well with the tip of a 10 μL gun. These were washed in PBS twice, and new cell culture medium was added. Then the width of the scratch was measured with an inverted microscope (Olympus, Japan). The cells were treated accordingly and incubated for a further 48 h and the width of the scratch was measured again. Cell migration was assessed by wound healing rate: wound healing rate = (0 h scratch width − 24 h scratch width)/0 h scratch width × 100%.
Transwell chambers with an 8-μm-pore-size polycarbonate membrane at the bottom were used for detecting the migratory and invasive capacity of the cells. Transfected cells (2 × 105) were resuspended in serum-free DMEM medium and added to the upper chamber (matrix gel coated or uncoated), and then 750 μL of DMEM culture medium containing 10% serum was added to the lower chamber. After 24 h incubation at 37 °C in 5% CO2, the cells were fixed in 4% paraformaldehyde (Meilunbio, Dalian, China) for 2 min and then in methanol for 20 min. Finally, the cells were stained with 0.1% crystalline violet stain for 15 min, and then the non-migrated cells and the stromal gel coating were gently scraped off the interior of the chambers with a cotton swab and placed on a slide for imaging and counting of the migrated cells under a microscope.
During cell transfection, all oligonucleotides and vectors were synthesised by GenePharma (Shanghai, China), including RYK small interfering RNA (siRYK) and its control (siNC), miR-7-5p mimic and inhibitor or its control (miR-NC mimic and miR-NC inhibitor). Cells were transfected using Lipofectamine 3000 (Mei5bio, Beijing, China) or LipoRNAiMAX (Mei5bio) according to the manufacturer’s requirements. Transfections were assayed after 48 h of normal culture. The sequences of miRNA mimics and inhibitors are shown in Additional file 1: Table S1.
RNAiso (Takara Bio, Japan) for small RNA and RNAiso (Takara Bio, Japan) for plus were used to extract miRNA and total RNA from cells and exosomes. miRNA 1st Strand cDNA Synthesis Kit (Vazyme Biotech, Nanjing, China) and HiScript II 1st Strand cDNA Synthesis Kit (Vazyme Biotech) were used to perform reverse transcription of miRNA and mRNA. RNA levels were quantified using SYBR Green stain (Vazyme Biotech) on an CFX 96Touch (Bio-Rad, USA) for real-time analysis. Real-time analysis was performed using SYBR Green on an CFX 96Touch according to the following protocol. Protocol for miRNA: 95 °C for 5 min, 40 cycles including 95 °C for 15 s and 60 °C for 20 s, 72 °C for 40 s. Protocol for mRNA: 95 °C for 5 min, 40 cycles including 95 °C for 10 s and 60 °C for 30 s. The expression levels of intracellular and exosomal miRNAs were normalised to U6. The expression levels of intracellular mRNAs were normalised to GADPH. Primer sequences are listed in Additional file 1: Table S2.
Cells or exosomes were first lysed with Western and IP Cell Lysis Solution (Coolaber) and incubated on ice for 15 min, and then the supernatant was gathered by centrifugation. Protein concentration was determined via the BCA protein assay kit (Meilunbio) for quantification. Protein samples were separated on 10% SDS–polyacrylamide gels, protein bands were transferred onto 0.45 µm PVDF membranes (Millipore, Massachusetts, USA). The PVDF films were then sealed with 5% skimmed milk powder (Bio-Rad). The closed PVDF membrane was incubated at 4 °C overnight with the corresponding primary antibody, washed with TBST buffer and incubated with secondary antibody (Proteintech, Wuhan, China) for 4–5 h at 4 °C. Washing with TBST buffer continued at the end of the secondary antibody incubation, followed by observation of the protein bands on the membrane using ECL luminescent solution (Meilunbio) and an imaging system (Bio-Rad). The primary antibodies included: TSG101 (1:20,000, cat. no. 67381-1-Ig), Alix (1:10,000, cat. no. 67715-1-Ig), CD63 (1:10,000, cat. no. 67605-1-Ig), RYK (1:1000, cat. no. 22138-1-AP), E-cadherin (1:5000, cat. no. 20874-1-AP), N-cadherin (1:6000, cat. no. 66219-1-Ig), ZEB1 (1:1000, cat. no. 21544-1-AP), Phospho-JNK (1:2000, cat. no. 80024-1-RR), Phospho-c-Jun (1:2000, cat. no. 28891-1-AP) and β-actin (1:10,000, cat. no. 66009-1-Ig) were obtained from Proteintech.
Using the Biology website (http://www.targetscan.org) to predict the binding site of miR-7-5p to RYK. The pmirGLO vectors for RYK-WT and RYK-MUT were then constructed (GenePharma). Logarithmic growth phase MDA-MB-231 cells were inoculated onto 12-well plates at a density of 5 × 105 cells per well. The miR-NC mimics or miR-7-5p mimics, RYK-WT and RYK-MUT, were transfected into MDA-MB-231 cells when cell confluency reached 70%. The reporter plasmid content was 2 µg per well, while miR-7-5p mimics or miR-NC were transfected at a total of 40 pmol per well. After 48 h of transfection, cell lysis was performed and luciferase activity was measured by the Luciferase Assay Kit (Meilunbio).
Data are presented as mean ± standard deviation (SD) (n = 3). For comparisons between the two groups, Student’s t-test was used to determine the difference between the means of the normal distribution. Significance analysis was performed on all data using GraphPad Prism 5 (San Diego, CA, USA) software, and probability levels of < 0.05 were considered significant.
The finding that cancer cells secrete more exosomes than normal cells further suggests that exosomes secreted by cancer cells may play a central role in their metastatic mechanism. To investigate the role of breast cancer-derived exosomes in breast cancer migration and invasion, exosomes first need to be isolated. We cultured two breast cancer cell lines, MDA-MB-231 cells and MCF7 cells, using a medium containing fetal bovine serum without exosomes. After collecting the cell cultures and extracting the exosomes using differential centrifugation, they were observed using transmission electron microscopy. The classical morphology of exosomes in a homogeneous cup-like structure was observed as shown in Fig. 1A. We examined the particle size of the extracted material using a nanoparticle size and zeta potential analyser and found that most of the particles were around 100 nm in size (Fig. 1B). The presence of these three marker proteins was further demonstrated using antibodies to CD63, TSG101 and Alix (Fig. 1C). All these results indicated that the extracted vesicular structures were indeed exosomes. After isolation of the exosomes, we co-cultured MCF7-derived exosomes with MDA-MB-231 cells and MDA-MB-231-derived exosomes with MCF7 cells. The co-cultured cells were also subjected to a wound healing assay to verify whether there were some functional differences between the two different exosomes. Furthermore, to determine that exosomes from different sources could enter different cells, we first labelled the extracted exosomes with Dio staining and then observed them with a two-photon laser confocal microscope. The results showed that exosomes were able to enter cells of different origins (Fig. 1D). And the results of the wound healing assay also showed that highly invasive breast cancer-derived exosomes promoted cell migration more than less invasive ones (Fig. 1E).
It is well known that miRNAs from cancer-derived exosomes are important regulatory molecules that mediate the link between cancer cells and host cells, so we investigated whether differentially expressed miRNAs within exosomes from different sources were responsible for mediating the functional differences between the two. We used the GSE114329 dataset from the GEO database to screen for differentially expressed miRNAs in two subsets of MDA231 EXO and MCF7 EXO by bioinformatics analysis. Nine relatively high and nine relatively low miRNAs were screened in exosomes produced by MDA-MB-231 cells (Fig. 2A). Several miRNAs with large differences in the replicate data were further excluded, several miRNAs that did not show significant differences probably owing to experimental reasons were selected, and finally eight miRNAs that were relatively highly expressed in exosomes produced by MDA-MB-231 cells and five miRNAs that were relatively lowly expressed were selected (Fig. 2A; Additional file 1: Table S3). We used qRT-PCR to validate the expression of several miRNAs in cells and exosomes. The experiments showed that hsa-miR-7-5p and hsa-miR-100-5p were most clearly different in cells and exosomes (Fig. 2B, C). We first selected hsa-miR-7-5p as our study subject. It was clear that hsa-miR-7-5p was significantly more expressed in low-invasive cells and exosomes than in highly invasive cells and exosomes.
To further determine whether microRNAs function in dependence on exosomes for delivery, we used transfection experiments to increase or decrease intracellular expression of miR-7-5p. Cell cultures of transfected cells were then collected, and the exosomes released from the transfected cells were isolated. Whether changes in intracellular miR-7-5p levels cause corresponding changes in miR-7-5p within the exosomes was investigated by qRT-PCR assay. The experiments conclusively demonstrated that an increase in intracellular miR-7-5p also increased the amount of miR-7-5p in the exosomes they released, and similarly, a decrease in miR-7-5p expression led to a decrease in miR-7-5p expression in the exosomes the cells released (Fig. 3A). This suggests that intracellular miR-7-5p acts through exosomal delivery, at least to some extent. We next investigate what role miR-7-5p plays in the intercellular delivery of breast cancer. We used wound healing assays and Transwell assays to investigate whether miR-7-5p has an effect on the migration invasion of breast cancer cells. We first verified that both mimics and inhibitors had been transfected into the cells within 48 h by qRT-PCR (Fig. 3B, C). The results of the wound healing and Transwell assays showed that the migration invasion ability of breast cancer cells in the miR-7-5p mimic group was significantly reduced, while the migration invasion ability of breast cancer cells in the miR-7-5p inhibitor group was significantly increased (Fig. 3D–G). This demonstrated that miR-7-5p significantly depressed breast cancer migration and invasion, which corresponds to our previous demonstration that miR-7-5p is highly expressed in low-invasive breast cancer cell lines and their exosomes, but lowly expressed in high-invasive breast cancer cell lines and their exosomes.
To further investigate the specific molecular mechanism by which miR-7-5p presents a significant inhibitory effect in breast cancer migration invasion, we utilised four miRNA target gene prediction software (miRTarBase, miRDB, TargetScan, miRWalk) to predict candidate target genes for miR-7-5p. We screened 41 candidate target genes (Additional file 1: Fig. S1), and then genes associated with tumour cell migration and invasion were included as further screening requirements. We finally identified the RYK genes with high scores as possible target genes for miR-7-5p. We next used only highly invasive MDA-MB-231 cells as our study subjects. We predicted the binding site for miR-7-5p in the 3′ UTR of the RYK gene (wild type) and targeted it for mutation (mutant type) and constructed plasmids for transfection (Fig. 4A). The experimental results showed that co-transfected miR-7-5p mimics significantly reduced reporter gene expression after the RYK wild type 3′ UTR, whereas no change in reporter gene expression was observed in the mutant group (Fig. 4B). Therefore, we concluded that RYK is a direct target of miR-7-5p. Consistent with the outcome of the dual luciferase reporter gene assay, the RYK gene also showed markedly reduced transcript levels and protein expression levels following transfer of miR-7-5p mimics (Fig. 4C, D). Our further in vitro experiments showed that RYK knockdown significantly inhibited the migratory and invasive ability of MDA-MB-231 cells compared with the control group. This result was identical to that obtained after treatment using miR-7-5p mimic. However, the inhibitory effect after RYK knockdown was reversed to some extent by miR-7-5p inhibitor (Fig. 4E, F). Thus, it is evident that exosomal miR-7-5p inhibits the migratory invasion of breast cancer to some extent by targeting the RYK gene.
Numerous studies have demonstrated that the migratory and invasion of breast cancer is closely related to the development of EMT. Our experiments also show that transfection of miR-7-5p mimics promotes the expression of E-cadherin and inhibits the expression of N-cadherin (Fig. 5A). Thus, miR-7-5p can inhibit the development of EMT. It has also been demonstrated that JNK and c-Jun in the atypical WNT signalling pathway, in which RYK is involved, can be involved in EMT development [23], which prompted us to investigate whether JNK and c-Jun, which are downstream factors of the RYK receptor, can be affected by miR-7-5p. We found that downregulation of miR-7-5p in breast cancer cells promoted a cascade response of the atypical WNT pathway, that is, phosphorylation of JNK and c-Jun proteins (Fig. 5B). Phosphorylated c-Jun protein inhibits the expression of the EMT core transcription factor ZEB1 (Fig. 5B), thereby suppressing the expression of E-cadherin and promoting the expression of N-cadherin, thereby facilitating the EMT process and promoting breast cancer metastasis. Ultimately, we demonstrated that miR-7-5p can inhibit breast cancer migration invasion by targeting the RYK gene, which is involved in the JNK-mediated atypical WNT signalling pathway.
Breast cancer is currently the leading malignancy threatening women’s mortality worldwide [24]. Metastatic malignant breast cancer accounts for 20–30% of breast cancer cases and the survival rate of the disease is only 22%, making it the leading cause of death for patients [5, 25, 26]. Metastatic spread of breast cancer involves many steps, including EMT, migration, invasion, extravasation, mesenchymal–epithelial transformation (MET) and colonisation [27]. An increasing range of research has demonstrated the importance of exosomes for all metastatic processes such as migration invasion of cancer [28, 29]. It has been shown that cancer cells secrete much higher levels of exosomes than those released by normal cells, and therefore the exosomes secreted by cancer cells themselves are critical for the exchange of genetic information and the reprogramming of metabolism between cells, as well as the microenvironment in which the cells live [30, 31]. We screened through validation that miR-7-5p was relatively highly expressed in low-invasive breast cancer cell lines and less expressed in highly invasive cells. Further investigation of the mechanism of miR-7-5p action revealed that the RYK gene may act as a new target gene for miR-7-5p. Among these, the RYK gene is a receptor-like tyrosine kinase, characterised by impaired kinase activity, which can exert regulatory effects by binding WNT ligands through its structural region [32]. In fact, RYK has been studied extensively in human development and more initially in cancer [33]. However, in recent years, RYK has been investigated as a receptor in atypical signalling pathways in many cancers [32, 34]. One study found that inhibition of β-catenin, a part of the typical WNT pathway, did not antagonise the RYK-induced metastatic phenotype in gastric cancer, demonstrating that the pro-metastatic effects of RYK in gastric cancer are mediated, at least in part, through the atypical Wnt signalling pathway [34]. It has been demonstrated that in prostate cancer the WNT5A/RYK signalling pathway is involved in the apoptotic and proliferative processes of cancer [35]. It has also been demonstrated that, as a response to WNT5A, RYK promotes the proliferation of breast stem and progenitor cells, and further studies have found that RYK plays a role as a receptor for the atypical WNT signalling pathway in the promotion of brain metastasis in breast cancer [36]. And in glioblastoma, RYK knockdown inhibited the invasiveness of wnt5a-induced U-105MG and U251MG glioma cells [37]. Various studies have demonstrated that abnormal WNT/RYK signalling may promote the oncogenic properties of cancer, particularly in tissues where RYK development is important. It has been reported that the atypical WNT pathway is often not dependent on β-catenin, but instead involves small GTPases of the Rho family, such as Rho or Rac, and that signalling enhances cell motility through the JNK/c-JUN cascade signalling response [36]. However, phosphorylated c-Jun protein is often able to affect the expression of EMT transcription factors (e.g. ZEB1) and thereby influence the EMT process. EMT is widely known to be an important process affecting the migration and invasion of breast cancer [23, 38, 39]. Interestingly, we demonstrated experimentally that miR-7-5p expression was significantly positively correlated with E-cadherin expression and significantly negatively correlated with N-cadherin expression. This indicates that miR-7-5p can inhibit the EMT process. We further experimentally verified that miR-7-5p was also able to affect the phosphorylation of JNK and c-Jun protein and ZEB1 protein. Therefore, we determined that miR-7-5p targets the RYK gene, causing deletion of the RYK receptor and affecting the JNK-mediated cascade of the atypical WNT pathway, leading to effects on the phosphorylation of JNK and c-Jun proteins, resulting in increased expression of EMT transcription factors such as ZEB1. This in turn affects the expression of E-cadherin and suppresses EMT, ultimately inhibiting the migration and invasion of breast cancer (Additional file 1: Fig. S2). There are of course limitations to our study. (1) We were not able to analyse the clinical significance of exosomal miR-7-5p in breast cancer by collecting case samples of tissue. (2) Given the limited experimental conditions, we should have used more breast cancer cell lines to validate our results. (3) We should further validate the effect of miR-7-5p in vivo by nude mouse tumorigenesis assay (Additional file 2).
In conclusion, our experimental data show that miR-7-5p in exosomes is closely associated with breast cancer migration and invasion. We identified a new target factor for miR-7-5p, RYK. We linked the oncogenic effect of miR-7-5p to the atypical WNT signalling pathway via the RYK gene. Our findings provide new targets for the treatment of advanced breast cancer and new ideas for the study of the molecular mechanisms of miRNAs.
Additional file 1: Table S1. Sequences of oligonucleotide fragment. Table S2 Sequences of primers required for the experiment. Table S3 Relative expression of several miRNAs screened from the GSE114329 dataset.Additional file 2. | true | true | true |
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PMC9549729 | 35920001 | Alexandre de Nonneville,Sébastien Salas,François Bertucci,Alexander P Sobinoff,José Adélaïde,Arnaud Guille,Pascal Finetti,Jane R Noble,Dimitri Churikov,Max Chaffanet,Elise Lavit,Hilda A Pickett,Corinne Bouvier,Daniel Birnbaum,Roger R Reddel,Vincent Géli | TOP3A amplification and ATRX inactivation are mutually exclusive events in pediatric osteosarcomas using ALT | 03-08-2022 | alternative lengthening of telomeres,ATRX,osteosarcomas,telomeres,TOP3A,Cancer,Chromatin, Transcription & Genomics,Musculoskeletal System | Abstract In some types of cancer, telomere length is maintained by the alternative lengthening of telomeres (ALT) mechanism. In many ALT cancers, the α‐thalassemia/mental retardation syndrome X‐linked (ATRX) gene is mutated leading to the conclusion that the ATRX complex represses ALT. Here, we report that most high‐grade pediatric osteosarcomas maintain their telomeres by ALT, and that the majority of these ALT tumors are ATRX wild‐type (wt) and instead carry an amplified 17p11.2 chromosomal region containing TOP3A. We found that TOP3A was overexpressed in the ALT‐positive ATRX‐wt tumors consistent with its amplification. We demonstrated the functional significance of these results by showing that TOP3A overexpression in ALT cancer cells countered ATRX‐mediated ALT inhibition and that TOP3A knockdown disrupted the ALT phenotype in ATRX‐wt cells. Moreover, we report that TOP3A is required for proper BLM localization and promotes ALT DNA synthesis in ALT cell lines. Collectively, our results identify TOP3A as a major ALT player and potential therapeutic target. | TOP3A amplification and ATRX inactivation are mutually exclusive events in pediatric osteosarcomas using ALT
In some types of cancer, telomere length is maintained by the alternative lengthening of telomeres (ALT) mechanism. In many ALT cancers, the α‐thalassemia/mental retardation syndrome X‐linked (ATRX) gene is mutated leading to the conclusion that the ATRX complex represses ALT. Here, we report that most high‐grade pediatric osteosarcomas maintain their telomeres by ALT, and that the majority of these ALT tumors are ATRX wild‐type (wt) and instead carry an amplified 17p11.2 chromosomal region containing TOP3A. We found that TOP3A was overexpressed in the ALT‐positive ATRX‐wt tumors consistent with its amplification. We demonstrated the functional significance of these results by showing that TOP3A overexpression in ALT cancer cells countered ATRX‐mediated ALT inhibition and that TOP3A knockdown disrupted the ALT phenotype in ATRX‐wt cells. Moreover, we report that TOP3A is required for proper BLM localization and promotes ALT DNA synthesis in ALT cell lines. Collectively, our results identify TOP3A as a major ALT player and potential therapeutic target.
The vast majority of human cancers upregulate telomerase, while the others rely on a mechanism called alternative lengthening of telomeres (ALT) based on homologous recombination (HR)‐mediated DNA replication (Sobinoff & Pickett, 2020). The choice between telomerase and ALT seems dependent on the cell‐of‐origin of the tumor (Lafferty‐Whyte et al, 2009; Claude & Decottignies, 2020). Tumors originating from epithelial cells endowed with low telomerase activity frequently upregulate telomerase through mutations in the TERT promoter (Chiba et al, 2017) or genomic rearrangements (Peifer et al, 2015). In tumors of mesenchymal or neuroectodermal origin, activation of TERT expression is less common and these tumors exhibit a high frequency of ALT activation (Kent et al, 2020). Alternative lengthening of telomeres is characterized by specific features including heterogeneous telomere length, partial clustering of telomeric DNA in promyelocytic leukemia (PML) bodies, partially double‐stranded circles with an intact C‐strand (C‐circles), and telomere sister chromatid exchanges (Yeager et al, 1999; Cesare & Griffith, 2004; Londoño‐Vallejo et al, 2004; Henson et al, 2009), although this last feature cannot be assessed directly on tumor tissue. It is accepted that tumors that acquire the ALT phenotype are prone to replication stress, which when unresolved may lead to fork collapse and as a consequence to double‐strand breaks (DSBs). ALT uses these breaks to initiate break‐induced telomere synthesis by RAD51‐dependent and RAD52‐dependent mechanisms (Verma et al, 2019; Zhang et al, 2019; Hoang & O'Sullivan, 2020). Multiple genomic repair pathways converge at telomeres to promote replication fork restart and telomere break repair (Sobinoff et al, 2017). Disruption of telomere chromatin may be at the root of replicative stress (Jiang et al, 2011; O'Sullivan et al, 2014). Recent results indicate that telomeres can be also elongated during mitosis (mitotic DNA synthesis) in ALT‐associated PML body (APB)‐like foci to counteract replication stress (Garcia‐Exposito et al, 2016; Min et al, 2017; Özer & Hickson, 2018). The α‐thalassemia/mental retardation syndrome X‐linked (ATRX) protein is a SWI/SNF2‐like chromatin remodeler that deposits histone H3.3 at pericentric heterochromatin and telomeres (Goldberg et al, 2010; Wong et al, 2010). ATRX, or the death domain‐associated protein (DAXX) gene which encodes a protein that forms a heterodimeric complex with ATRX, is frequently inactivated by mutation in tumors with ALT (Heaphy et al, 2011; Lovejoy et al, 2012). Because ATRX limits replication stress (Clynes et al, 2013; Leung et al, 2013; Huh et al, 2016) and telomeres are prone to replication stress (Sfeir et al, 2009), loss of ATRX likely results in telomeric DSBs that initiate homology‐directed repair at telomeres (Hoang et al, 2020; Sobinoff & Pickett, 2020). In human tumors, ALT was described as associated with mutations in the ATRX pathway (Heaphy et al, 2011). This is well established in ALT‐positive gliomas in which the IDH1R132H mutation is associated with ATRX loss (Nguyen et al, 2013; Ohba et al, 2020). ATRX loss has been proposed as a marker of ALT (Sieverling et al, 2020), but the view that ATRX/DAXX loss is essentially equivalent to the presence of ALT activity may apply only to specific types of tumors, in specific genomic or epigenetic contexts, and may divert attention from the need to identify alternative molecular actors involved in this telomere maintenance mechanism (TMM; Barthel et al, 2017; Brosnan‐Cashman et al, 2018; Graham et al, 2019; de Nonneville & Reddel, 2021). High‐grade osteosarcomas are highly aggressive malignant bone tumors that mainly occur in children and adolescents. Their therapeutic management includes neoadjuvant chemotherapy, which in pediatric contexts consists of the combination of high‐dose methotrexate, ifosfamide, and VP16, followed by surgery, and then adjuvant chemotherapy (Le Deley et al, 2007). When metastatic, the 5‐year survival rate of these tumors is less than 30%, indicating the critical need for new treatment strategies (Sayles et al, 2019). Osteosarcomas exhibit a high frequency of ALT activation (Ulaner et al, 2003; Sanders et al, 2004; Henson et al, 2005). Strikingly, previous reports showed that ATRX mutation and/or loss of protein expression is detectable in only 30% of ALT‐positive osteosarcomas (Chen et al, 2014; Liau et al, 2015). This discrepancy between a high level of ALT and a low proportion of ATRX inactivation led us to hypothesize that ATRX alteration may not be the only alteration responsible for the ALT mechanism in osteosarcoma. We have here analyzed the TMM in 22 non‐metastatic, non‐pre‐treated, high‐grade pediatric osteosarcomas. We identified TOP3A amplification and overexpression as a mutually exclusive event with ATRX inactivation, and validated TOP3A as an ALT regulator in the ATRX wild‐type (wt) setting. We also identified a number of genes for which mutation, amplification, or loss of copy number are closely associated with ALT, revealing new insights into the mechanisms by which telomeres are maintained. Moreover, our data suggest that ALT‐positive osteosarcomas may represent different entities in term of therapeutic opportunities.
We characterized a series of high‐grade osteosarcomas from 22 non‐metastatic and non‐pre‐treated pediatric patients whose clinico‐pathological characteristics are described in Table 1. Using the presence of circular partially single‐stranded extrachromosomal C‐rich telomeric repeat sequences (C‐Circles) as an ALT marker, we found that 16 of the 22 high‐grade osteosarcomas were ALT positive (Fig 1A). The C‐circle assay‐based classification was consistent with the presence or absence of APBs in ALT‐positive and ‐negative tumors, respectively (Fig 1B shows a representative photomicrograph; APB analysis was done on 14/22 tumors due to limited availability of tumor material). To explore telomere length distribution in the tumor samples, we further used a telomere shortest length assay (TeSLA), which allows the evaluation of the size of individual telomeres in the bulk population of telomeres (Lai et al, 2017). In ALT‐positive tumors, telomere length was more heterogeneous with an increase in the median telomeric fragment size consistent with the general organization of ALT telomeres (Cesare & Reddel, 2010; Fig 1C–E). Thus, by using three different criteria, we were able to unambiguously determine that 73% of our series of high‐grade osteosarcomas maintained their telomeres by ALT. Compared to patients with ALT‐negative tumors, patients with ALT‐positive tumors had no significant differences regarding age at diagnosis, sex, tumor size, response to neoadjuvant chemotherapy, relapse rate, or deaths (Table 2). With a median follow‐up of 126.2 months, 7 out of 16 patients with an ALT‐positive tumor, and 1 out of 6 patients with an ALT‐negative tumor relapsed. The 5‐year Disease‐Free Survival (DFS) was 55.6% in ALT‐positive tumors vs. 83.3% in ALT‐negative tumors, but the difference was not significant likely because of the small cohort size (P = 0.319; Log‐rank test; Fig EV1A). When the cohort was stratified according to the pathological response to neoadjuvant chemotherapy, poor responders, whether ALT positive or ALT negative, experienced poor DFS outcomes, whereas in the good responders group, only ALT‐positive patients relapsed with 64.8% 5‐year DFS vs. 100% in ALT‐negative patients (P = 0.205; Log‐rank test; Fig EV1B).
We next applied targeted next‐generation sequencing (tNGS) to the 22 tumors using a panel of 756 genes (Table EV1). With an average sequencing depth of 994×, we identified in the whole series a total of 288 mutations in 200 different genes the potential function of which in telomere maintenance is indicated in Table EV2. We found 244 single‐nucleotide variants (non‐synonymous and stop‐gains), 25 indels, and 1 splice‐site mutation (Table EV2). The median mutational burden per tumor (5.46) was higher in ALT‐positive tumors than in ALT‐negative tumors, but the difference was not significant (Fig EV2). tNGS revealed recurrent genetic alterations (7/22) in TP53 as previously reported (Chen et al, 2014; Kovac et al, 2015; Bousquet et al, 2016), with 6 out of the 7 mutated tumors being in the ALT‐positive group (Fig 2A, Table EV2). Overall, 13 genes were found mutated in at least three tumors (TP53, ATRX, ATAD2, ERCC2, FAMA35B, KMT2D, PCH15, PRX, RB1, REV3L, TET2, TPR, and TSC2, the functions of which are described in Table EV1). Strikingly, only 4 out of the 16 ALT‐positive tumors had an ATRX mutation and 1 of the 16 had an ATRX deep deletion (Fig 2A; see also the array‐comparative genomic hybridization [aCGH] data). Moreover, none of the tumors exhibited a mutation in the gene encoding the ATRX‐associated protein DAXX. Consistent with the tNGS results, immunohistochemistry analysis of 14/22 available tumors confirmed ATRX and DAXX protein expression in those identified by DNA sequencing as wt for ATRX and DAXX (Fig 2B). We concluded that 69% (11/16) of the ALT‐positive tumors displayed a seemingly unaltered ATRX/DAXX complex. Our results reveal that a majority of pediatric osteosarcomas were able to maintain their telomeres by ALT while expressing wt ATRX. Many of the mutated genes were functionally related (Fig 2C and Table EV1). For instance, in addition to ATRX, several play a role in replication, replication stress response, or DNA repair (MUS81, ERCC2, SMARCAD1, SMARCAL1, POLA1, POLE, POLD1, REV3L, and RAD54L). Along the same line, although the frequency of mutation for each individual gene was low, 16 of the 22 tumors were mutated in genes associated with histone lysine methylation (KMT2B, KMT2C, KMT2D, DOT1, NSD1, KDM4A, and TET2) or nucleosome remodeling (SMARCAD1; Fig 2C and Table EV1). Although most of these genes were not previously reported to be altered in osteosarcoma including pediatric forms (Chen et al, 2014; Kovac et al, 2015; Bousquet et al, 2016; Sayles et al, 2019), and although the mutations detected were not functionally validated, our results suggest that the epigenetic landscape in these pediatric tumors might be frequently altered (see Discussion). We also sequenced canonical histone genes of the HIST1 cluster that are frequently mutated in sarcomas (Nacev et al, 2019; Flaus et al, 2021). We found histone mutations in HIST1H1B, HIST1H1C, HIST1H1D, HIST1H1E, HIST1H1T, HIST1H2AJ, HIST1H2AM, HIST1H2BF, HIST1H3A, HIST1H3B, HIST1H4H, and HIST1H4L potentially expanding the landscape of oncohistone mutations in osteosarcoma (Table EV2 and Fig EV3; Nacev et al, 2020). Of note, 11/13 of the histone mutations including two mutations in HIST1H3A and HIST1H4H that modify their C‐terminal region were found in ALT‐positive tumors suggesting that these different mutations may contribute to a favorable environment for ALT activity (see Discussion).
We next determined the genomic rearrangements of the 22 tumors. DNA copy number profiling using aCGH showed many regions of frequent gains and losses. Globally, ALT‐positive tumors appeared more rearranged than ALT‐negative tumors, but the difference was not significant, likely due to the low number of ALT‐negative tumors (Fig EV2B). Four regions (6p21.1, 8q24.21, 17p11.2, and 19q12) were amplified with high frequency in the tumors, while two were frequently deleted (6q14.3 and 11q14.1; Fig 3A and Table EV2). We classified the most relevant genes that were either amplified (red bar) or deleted (blue bar) in the tumors and mainly considered the genes for which an amplification or a deletion occurred in at least three tumors (see Fig 2A). Within the gained regions, ATAD2, MYC, RUNX2, RECQL4, ERBB2, PDGFRA, and CCNE1 were recurrently observed in the tumors and appear to be potential drivers, confirming previous studies in osteosarcoma (Chen et al, 2014; Kovac et al, 2015; Both et al, 2016; Bousquet et al, 2016; Sayles et al, 2019; Suehara et al, 2019; Guimarães et al, 2021). Within the 17p11 amplified region, previously described to be frequently amplified in osteosarcomas (Forus et al, 1995; Tarkkanen et al, 1995; van Dartel et al, 2002, 2004; Bayani et al, 2003; Henriksen et al, 2003; Squire et al, 2003; Lau et al, 2004; Both et al, 2016), the TOP3A gene was always present in the amplicon, that is, all amplifications included TOP3A, among a number of other genes (Fig 3B). TOP3A caught our attention since it has an essential role in ALT (Tsai et al, 2006; Temime‐Smaali et al, 2008; Sobinoff et al, 2017; Pan et al, 2019; Loe et al, 2020; see below). Strikingly, TOP3A was amplified only in the ALT‐positive ATRX‐wt tumors and not in ALT‐positive ATRX‐mutated/deleted (ATRX‐mutated) tumors (71 vs. 0%; Fig 2A). Interestingly, we found that in most tumors in which TOP3A is amplified (4,001, 4,078, 4,591, 4,665, and 5,136), the TP53 gene was at the edge of the TOP3A amplification (Table EV3). This is particularly notable in tumors 4,001, 4,078, and 5,138, as opposed to tumors 2,254, 3,103, 4,464, and 8,299 where the copy number alteration (CNA) profile of the TP53 region upstream TOP3A amplification is flat (Fig 3C and Table EV3). Although the TP53 locus is represented on the array‐CGH chip by only two oligonucleotides, it seems likely that these amplifications result in breakage‐induced inactivation of at least one of the two alleles of TP53. We also observed that MMS21 (which cooperates with the SMC5/6 complex in DNA repair) and NBS1 (from the MRE11/RAD50/NBS1 DNA repair complex), which both contribute to maintain telomere length by ALT (Compton et al, 2007; Potts & Yu, 2007; Zhong et al, 2007; Barroso‐González et al, 2019), were amplified with high frequency in the tumors (Fig 2A). However, in contrast to TOP3A and NBS1, MMS21 amplification was also observed at high frequency in ALT‐negative tumors, suggesting that it does not have a specific role in the maintenance of ALT telomeres in pediatric osteosarcomas. Conversely, copy number losses of SMARCAL1 and XRCC5/KU80 were recurrently observed in ALT‐positive tumors, suggesting that depletion of these proteins may promote ALT (see Discussion). Overall, these results suggest that amplification of TOP3A could be a new hallmark of the ALT‐positive/ATRX‐wt tumors.
Next, we analyzed the transcriptomic profiles of the tumor samples (12 had good quality RNA) to highlight the differentially expressed genes (DEGs) between 9 ALT‐positive and 3 ALT‐negative tumors (Fig 4 and Table EV3). As shown in Fig 4A, the most upregulated genes in the ALT‐positive tumors were CBR3, COPS3, MAGEA6, and TOP3A, and a large number of histone genes from the HIST1 cluster (HIST1H2AI, HIST1H3I, HIST1H1B, and HIST1H3B). Consistent with the amplification of the gene, TOP3A mRNA was overexpressed in the ALT‐positive tumors overall and in the ALT‐positive ATRX‐wt tumors but not in the ALT‐negative or ALT‐positive ATRX‐mutated tumors (Fig 4B), strengthening the point that TOP3A overexpression and ATRX mutation are exclusive genomic events in ALT‐positive osteosarcomas. The fact that several histone genes were overexpressed in ALT‐positive tumors compared to ALT‐negative tumors suggests that overexpression of histone genes may favor ALT in pediatric osteosarcomas (Fig EV4). Globally, ontology analysis by Gene Set Enrichment Analysis (GSEA) in ALT‐positive versus ALT‐negative tumors revealed an enrichment in the expression of classical pathways related to chromosome duplication and transmission (Fig 4C and Table EV4). The prominence of DNA replication pathways in ALT‐positive tumors in the absence of any evidence of increased replication rate may reflect an increased need for restarting of stalled replication forks (Zhang & Zou, 2020). Conversely, ALT‐negative tumors were particularly enriched in genes related to the FGFR2‐associated signaling pathways that may be associated with telomerase reactivation in pediatric osteosarcoma (Greenfield et al, 2020).
One of the main discoveries of our study is that TOP3A amplification and ATRX mutation are mutually exclusive genomic events in ALT‐positive high‐grade osteosarcoma. However, in ALT‐positive/ATRX‐wt tumors, even if wt ATRX is normally expressed, the possibility exists that the ATRX protein might be non‐functional. We therefore sought to validate the results obtained from the tumors. We analyzed nine ALT‐positive human osteosarcoma‐derived cell lines (CAL72, HuO9, KPD, ZK58, NOS1, SaOS2, U2OS, G292, and NY; Lovejoy et al, 2012; Flynn et al, 2015). Sequencing data from the Sanger and Broad Institutes indicated that none of these cancer cell lines displayed a mutation in ATRX or DAXX (Tate et al, 2019), except NOS1 that had a homozygous loss of the ATRX genes (Loo et al, 2010). By Western blot, five out nine of these cell lines did not produce ATRX full‐length protein, while four cell lines (KPD, ZK‐58, G292, and NY) maintained ATRX protein expression (Fig 5A). We measured TOP3A mRNA expression in these nine osteosarcoma cell lines by quantitative reverse transcription polymerase chain reaction (RT‐qPCR) and found that its expression was higher in the ALT‐positive ATRX‐wt cell lines than in the ALT‐positive ATRX‐mutated cell lines, except NOS1 (t = 2.642, df = 7; P = 0.033) (Fig EV5). The NOS1 cell line turned out to have an elevated expression of TOP3A despite the fact it does not produce ATRX (see further). We monitored the expression of TOP3A by Western blot in these cell lines, which confirmed TOP3A overexpression in the ALT‐positive ATRX‐wt cell lines (Fig 5B). By fluorescence in‐situ hybridization‐immunofluorescence (FISH‐IF), we found that TOP3A colocalized with telomeric DNA in APBs in both ATRX‐mutated and ATRX‐wt (ALT positive) cell lines (Fig 5C) indicating that the ATRX status did not modify the localization of TOP3A. To determine whether the ATRX protein was functional or not in the ALT‐positive ATRX‐wt cell lines, we measured the effect of the ectopic expression of wt ATRX in ALT‐positive cell lines that were either ATRX‐wt or ATRX–mutated. We used the U2OS and NY cancer cell lines described above. In addition, we used immortalized IIICF cell lines that had been established from breast fibroblasts of a Li‐Fraumeni Syndrome patient (Maclean et al, 1994; Rogan et al, 1995; Bryan et al, 1997). Because C‐circle levels are a robust readout of ALT and rapidly respond to perturbations in ALT activity (Henson et al, 2009), we determined whether C‐circle levels changed in response to transfection of a plasmid expressing wt ATRX in the U2OS, NY, and IIICF lines (Fig 5D). The level of C‐circles was reduced following ATRX expression in each of the ALT‐positive ATRX‐mutated cell lines examined (IIICF TB1, IIICF TC4, and U2OS) compared to empty vector‐transfected control cells. In contrast, in ALT‐positive ATRX‐wt cell lines transfected with wt ATRX (IIICF DE, IIICF E6E7, and NY), the C‐circle levels increased (Fig 5D). Of note, exogenous expression of ATRX did not affect the growth rate in any of the cell lines tested (Fig EV5). Therefore, while ATRX expression reduced C‐circles in ATRX‐mutated cells, it had rather the opposite effect on ATRX‐wt cells. These results suggest that wt ATRX is functional in the ALT‐positive ATRX‐wt cell lines. To determine whether TOP3A overexpression is sufficient to overcome the ATRX‐dependent inhibition of ALT in U2OS expressing ectopic ATRX, we generated a U2OS cell line that stably overexpressed TOP3A (see Materials and Methods) and examined C‐circle levels (Fig 5E). As observed above, the level of C‐circles was reduced following pCMV‐ATRX transfection. However, the same cells also expressing TOP3A (pCMV‐TOP3A) exhibited only a mild reduction of the C‐circle level (Fig 5E). TOP3A overexpression restored APB frequency and mean telomere intensity in APB in U2OS transfected with pCMV‐ATRX (Fig 5F). Thus, TOP3A overexpression countered the ATRX‐mediated ALT inhibition, strengthening the results obtained with the clinical samples.
We next sought to determine the importance of TOP3A in ALT‐positive ATRX‐wt cells. To do this, we did a TOP3A knockdown (KD) in different ALT‐positive cell lines described above and analyzed its impact on ALT hallmarks (Fig EV4B). In the five ALT‐positive ATRX‐wt cell lines, TOP3A KD decreased C‐circles levels to different levels reflecting a disruption of the ALT phenotype. In contrast, TOP3A KD did not compromise C‐circle levels in ALT‐positive ATRX‐mutated cell lines (Fig 6A). Interestingly, TOP3A KD did not affect APB frequency (Fig 6B and C) in ALT‐positive cells, regardless of ATRX expression but induced an increase in telomeric damage‐induced foci (TIF) in U2OS, NY, and IIICF TC4 (Fig 6D). However, this increase in TIF numbers was associated with the appearance of very short telomeres (< 0.5 kb) only in the ALT‐positive ATRX‐wt cancer cell line NY (Fig 6E). Maintenance of telomeres in the ALT‐positive ATRX‐wt NY cell line was particularly sensitive to TOP3A depletion. Taken together, these results indicate that TOP3A overexpression contributes to maintenance of telomeres in ALT‐positive ATRX‐wt cells.
Interestingly, our results indicate that TOP3A depletion particularly affects telomere maintenance in the ALT‐positive ATRX‐wt NY cell line. Because NY cells overexpress TOP3A, we hypothesized that this may lead to more BLM localization at telomeric sequences. Although not significant via Mann–Whitney, we observed an increase in the intensity of BLM at telomeres in the NY cells compared to U2OS cells (Fig 7A, right and left panels). We also found that TOP3A depletion clearly affects BLM localization at APBs in both cell lines (Fig 7A). Given this result, we measured ALT DNA synthesis (Sobinoff et al, 2017; Zhang et al, 2019) in the NY and UO2S cell lines (Fig 7B). We found that the NY cell line had a higher number of cells with EdU foci in APBs and that TOP3A depletion compromised ALT DNA synthesis in both cell lines (Fig 7B, right and left panels). Taken together, these results indicate that increased levels of TOP3A in NY cells correlate with increased levels of BLM at ALT telomeres and that TOP3A promotes ALT DNA synthesis. These results may explain the greater dependence of NY cells on TOP3A.
Although ALT is the TMM commonly utilized by osteosarcomas, many of these tumors have wt ATRX, a gene which is frequently mutated in ALT‐positive cancers (Ulaner et al, 2003; Sanders et al, 2004; Henson et al, 2005; Chen et al, 2014; Liau et al, 2015). The contrast with other types of sarcomas is illustrated by a study of ALT phenotype and ATRX status in 519 sarcoma samples which found loss of ATRX expression in approximately 50% of ALT‐positive leiomyosarcomas, undifferentiated pleomorphic sarcomas, and pleomorphic liposarcomas, whereas ATRX mutation and loss of expression was observed in only 30% of osteosarcomas (Liau et al, 2015). We show here that another mutational event is characteristic of ATRX‐wt osteosarcomas. We found that ALT tumors carried either an ATRX mutation or an amplification of the 17p11.2 region as two mutually exclusive events. In this chromosomal region, we identified TOP3A amplification as the major genomic feature of the ALT tumors expressing wt ATRX. Gene expression analyses revealed that TOP3A was overexpressed in the ALT‐positive ATRX‐wt tumors compared to either ALT‐positive ATRX‐mutated or ALT‐negative tumors. Amplification of the 17p11.2 region has been previously reported in osteosarcomas with a frequency ranging from 20 to 78% suggesting the presence of one or more oncogenes in this region (Forus et al, 1995; Tarkkanen et al, 1995; van Dartel et al, 2002, 2004; Bayani et al, 2003; Henriksen et al, 2003; Squire et al, 2003; Lau et al, 2004; Both et al, 2016). Of note, overexpression of genes belonging to the amplified region (COPS3, PMP22, GID4, ARGHAP44, TOP3A, SHMT1, and RASD1) was studied in osteosarcoma cell lines (Both et al, 2016). While TOP3A, SHMT1, and RASD1 overexpression resulted in increased proliferation, ARGHAP44, COPS3, and PMP22 overexpression had a stimulatory effect on migration and invasion of the cells. COPS3 and PMP22 overexpression additionally improved the ability of the cells to form new colonies (Both et al, 2016). However, the contribution of this region was not studied with respect to telomere maintenance previously. Here, we have shown that TOP3A amplification and overexpression is an alternative to ATRX inactivation, and the most frequent genetic event identified in ALT‐positive high‐grade pediatric osteosarcoma. The hypothesis that TOP3A overexpression was instrumental in maintaining ALT in ATRX‐wt cells was confirmed by in vitro experiments showing first that TOP3A overexpression could restore ALT features in ALT‐positive ATRX‐mutated cell lines transfected with wt ATRX and second that TOP3A KD disrupted the ALT phenotype with a concomitant increase in telomeric DNA damage in ALT‐positive ATRX‐wt cells. TOP3A is a type I DNA topoisomerase operating within the BLM‐TOP3A‐RIM1 complex (known as the BTR complex) that suppresses crossing‐over during HR (Wu & Hickson, 2003). TOP3A was previously shown to be localized at ALT telomeres and to be required to maintain ALT telomeres (Tsai et al, 2006; Temime‐Smaali et al, 2008). TOP3A was further shown to promote POLD3‐dependent telomere synthesis through a mechanism analogous to break‐induced replication (Dilley et al, 2016; Sobinoff et al, 2017; Lu et al, 2019). The central role of the BTR complex in ALT was further underscored by the recent discovery that its localization at telomere ends is essential for ALT activity (Loe et al, 2020; Zhang et al, 2021). Here we have shown that TOP3A depletion affects BLM localization at APBs and compromises ALT DNA synthesis in U2OS and NY cell lines that are ATRX mutated and ATRX‐wt, respectively. However, we found that the NY cell line has more BLM at APBs and higher levels of ALT DNA synthesis consistent with the fact that NY cells overexpress TOP3A and are more sensitive to TOP3A depletion. TOP3A has also been described to have a role in the processing of ultra‐fine bridges that connect the separating sister DNA molecules during anaphase at specific unreplicated genomic loci, including telomeres (Sarlós et al, 2018), suggesting that TOP3A plays a role in mitotic DNA synthesis (MiDAS; Özer & Hickson, 2018). Moreover, recent results indicated that reconstituted PML bodies consisting of polySUMO/polySIM condensates targeting telomeres were able to cluster telomeres and generate ALT telomeres through a process mediated by BLM and RAD52 (Min et al, 2019; Zhang et al, 2019, 2020). Collectively, these studies reveal that BIR, MiDAS, and ALT share molecular processes in which TOP3A is a major actor (Epum & Haber, 2021). We speculate that in tumors undergoing replication stress, TOP3A overexpression promotes these molecular processes, accounting for its overexpression being a critical contributor to ALT activity in tumors. Strikingly, we observed that amplification of the 17p11.2 region may both amplify TOP3A and disrupt at least one allele of TP53 in most ATRX‐wt tumors. Analysis of the TP53 status in the tumors carrying an amplified 17p11.2 region raises the interesting hypothesis that the 17p11 amplification could do “double duty,” on the one hand amplifying TOP3A and on the other hand inactivating TP53. Beside TOP3A amplification, our study revealed alterations in other genes that have been implicated in ALT. NBS1, the depletion of which results in inhibition of ALT in human cell lines (Compton et al, 2007; Zhong et al, 2007), was amplified in ALT‐positive tumors. SP100, which sequesters the MRN complex thereby suppressing ALT (Jiang et al, 2005), had a loss of copy number. These results highlight the importance of the MRN complex in the formation of ALT telomeres in these pediatric tumors. Loss of KU86 may also play a role in ALT, as suggested by several studies (Zellinger et al, 2007; Wang et al, 2009; Yu et al, 2015). Of note, we did not find alterations in SLX4IP that was reported to antagonize BLM activity during ALT Maintenance (Panier et al, 2019). We found mutations in genes that organize the structure of chromatin. Although not previously reported in osteosarcomas, mutations in KMT2B/MLL2, KMT2C/MLL3, or KMT2D/MLL4 that catalyze mono‐ or di‐methylation of H3K4 (Hyun et al, 2017) are frequently observed in many types of cancer (Rao & Dou, 2015; Fagan & Dingwall, 2019). Interestingly, it was recently reported in mouse embryonic stem cells deleted for ATRX, TP53, and TERT that inhibiting KDM4B/JMJD2B (which demethylates H3K9 and H3K36) drives ALT activation (Udugama et al, 2021). Consistent with this observation, we found that among the five ALT‐positive ATRX‐mutated tumors, two carried mutations in TP53 and KDM4A/JMJD2A (E23K and K463Q; that also demethylates H3K9 and H3K36), suggesting that simultaneous inactivation of TP53, ATRX, and KDM4A/JMJD2A may also drive ALT in pediatric osteosarcoma. In pediatric high‐grade glioma, the G34R mutation in H3.3 triggers ALT, irrespective of the ATRX status. In contrast, only a subset of H3.3‐K27M tumors activate ALT (Minasi et al, 2021). This result is to be compared with a recurrent amplification of 17p11.2 targeting TOP3A and mutually exclusive with ATRX deletion/mutations that has been identified in diffuse intrinsic pontine glioma with a H3.3‐K27M mutation (Mackay et al, 2017). Together with our data, these results suggest that under conditions that reprogram the epigenetic landscape, ATRX inactivation or TOP3A amplification may represent two independent ways of promoting ALT. We found that of the 13 tumors displaying mutations in histones genes of the HIST1 cluster, 11 were ALT positive irrespective of their ATRX status. Two mutations (in HIST1H3A and HIST1H4H) either introduced a frameshift or modified the C‐terminal region known to be crucial for the interaction with the histone chaperone ASF1 (Natsume et al, 2007), the depletion of which leads to the rapid induction of ALT in primary human lung fibroblasts (O'Sullivan et al, 2014). In addition, we observed that many histone genes of the HIST1 cluster were upregulated in ALT‐positive tumors compared to ALT‐negative tumors. We favor the idea that overexpression of canonical histone genes in the ALT‐positive tumors might create an imbalance between canonical histones and histone variants (Maya Miles et al, 2018), which may generate replication stress promoting ALT. Finally, the analysis of clinical data revealed that, among patients with good response to neoadjuvant chemotherapy, ALT positivity of the pre‐treatment biopsy was associated with worse DFS than ALT negativity (4/9 events vs. 0/4 at 126.2 of median follow‐up, respectively). This observation, which needs to be validated in a larger cohort, might suggest the relevance of studying TMM as a biomarker in high‐grade pediatric osteosarcomas to reassign ALT‐positive good responders as candidates for alternative adjuvant therapy after surgery. To date, there is no prognostic marker able to differentiate good responders from poor responders at diagnosis. This result is consistent with many other studies showing that, with the notable exception of glioblastomas, ALT positivity is associated with unfavorable clinical outcome of most tumor types (Henson & Reddel, 2010). In conclusion, our study identified a number of genomic features associated with ALT, providing new targetable proteins and potential therapeutic opportunities for osteosarcoma. The results emphasize the potential interest in developing TOP3A inhibitors for treatment of ALT‐positive ATRX‐wt osteosarcomas.
Frozen tumor samples of 22 high‐grade osteosarcomas from pediatric patients treated at Timone Hospital (Marseille, France) were retrospectively obtained. At the time of these diagnostic biopsies, all patients had strictly localized diseases and were naïve of any pre‐treatment. Diagnosis of osteosarcoma was made by an expert pathologist of the French Sarcoma Group and all specimens were conventional high‐grade osteosarcomas. Normal tissue was obtained from surgical resection and after neo‐adjuvant chemotherapy for 21 patients. All patients or their legal guardian provided written informed consent (also see Ethics Declaration below).
This study was approved by the Aix‐Marseille University Research Ethics Committee. Tumor material was obtained from the Timone Hospital biobank (Tumorothèque et Banque de Muscles, Hôpital de la Timone—Registration no. AC‐2018‐3105 at the Ministry of Higher Education, Research and Innovation). Signed and written formal consent was obtained from all patients or their legal guardian. The experiments conformed to the principles set out in the WMA Declaration of Helsinki and the Department of Health and Human Services Belmont Report.
C‐circles were amplified with Phi29 polymerase using dATP, dTTP, and dGTP overnight. Products were dot blotted onto Biodyne B membranes (Pall) and pre‐hybridized in PerfectHyb Plus (Sigma) for at least 30 min. γ‐[32P]‐ATP‐labeled telomeric C‐probe (CCCTAA)4 was then added and blots were hybridized overnight at 37°C (Henson et al, 2009). Blots were washed with 0.5× SSC, 0.1% SDS three times for 5 min each, then exposed to a PhosphorImager screen. Imaging was performed on the Typhoon FLA 7000 system (GE Healthcare) with a PMT of 750 V.
DNA and RNA extraction from tumor frozen samples was performed using the All prep DNA/RNA kit from QIAGEN. Frozen biopsies were first ground in a mortar containing liquid nitrogen to obtain a fine powder. Then, we proceeded according to the manufacturer's instructions. DNA amounts were quantified with Nanodrop® and QUBIT® (Qubit DNA HS assay kit). RNA quality was controlled on an Agilent Bioanalyzer (Agilent Technologies, Massy, France) assessing RNA integrity Number (RIN) for each sample. To extract DNA from cell lines, cells were harvested via trypsinization, washed in PBS, and resuspended in lysis buffer (50 mM Tris–HCl, 100 mM NaCl, 50 mM ethylenediamine tetraacetic acid (EDTA), 0.5% SDS, pH 8). Lysed cells were subjected to RNase A (50 μg/ml) treatment for 20 min at room temperature, followed by protein digestion with 400 μg/ml proteinase K (Invitrogen) overnight at 55°C. DNA was extracted using three rounds of phenol/chloroform extraction followed by ethanol precipitation. Total RNA was isolated using the RNeasy mini kit (Qiagen) and DNase‐treated to remove genomic DNA.
tNGS was applied to a custom‐made panel of 755 “cancer‐associated” and “actionable” genes (Table EV1). For each of the 22 clinical samples, the DNA libraries of all coding exons and intron–exon boundaries of all genes were prepared using the HaloPlex Target‐Enrichment‐System (Agilent, Santa Clara, CA, USA), as previously described (Collette et al, 2015). Sequencing was done using the 2 × 150‐bp paired‐end technology on the Illumina NextSeq500 platform, according to the manufacturer's instructions (Illumina, San Diego, CA, USA). Sequence data were aligned to the human reference genome (UCSC hg19) and analyzed, as previously described (Collette et al, 2015; Bertucci et al, 2016). Computing resources for this study were provided by the computing facilities DISC (Datacenter IT and Scientific Computing) of the Centre de Recherche en Cancérologie de Marseille.
For each sample, the genomic profile was established by using aCGH onto high‐resolution 4 × 180 K CGH‐microarrays (SurePrint G3‐Human CGH‐Microarray, Agilent Technologies). Human female DNA was used as reference (G152A, Promega, Madison, WI, USA). Both experimental and analytic methods have been previously described (Adélaïde et al, 2007). All probes for aCGH were mapped according to the Genome Reference Consortium Human Build 37 (CGCh37/Hg19; https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.13/). We used two different threshold values (log2 ratio > ¦0.2¦ and ¦0.5¦) to distinguish low‐ (gain/loss) from high‐(amplification/deletion) level CNA, respectively. Percentage of altered genome was the number of probes above the threshold divided by the total number of probes for autosomal chromosomes. To identify the overall altered regions, we used the GISTIC2.0 algorithm with alteration thresholds set to 0.15 and with a corrected threshold probability (q < 0.25) to define a statistically relevant region.
DNA microarrays were used to define the transcriptional profiles of 12 tumor samples with a RIN ranging from 8.1 to 9.9. Experiments were done as recommended by the manufacturer (Affymetrix, Thermo Fisher) from 100 ng of total RNA for each sample using the GeneChip™ WT PLUS Reagent Kit and the Affymetrix GeneChip™ HuGene 2.0 ST arrays. Expression data were normalized by RMA with the nonparametric quantile algorithm in R using Bioconductor and associated packages (version 3.5.2; http://www.cran.r‐project.org/). Supervised analysis comparing the expression profiles between sample classes was done using a moderated t‐test with empirical Bayes statistic100 included in the limma R package (version 3.38.3). Significantly, DEGs were defined by the following thresholds: P‐value < 0.05 and fold change FC > ¦2x¦. Ontology analysis was done by the GSEA algorithm with the Reactome pathway database included in the MSigDB (version 7.2) 101. GSEA was done with 1000 gene‐set permutations as parameters and significantly DEG sets were defined by the following thresholds: P‐value < 0.05 and q‐value < 0.25.
Immunohistochemistry was performed using ATRX (1:500, Sigma Aldrich) and DAXX (1500, Sigma Aldrich) antibodies. The immunohistochemical protocol included deparaffinization, hydration, antigen retrieval, primary antibody incubation, and detection and visualization as per the manufacturer's instructions.
The TeSLA method was performed as described (Lai et al, 2017). Briefly, 50 ng of genomic DNA was added to a final volume of 20 μl ligation buffer containing 1,000 units of T4 DNA ligase (New England Biolabs), 1× Cut Smart Buffer (New England Biolabs), 1 mM ATP, and 1 nM of TeSLA telorettes (TeSLA Telo 1–6) and incubated at 35°C for 16 h followed by heat inactivation at 65°C for 10 min. After ligation, genomic DNA was digested using a set of restriction enzymes (2 U each of CviAII, BfaI, NdeI, and MseI, New England Biolabs) and then treated with 1 U of Shrimp Alkaline Phosphatase (rSAP, New England Biolabs) at 37°C for 60 min in a final volume of 50 μl. This mixture was subsequently heat inactivated at 80°C for 20 min and 10 μl of sample was added to 10 μl of adapter ligation mix (1 μM AT adapter, 1 μM TA adapter, 1 mM ATP, 1× Cut Smart Buffer and 2,000 units of T4 DNA Ligase) and incubated at 16°C for 16 h. After adapter ligation, the sample was heat inactivated at 65°C for 10 min and subsequently diluted to a concentration of 15 pg DNA/μl (1:25 dilution). For each sample analyzed, we performed eight independent PCRs (94°C for 2 min followed by 26 cycles of 94°C for 15 s, 60°C for 30 s, and 72°C for 15 min) using a total of 25 μl mix containing 30 pg DNA, 2.5 U FailSafe enzyme (Epicenter), 1× FailSafe buffer H (Epicenter), and 250 nM primers (adapter and TeSLA TP). PCR products were electrophoresed on a 0.85% agarose gel (1.5 V/cm for 19 h). The gels were dried for 75 min at 60°C, denatured in 0.5 M NaOH/1.5 M NaCl for 1 h, and neutralized in 0.5 M Tris–HCl (pH 8.0)/1.5 M NaCl for 1 h. Gels were then rinsed in 2× SSC and prehybridized in Church buffer (250 mM sodium phosphate buffer, pH 7.2, 7% [wt/vol] SDS, 1% [wt/vol] BSA fraction V grade, and 1 mM EDTA) for 2 h at 37°C. Finally, gels were hybridized overnight with a γ‐[32P]‐ATP‐labeled (TTAGGG)3 oligonucleotide probe, washed three times in 0.1× SSC for 15 min at 37°C, and exposed to a PhosphorImager screen overnight. Images were analyzed using MATLAB‐based software to detect and annotate the size of telomere bands including the percentage of shortest telomeres and average telomere lengths.
All cell lines were cultured in Dulbecco's modified Eagle's medium supplemented with 10% (v/v) fetal bovine serum in a humidified incubator at 37°C with 5% CO2. HCT116, CAL72, HuO9, KPD, ZK58, NOS1, SaOS2, U2OS, G292, and NY cell lines were obtained from the American Type Culture Collection. IIICF cell lines are in vitro‐immortalized breast fibroblast cells that were established from an individual with Li–Fraumeni syndrome (Maclean et al, 1994; Rogan et al, 1995; Bryan et al, 1997). Cell lines were authenticated by 16‐locus short‐tandem‐repeat profiling and tested for mycoplasma contamination by CellBank Australia (Children's Medical Research Institute, Westmead, NSW, Australia).
An ATRX expression vector, pCMV6‐Entry‐ATRX, and the empty vector pCMV6‐Entry were obtained from OriGene. Transfection with each vector was performed using FuGENE reagent (Promega). Cells were harvested at 72 h post‐transfection and analyzed as described. Stable TOP3A‐overexpressing U2OS cell lines were generated as follows: cells were seeded at 2 × 105 per 6‐well plates and reverse transfected with 1 μg DNA of either pcDNA‐TOP3A or pcDNA‐Empty plasmid (courtesy of JF Riou), using FuGENE‐6 reagent (Promega) according to the manufacturer's instructions. G418 (400 μg/ml) was added after 24 h for selection over 1 month. Cells were continuously cultured in G418 to ensure overexpression. Protein overexpression was confirmed via Western blot analysis.
Cells were collected and lysed in radioimmunoprecipitation assay buffer. Proteins were resolved by electrophoresis using a Tris‐acetate gel or 4–12% Bis‐Tris gel (Invitrogen). Transferred membranes were blocked in 5% milk and incubated with primary antibody overnight. Antibodies were used against ATRX (Sigma HPA064684, SC10078, and SC1540; 1:800 dilution), DAXX (Sigma HPA008736; 1:800 dilution), Vinculin (T5191; 1:600 dilution), γ‐tubulin (Sigma, T5192; 1:1,000 dilution), and TOP3A (proteintech 14,525‐1‐AP; 1:600 dilution).
Two TOP3A Silencer Select siRNAs were designed and synthesized by Life Technologies (s14311 & s224746), and Silencer Select RNAi siRNA Negative Control #2 (#4390847) was used as the control siRNA. Cell suspensions were transfected at 20–50% confluency with Lipofectamine RNAiMAX (Life Technologies) at a final siRNA concentration of 30 nM. Culture medium was changed after 48 h and cells were harvested for analysis 72 h post‐transfection. KD efficiency was validated by western blot analysis.
KD experiments using siRNA were verified by qRT–PCR. Total RNA was isolated using the RNeasy mini kit (Qiagen) and DNase‐treated to remove genomic DNA. Reverse transcription was performed with 2 μg isolated RNA, 500 ng oligo(dT)15 primer, 40 U RNasin, 0.5 mM dNTPs, and 20 U M‐MLV‐Reverse Transcriptase (Promega). Quantitative PCR was performed using SYBR Green qPCR Master Mix (Roche) according to the manufacturer's instructions. Primer sequences are supplied as supplementary data (Table EV4). PCRs were performed on cDNA equivalent to 100 ng total RNA and carried out for 40 amplification cycles, followed by melt curve analysis. For each sample, a replicate omitting the reverse transcription step was included as a negative control. Primer PCR efficiencies were calculated by standard curve. Real‐time data were analyzed using the ΔΔC(t) method, with GAPDH as the reference gene, and expressed as fold‐change relative to the appropriate control (±SEM).
Cells were grown on cover slips. Slides were subjected to pre‐extraction by incubation in KCM permeabilization solution (120 mM KCl, 20 mM NaCl, 10 mM Tris, 0.1% (v/v) Triton X‐100) for 10 min. Slides were then washed in PBS, fixed at room temperature for 10 min in PBS with 4% (v/v) formaldehyde. For tumor samples, 4 μm paraffin sections were cut and dewaxed. Slides were rehydrated then microwave heated to 120°C in 90% glycerol, 10 mmol/l Tris (pH 10.5), 1 mmol/l EDTA, and maintained at 110–120°C for 15 min. The slides were cooled and rinsed in PBS. All subsequent treatments of cell lines and paraffin sections were identical. Cells were blocked with 100 μg/ml DNase‐free RNase A (Sigma) in antibody‐dilution buffer (20 mM Tris–HCl, pH 7.5, 2% (w/v) BSA, 0.2% (v/v) fish gelatin, 150 mM NaCl, 0.1% (v/v) Triton X‐100, and 0.1% (w/v) sodium azide) for 1 h at room temperature. Antibodies were used against PML (Santa Cruz, sc‐966; Goat; 1:400 dilution), γ‐H2AX (Merck Millipore, Mouse, 1:500 dilution), BLM (Bethyl Laboratories, A300‐110A; Rabbit; 1:500 dilution), and TOP3A (Temime‐Smaali et al, 2008; Rabbit; 1:1,000 dilution). Slides were incubated with primary antibody diluted in antibody‐dilution buffer for 1 h at room temperature, washed in phosphate‐buffered saline‐Tween‐20, and incubated with appropriate AlexaFluor secondary antibodies diluted in antibody‐dilution buffer for 1 h at room temperature in a humidified chamber. Subsequent telomere FISH was performed. Slides were washed in PBST and fixed for 10 min in PBS with 4% (v/v) formaldehyde at room temperature. Slides were then subjected to a graded ethanol series (70% (v/v) for 3 min, 90% (v/v) for 2 min, and 100% for 2 min) and allowed to air‐dry in the dark. Dehydrated slides were then overlaid with 0.3 μg/ml TAMRA–OO‐(CCCTAA)3 or Alexa 488‐OO‐(CCCTAA)3 telomeric PNA probe (Panagene) in PNA hybridization solution (70% (v/v) deionized formamide, 0.25% (v/v) NEN blocking reagent (PerkinElmer), 10 mM Tris–HCl, pH 7.5, 4 mM Na2HPO4, 0.5 mM citric acid, and 1.25 mM MgCl2), denatured at 80°C for 3 min, and hybridized at room temperature overnight. Slides were washed in PNA wash A and then in PNA wash B for 15 min each. 4',6‐diamidino‐2‐phénylindole (DAPI) was added at 50 ng/ml to the final wash. Finally, slides were rinsed briefly in deionized water and mounted in DABCO anti‐fade mounting media.
To visualize DNA synthesis at telomeres, cells were treated with 10 μM of RO‐3306 for 18 h for G2 synchronization. G2 synchronized cells were then pulsed with 10 μM EdU for 1 h. Cells were permeabilized in KCM permeabilization solution (120 mM KCl, 20 mM NaCl, 10 mM Tris, 0.1% (v/v) Triton X‐100) for 10 min, then fixed with 4% formaldehyde PBS solution for 10 min. The Click‐iT® Alexa Fluor 647 azide reaction (Invitrogen) was then performed according to the manufacturer's instructions. Indirect immunofluorescence for PML and telomere‐FISH were then performed according to the relevant methods section.
ZEN microscopy images (.czi) were processed into extended projections of z‐stacks using ZEN desk 2011 software (Zeiss) and imported into Cellprofiler v2.1.1 (29) for analysis. The DAPI channel was used to mask individual nuclei as primary objects. Foci within each segmented nucleus were identified using an intensity threshold‐based mask. Any given object was considered to be overlapping another object when at least 80% of the first object's area was enclosed within the area of a second object.
Alexandre de Nonneville: Conceptualization; formal analysis; validation; supervision; investigation; visualization; methodology; writing – original draft. Sébastien Salas: Resources; project administration. François Bertucci: Investigation; methodology; writing – review and editing. Alexander P Sobinoff: Investigation; methodology. José Adélaïde: Investigation; methodology. Arnaud Guille: Investigation. Pascal Finetti: Investigation; methodology. Jane R Noble: Project administration. Dimitri Churikov: Conceptualization; supervision; investigation; methodology. Max Chaffanet: Methodology. Elise Lavit: Investigation. Hilda A Pickett: Investigation; methodology. Corinne Bouvier: Resources; investigation; methodology. Daniel Birnbaum: Conceptualization; supervision; funding acquisition; validation; investigation; writing – review and editing. Roger R Reddel: Conceptualization; formal analysis; funding acquisition; validation; investigation; methodology; writing – review and editing. Vincent Géli: Conceptualization; formal analysis; supervision; funding acquisition; validation; investigation; writing – original draft; project administration.
The authors declare that they have no conflict of interest.
To maintain their telomeres, most human cancer cells upregulate telomerase, while the rest uses a mechanism based on HR‐mediated DNA replication ALT. High‐grade osteosarcomas are highly aggressive bone tumors that mainly occur in children and adolescents, with limited treatment options. Strikingly, osteosarcomas exhibit a high frequency of ALT. In contrast to many other tumors, ATRX, a chromatin remodeler, is mutated in only 30% of ALT‐positive osteosarcomas, indicating that these may not be the only alterations responsible for ALT.
We characterized non‐metastatic, non‐pre‐treated, high‐grade pediatric osteosarcomas and uncovered that more than 70% of these tumors maintained their telomeres via the ALT pathway. In the ALT tumors, TOP3A gene amplification and overexpression was more prevalent than ATRX loss‐of‐function. Because ATRX mutation and TOP3A overexpression were mutually exclusive, overexpression of TOP3A appeared as an alternative mechanism driving ALT in pediatric osteosarcoma. In ALT‐positive human osteosarcoma‐derived cell lines, TOP3 overexpression also correlated with the presence of ATRX. Moreover, TOP3A was required to localize the BLM helicase to telomeres and promote ALT‐associated DNA synthesis in ALT osteosarcoma cell lines. Several genes whose alteration is associated with ALT in pediatric osteosarcoma were additionally identified, revealing new mechanistic insights into telomere maintenance in these tumors. Overall, these results identify TOP3A or TOP3A downstream signaling as a potential therapeutic target.
Amplification of TOP3A is a new hallmark of the ALT mechanism in tumors that are otherwise wt for ATRX. The discovery that TOP3A amplification/overexpression is mutually exclusive with ATRX mutation constitutes a strong argument for the involvement of TOP3A in oncogenesis. Our work therefore positions TOP3A action at telomeres as a prognostic marker and a new potential therapeutic target in ALT‐associated pediatric osteosarcomas.
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PMC9550049 | Xiangbin You,Min Liu,Qian Liu,Huijuan Li,Yilin Qu,Xiaoxiao Gao,Chengyu Huang,Gan Luo,Gang Cao,Dequan Xu | miRNA let-7 family regulated by NEAT1 and ARID3A/NF-κB inhibits PRRSV-2 replication in vitro and in vivo | 10-10-2022 | Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating diseases affecting the swine industry worldwide. To investigate the role of miRNAs in the infection and susceptibility of PRRS virus (PRRSV), twenty-four miRNA libraries were constructed and sequenced from PRRSV-infected and mock-infected Porcine alveolar macrophages (PAMs) of Meishan, Landrace, Pietrain and Qingping pigs at 9 hours post infection (hpi), 36 hpi, and 60 hpi. The let-7 family miRNAs were significantly differentially expressed between PRRSV-infected and mock-infected PAMs from 4 pig breeds. The let-7 family miRNAs could significantly inhibit PRRSV-2 replication by directly targeting the 3’UTR of the PRRSV-2 genome and porcine IL6, which plays an important role in PRRSV replication and lung injury. NEAT1 acts as a competing endogenous lncRNA (ceRNA) to upregulate IL6 by attaching let-7 in PAMs. EMSA and ChIP results confirmed that ARID3A could bind to the promoter region of pri-let-7a/let-7f/let-7d gene cluster and inhibit the expression of the let-7 family. Moreover, the NF-κB signaling pathway inhibits the expression of the let-7 family by affecting the nuclear import of ARID3A. The pEGFP-N1-let-7 significantly reduced viral infections and pathological changes in PRRSV-infected piglets. Taken together, NEAT1/ARID3A/let-7/IL6 play significant roles in PRRSV-2 infection and may be promising therapeutic targets for PRRS. | miRNA let-7 family regulated by NEAT1 and ARID3A/NF-κB inhibits PRRSV-2 replication in vitro and in vivo
Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating diseases affecting the swine industry worldwide. To investigate the role of miRNAs in the infection and susceptibility of PRRS virus (PRRSV), twenty-four miRNA libraries were constructed and sequenced from PRRSV-infected and mock-infected Porcine alveolar macrophages (PAMs) of Meishan, Landrace, Pietrain and Qingping pigs at 9 hours post infection (hpi), 36 hpi, and 60 hpi. The let-7 family miRNAs were significantly differentially expressed between PRRSV-infected and mock-infected PAMs from 4 pig breeds. The let-7 family miRNAs could significantly inhibit PRRSV-2 replication by directly targeting the 3’UTR of the PRRSV-2 genome and porcine IL6, which plays an important role in PRRSV replication and lung injury. NEAT1 acts as a competing endogenous lncRNA (ceRNA) to upregulate IL6 by attaching let-7 in PAMs. EMSA and ChIP results confirmed that ARID3A could bind to the promoter region of pri-let-7a/let-7f/let-7d gene cluster and inhibit the expression of the let-7 family. Moreover, the NF-κB signaling pathway inhibits the expression of the let-7 family by affecting the nuclear import of ARID3A. The pEGFP-N1-let-7 significantly reduced viral infections and pathological changes in PRRSV-infected piglets. Taken together, NEAT1/ARID3A/let-7/IL6 play significant roles in PRRSV-2 infection and may be promising therapeutic targets for PRRS.
Porcine reproductive and respiratory syndrome (PRRS), also known as blue-ear pig disease, is one of the most economically devastating diseases affecting the swine industry worldwide [1]. It is characterized by high fever, high morbidity, high mortality, severe reproductive failure in pregnant sows and respiratory tract distress and persistent infection, particularly in suckling pigs [2]. PRRS virus (PRRSV) is a small enveloped single-stranded, 5’-capped positive sense RNA virus and is classified as a member of the family Arteriviridae, order Nidovirales [3]. Conventionally, all PRRSV isolates are classified into two genotypes: PRRSV-1(European-like isolate) and PRRSV-2(North America-like isolate) [4]. Porcine alveolar macrophages (PAMs) are immune defense cells of the lung that first contact pathogenic microorganisms [5] and are considered as the major target cells of viral replication during the acute infection period [6]. Some reports suggest that host genetics play a role in susceptibility to respiratory disease and differences in the severity and distribution of lesions in growing pigs caused by PRRSV [5,7–9]. For example, the Large White line had a significantly higher average percent monocyte-derived macrophages positive for PRRSV infection in vitro and in vivo than the Duroc-Pietrain synthetic line [10,11]. The Hampshire pigs had significantly more severe PRRSV-induced macroscopic lung lesions than did the Meishan or Duroc pigs [7]. Meishan pigs had significantly less PRRSV antigen detected in the lungs and significantly higher normalized serum antibody titers to PRRSV than Duroc pigs [12]. PRRS resistance and remarkable differences in susceptibility between breeds may be in part influenced by pig genetic factors. MiRNAs play a vital regulatory role in the immune response and development of PRRS. Numerous eukaryotic miRNAs have been identified to be produced by hosts or viruses and target viral RNAs during infections. Many host miRNAs have been shown to affect diverse processes, including pathogenic diseases and host immunity [13]. For example, let-7 was initially described in C. elegans as a key gene involved in embryonic development and is a highly conserved miRNA in animal species [14]. The let-7 family of pigs includes let-7a, let-7c, let-7d, let-7e, let-7f, let-7g, let-7i and miR-98. More and more studies have shown that let-7 played a crucial role in the regulation of innate and adaptive immune responses, and was involved in the occurrence and development of viral diseases, cancer and other diseases [15,16]. Here, we showed that the let-7 family, which was significantly differentially expressed between PRRSV-infected and mock-infected PAMs from Pietrain, Qingping, Meishan, and Landrace pigs, had a significant inhibitory effect on PRRSV-2 replication in vitro and in vivo. In addition, the let-7 family was downregulated by NEAT1 and ARID3A. The data showed that NEAT1/ARID3A/let-7/IL6 had significant roles in PRRSV-2 infection and may be promising therapeutic targets for PRRS.
To understand the early, middle, and late stages of virus replication, the timing of cell harvesting was set at 6, 12, 24, 36, 48, and 72 hpi. As shown in Fig 1A, the curves continuously increased from 6 hpi to 36 hpi and continuously decreased from 36 hpi to 72 hpi in PAMs of all pig breeds. During 24–72 hpi, the virus copy number was different among the 4 pig breeds. The virus copy number in PAMs of Pietrain and Landrace pigs was higher than that of Qingping and Meishan pigs. According to virus growth curves, PAMs from the Meishan (MS), Landrace (L), Pietrain (P), and Qingping (QP) pig breeds infected with PRRSV for 9 h (early), 36 h (middle) and 60 h (later) were chosen to investigate the effect of PRRSV on PAM miRNAomes. As a control, mock-infected PAMs were collected at the same time (9 h, 36 h, and 60 h). Twenty-four miRNA libraries were constructed and analyzed using Solexa/Illumina deep-sequencing technology.
Differentially expressed miRNAs (DE-miRs) were analyzed using previously reported methods [17–19]. As shown in Fig 1B, the DE-miRs were divided into increased and decreased expression groups. At 9 hpi, Pietrain and Landrace pigs had the largest number of DE-miRs, 121 and 103, respectively. Meanwhile, the total number of DE-miRs in Qingping pigs was the lowest. It seems that virus infection has the least effect on host immunity in Qingping pigs. At 36 hpi and 60 hpi, the number of DE-miRs in Meishan pigs was the largest, 38 and 70, respectively. The let-7 family (ssc-let-7a, ssc-let-7c, ssc-let-7d, ssc-let-7e, ssc-let-7f, ssc-let-7g, ssc-let-7i and ssc-mir-98) was found to be significantly differentially expressed between PRRSV-infected and mock-infected PAMs (Fig 1C). The expression of the let-7 family was significantly lower in mock-infected PAMs from Pietrain pigs than in PAMs from the other three breeds. The results of stem–loop RT–qPCR were consistent with the sequencing results (Fig 1D–1I). In Meishan pigs, let-7 family expression was significantly decreased in PAMs infected with PRRSV-2 for 9 h, while let-7 family expression was significantly increased in PAMs from Pietrain pigs at 9 hpi.
The mature sequences of let-7 family members of monkey and pig were completely consistent. Marc-145 cells, model cells for PRRSV studies, were transfected with the mimic or inhibitors of each let-7 family member (10 nM) and then infected with the PRRSV-2 strain WuH3 at an MOI of 0.1 and the cells were collected at 9 h and 36 h after infection. Compared with NC (negative control) mimics, mimics of the let-7 family, except for let-7d, significantly (p<0.05) or highly significantly (p<0.01) reduced the virus copy number at both 9 hpi and 36 hpi (Fig 2A). In contrast, inhibitors of the let-7 family facilitated PRRSV-2 replication. Meanwhile, the inhibitory effect of let-7a, let-7c, let-7f, let-7i, and mir-98 on PRRSV-2 replication was significantly stronger than that of other let-7 family members (Fig 2B). Moreover, let-7 family members also reduced the expression of the PRRSV-2 N protein in the Western blot assay (Fig 2C).
Previous studies have shown that miRNAs might interact directly with the viral genome RNA to inhibit virus replication [20,21]. The prediction of miRNA target sites showed that the let-7 family could target the 3’UTR (15189 to 15195 bp) of the PRRSV-2 strain WuH3 genome. The 7-bp target region in PRRSV-2 is highly conserved. Furthermore, all members of the let-7 family share an almost identical 7-bp seed region, except let -7d is base A in the first base of the binding site (Fig 2D). Then, we created a reporter construct (PRRSV3’UTR-WT) containing the predicted 7-bp target site in the 3’UTR and another construct (PRRSV3’UTR-MUT) with mutations of four nucleotides in the 7-bp target site. The luciferase reporter assay results showed that let-7a, let-7c, let-7e, let-7f, let-7g, let-7i and mir-98 robustly downregulated the luciferase activity of PRRSV3’UTR-WT. Conversely, the luciferase activity of PRRSV3’UTR-MUT was not affected by the let-7 family (Fig 2E and 2F).
In addition, miRNAs regulate viral replication by targeting host genes, which is also an important pathway. The let-7 family was predicted to target the porcine interleukin 6 (IL6) gene (Fig 3A). The mimics of the let-7 family significantly (p <0.01 or p <0.05) inhibited the activity of the luciferase reporter plasmid containing the IL6 3’ UTR. Inhibitors of the let-7 family, except for let-7d, significantly (p <0.01 or p <0.05) enhanced the luciferase activity. Moreover, the mimics and inhibitors of the let-7 family had no significant effect on the luciferase activity when transfected with the mutant plasmid IL6-MUT (Fig 3B and 3C). Compared with the NC group, the mimics of the let-7 family significantly (p<0.01) reduced IL6 expression, and their inhibitors significantly (p<0.05) increased IL6 expression at the mRNA and protein levels (Fig 3D and 3E). In particular, let-7f had the strongest effect. In addition, the let-7 family also repressed IL6 mRNA and protein expression in PRRSV-infected Marc-145 cells (MOI = 0.1) at 9 hpi and 36 hpi (Fig 3F and 3H). The opposite results were observed in Marc-145 cells transfected with let-7 family inhibitors (Fig 3G and 3I).
IL6 is a well-known pro-inflammatory factor, and its abnormally high expression can lead to tissue damage, and then affect the immune function of the host. The IL6 gene in pigs and monkeys is highly conserved. So, an expression plasmid for porcine IL6 (pCDNA3.1-IL6) was constructed and transfected into Marc-145 cells. The obtained results showed that pCDNA3.1-IL6 enhanced the expression of NF-κB p65 in Marc-145 cells infected with PRRSV-2 (Fig 3J). Let-7e mimics downregulated the expression of NF-κB p65 (Fig 3K). In addition, RT–qPCR results showed that IL6 could significantly (p<0.05) influence the expression of macrophage cationic peptide 1 (MCP-1) and vascular cell adhesion molecule 1 (VCAM-1) (Fig 3L). Let-7e significantly (p<0.05) inhibited the expression of MCP-1 and VCAM-1 (Fig 3M), and play an important role in inflammatory diseases such as lung inflammation/injury.
The ceRNA-miRNA-mRNA cross talk maintains the overall activity and functional balance of gene networks in a cell [22]. The lncRNA–miRNA–mRNA ceRNA network has been theorized to play an indispensable role in many types of diseases [23]. Bioinformatics analysis showed that let-7a, let-7d, let-7f, let-7i, and mir-98 target the 127–135 bp region of NEAT1, let-7c and let-7 g target the 1061–1069 bp region of NEAT1, and let-7e targets the 2612–2619 bp region of NEAT1 (Fig 4A). The luciferase reporter plasmids NEAT1-WT1 (127–135 bp), NEAT1-WT2 (1061–1069 bp) and NEAT1-WT3 (2612–2619 bp) were constructed. The mimics of the let-7 family were transfected into Marc-145 cells with the corresponding luciferase reporter plasmid and the obtained results showed that let-7c, let-7e and let-7g significantly inhibited the luciferase activity (Fig 4B). Meanwhile, significantly increased (p<0.01) luciferase activity was observed when inhibitors of let-7c, let-7e, let-7g and let-7i were transfected with the corresponding luciferase reporter plasmid (Fig 4C). In addition, let-7e mimics had no significant effect (p>0.05) on the luciferase activity of NEAT1-MUT (S1 Fig). The RT–qPCR results showed that NEAT1 expression was significantly elevated in the let-7e inhibitor group and decreased in the let-7e mimic group (Fig 4D). Let-7e expression was significantly downregulated in pCDNA3.1-NEAT1-transfected cells and upregulated in Aso-NEAT1 (Antisense oligonucleotide of NEAT1)-transfected cells (Fig 4E).
NEAT1 was differentially expressed and had an inverse difference from let-7 in different breeds of pigs and between PRRSV-infected and mock-infected PAMs (Fig 4F). To investigate whether NEAT1 regulate PRRSV-2 replication, PAMs were transfected with Aso-NEAT1, pCDNA3.1-NEAT1, pCDNA3.1-NEAT1 + let-7e mimics or matched negative control and infected with PRRSV-2 for 9 h and 36 h. The RT–qPCR and Western blot results showed that Aso-NEAT1 dramatically repressed PRRSV-2 replication (Fig 4G and 4H). On the other hand, overexpression of NEAT1 could conspicuously promote PRRSV-2 replication. Let-7e mimics partially alleviated this trend (Fig 4I and 4J). Furthermore, NEAT1 overexpression significantly increased IL6 expression, while let-7e overexpression partly reduced IL6 expression induced by NEAT1 (Fig 4K and 4L).
The precursor sequences of let-7a-2, let-7f-2 and let-7d come from the same miRNA cluster, which is located on pig chromosome 3 within a ~2647 bp region. A homologous let-7a-1/let-7f-1/let-7d cluster is found on human chromosome 9 and monkey chromosome 15 (Fig 5A). To investigate the transcriptional mechanism of let-7 family, the 1798 bp sequence on the 5´-flanking region of the let-7a-2/let-7f-2/let-7d cluster was obtained through PCR. A series of deletions of the pig let-7a-2/let-7f-2/let-7d potential promoter was used to drive luciferase gene expression and luciferase activity was determined in Marc-145 cells. The deletion of the region ranging from nucleotide -1657 to -623 in the PGL3-D7 (with the first nucleotide of pre-let-7a-2 assigned as +1) increased the promoter activation, which suggests that there are repressor binding sites in the deleted region. The results of further experiments with truncated let-7a-2/let-7f-2/let-7d promoters showed that the fragment from position -623 to position -358 was important for the activation of the let-7a-2/let-7f-2/let-7d promoter (Fig 5B).
Three ARID3A transcription factor-binding sites were predicted in the -623 and -358 regions of the let-7a-2/let-7f-2/let-7d promoter. Furthermore, ARID3A binding sites were also predicted in the 2 kb region upstream of the other let-7 family member. ARID3A was significantly differentially expressed and had an inverse difference from let-7 between PRRSV-infected and mock-infected PAMs from 4 pig breeds (Fig 5C). Then, the three binding sites for ARID3A were mutated in the PGL3-D7 (-623 to +141) plasmid. The mutant plasmid ARID3A-mut-1, ARID3A-mut-2, ARID3A-mut-3.or the wide-type PGL3-D7 plasmid ARID3A-WT was respectively transfected into PAM. The results showed that luciferase activity of the three ARID3A-muts were significantly (p<0.01) higher than that of ARID3A-WT (Fig 5D). This indicated that ARID3A negatively regulated the expression of let-7a-2/let-7f-2/let-7d. Meanwhile, the EMSA was performed with nuclear extracts from PAMs to verify ARID3A binding to the promoter of let-7a-2/let-7f-2/let-7d. The specific DNA–protein complex was found in the biotin-labeled probe group containing the putative ARID3A binding sequences (Lane 2) and was attenuated after the addition of the competitor probe (Lane 3), while the mutated competitor probe failed to attenuate complex formation (Lane 4). The specific complex did not appear without nuclear extracts in Lane 1. Fig 5E, 5F and 5G respectively represent the three binding sites of ARID3A in let-7a-2/let-7f-2/let-7d promoters. Meanwhile, the ChIP assay was also performed. The immunoprecipitates were analyzed by PCR with primers specific to the let-7a-2/let-7f-2/let-7d promoter harboring the ARID3A binding site. These results clearly demonstrate that ARID3A binded the three sites in its promoter (Fig 5H).
To further determine whether ARID3A regulate let-7 expression, pCDNA3.1-ARID3A was cotransfected with PGL3-D7 (ARID3A-WT), ARID3A-mut-1, ARID3A-mut-2 or ARID3A-mut-3. The obtained results showed that the luciferase activity of the three ARID3A-mut plasmids was significantly (p<0.05) higher than that without mutation (Fig 5I). Furthermore, RT–qPCR results showed that overexpression of ARID3A significantly (p<0.05) suppressed the expression of let-7a and let-7f, whereas knockdown of ARID3A significantly (p<0.05) promoted (p<0.05) let-7a and let-7f expression (Fig 5J). To determine whether ARID3A can affect PRRSV replication, pCDNA3.1-ARID3A, pCDNA3.1, si-ARID3A and si-NC were transfected into Marc-145 cells. The obtained results showed that overexpression of ARID3A significantly (p<0.05) promoted PRRSV-2 replication. Meanwhile, the opposite tendency was observed when cells were transfected with si-ARID3A (Fig 5K and 5L) (p<0.05). Furthermore, immunofluorescence assay (IFA) results showed that pCDNA3.1-ARID3A significantly promoted PRRSV-2 replication at 9 hpi and 36 hpi (Fig 5M).
To investigate how NF-κB p65 regulate let-7 expression, Marc-145 cells were pretreated with Bay117082 (5 mM), a specific NF-κB inhibitor, for 1 h prior to PRRSV-2 infection. The RT–qPCR results revealed that Bay117082 significantly promoted the expression of let-7a and let-7f at 9 hpi and 36 hpi (p<0.01) (Fig 6A). Meanwhile, ARID3A was significantly inhibited by Bay117082 (p<0.01) (Fig 6B and 6C). Then, the PGL3-D7 luciferase reporter plasmid was cotransfected with siARID3A, Bay117082 and siARID3A+Bay117082 into Marc-145 cells respectively. The luciferase activity was significantly activated by siARID3A and siARID3A+Bay117082 (Fig 6D). However, Bay117082 alone showed no significant (p>0.05) increase in PGL3-D7 activity. These results suggest that NF-κB p65 regulates let-7 family expression through the transcription factor ARID3A.
To further investigate whether there is a direct interaction mechanism between ARID3A and NF-KB, coimmunoprecipitation (Co-IP) assays were performed in Marc-145 cells. The obtained results showed that ARID3A protein was detected in the immunoprecipitates of the anti-NF-κB p65 group, and NF-κB p65 protein was detected in the immunoprecipitates of the anti-ARID3A group, which demonstrated that ARID3A could interact with NF-κB p65 (Fig 6E). Meanwhile, immunofluorescence and Western blot showed that ARID3A was expressed in both the nucleus and cytoplasm when cells were in a normal state, increased in the nucleus after PRRSV infection, and was expressed in the nucleus and cytoplasm of cells after adding Bay117082 (Fig 6F and 6G). This finding indicated that NF-κB p65 promoted ARID3A nuclear import and regulation of the let-7 family. In addition, immunohistochemistry staining results showed that ARID3A was mainly located in alveolar epithelial cells and alveolar macrophages (Fig 6I). Meanwhile, the protein expression of ARID3A was significantly increased in Marc-145 cells after PRRSV-2 infection (Fig 6H).
To study the role of the let-7 family in pigs infected with PRRSV-2, the recombinant plasmid pEGFP-N1-let-7, which containing all eight let-7 family members coexpressing simultaneously, was constructed (S2A Fig). The obtained results showed that pEGFP-N1-let-7 could significantly (p<0.001) inhibit PRRSV replication and IL6 expression (S2B–S2F Fig). Four-week-old piglets were randomly divided into two groups (n = 3 in each group). The piglets were infected with 105.7 TCID50 of the PRRSV-2 strain WuH3 at 5 h after injection (2.5 mg/kg) of plasmid pEGFP-N1-let-7 (the experimental group) or pEGFP-N1 (the NC group). The RT–qPCR results showed that the expression of the all eight let-7 family members in the pEGFP-N1-let-7 group was significantly higher than that in the pEGFP-N1 group (Fig 7A). The experimental group piglets exhibited a lower rectal temperature than the NC group piglets (Fig 7B). The NC group displayed a range of clinical signs, including inappetence, lethargy, dyspnea, eyelid edema and purple surface on the abdomen. On the tenth day post-infection, all the piglets were sacrificed, and lungs and PAMs were collected. Severe interstitial pneumonia and pulmonary hemorrhages were observed in NC group piglets (Fig 7D). The NC group piglets also presented obvious microscopic lung lesions with more severe lesions, including a disappeared lung structure, numerous inflammatory cells and necrotic debris infiltrated in alveolar spaces and bronchioles, compared with the experimental group piglets (Fig 7E and 7F). The copy number of PRRSV-2 was significantly lower in the lungs and PAMs (p<0.05, decreased by more than 90%) of the experimental group piglets compared with that of the NC group (Fig 7G). IL6 expression was also significantly reduced in the lungs and PAMs (p<0.05) of the experimental group (Fig 7H and 7I). In addition, pEGFP-N1-let-7 also significantly (p<0.05) reduced the expression of MCP-1, VCAM-1, and intercellular adhesion molecule 1 (ICAM-1) in the lungs of the experimental group piglets (Fig 7J). This means that the degree of inflammation/injury in the lungs of the control group is more severe than that of the pEGFP-N1-let-7 experimental group.
Previous studies indicated that the susceptibility of different pig breeds to PRRSV was different. In this study, it was confirmed that the PRRSV-2 copy number was different in PAMs from 4 pig breeds during 24–72 h post-infection. The viral loads of PAMs in Qingping and Meishan pigs were lower than those in Pietrain and Landrace pigs. The expression of the let-7 family in PAMs from Pietrain pigs was significantly lower than that in PAMs from Meishan, Landrace and Qingping pigs. In addition, the let-7 family might inhibit PRRSV-2 replication by binding to the PRRSV-2 3’UTR. This may be one of the reasons why Pietrain pigs’ resistance to PRRSV-2 is significantly lower than that of the other three pig breeds. In the early stages (9 hpi) of PRRSV-2 infection, the expression level of the let-7 family was decreased in Meishan pigs and increased in Pietrain pigs after PRRSV-2 infection. Furthermore, the expression levels of NEAT1 and ARID3A, which inhibit the let-7 family, were significantly increased in PAMs from Meishan pigs and reduced in PAMs from Pietrain pigs. Previous studies indicated that the first 8–10 h of initial infection is critical for the virus to divert host signaling and set up an intracellular environment more beneficial to viral growth [24]. The PRRSV-2 infection promoted the expression of NEAT1 and ARID3A and inhibited the expression of let-7, which created excellent conditions for PRRSV-2 replication in PAMs from Meishan pigs. It may be that it is not necessary for Pietrain pigs to establish a beneficial environment for viral growth due to their low resistance to PRRSV-2. The increase in the let-7 family expression in PAMs from Pietrain pigs inhibited PRRSV-2 replication. Overall, the NEAT1/ARID3A/let-7 family may have important contributions to the susceptibility of different pig breeds to PRRSV-2. IL-6 is a multifunctional cytokine that is produced by a wide range of cells and plays a critical role in the progression of lung inflammation/injury [25]. Previous studies have shown that PRRSV infection causes an increase in IL6 expression levels and leads to lung lesions [26,27]. Our results also confirmed that IL6 could promote the expression of NF-κB, a central transcription factor and a pleiotropic regulator of many genes involved in acute lung injury [28], resulting in sequential signaling cascades and upregulating the expression of proinflammatory cytokines such as MCP-1, VCAM-1, and ICAM-1, which was consistent with previous studies [29–31]. Lung inflammation/injury, which is associated with systemic inflammatory responses, is a common problem with significant morbidity and mortality [32]. A series of adhesion molecules (e.g., VCAM-1 and ICAM-1) and cytokines (e.g., MCP-1, IL-6, and NF-κB) are expressed in inflammatory disorders. Therefore, medications that suppress the expression of proinflammatory cytokines are promising candidates for the treatment and prevention of chronic inflammatory diseases [33]. Previous studies have shown that IL-6 plays an important role in both primary and secondary storms; thus, inhibition of IL-6 has potential value in the treatment of lung inflammation/injury [34]. This is consistent with the constructed plasmid pEGFP-N1-let-7 reducing IL6, NF-κB, MCP-1, VCAM-1, and ICAM-1 expression by approximately 10 times and attenuating lung injury induced by PRRSV in vivo. In addition, with PRRSV infection, IL6 was differentially expressed among different pig breeds, which is consistent with previous reports [24,35] (S3 Fig). Our results confirmed that the let-7 family could significantly inhibit the expression of IL6. The let-7 family is also differentially expressed among 4 pig breeds and has an opposite trend with IL6, suggesting that let-7/IL6 may play an important role in the susceptibility of different breeds of pigs to PRRSV-2. On the other hand, previous studies have revealed that PRRSV-2 infection activates NF-κB signaling in Marc-145 cells and PAMs by inducing IκB degradation and p65 nuclear translocation. Additionally, NF-κB was required for optimal PRRSV replication. [36,37] Thus, the let-7 family inhibited NF-κB activity through IL6, thereby inhibiting PRRSV-2 replication. NEAT1 is known as virus-inducible noncoding RNA [38] and binds with many miRNAs, acting as a miRNA sponge, thus removing the inhibitory effect of miRNA on target genes [39,40]. Our results shown that the expression of NEAT1 and let-7 had a significantly negative correlation in PAMs and found that NEAT1 could regulate let-7 through all three binding sites (S1 Fig). Meanwhile, let-7e overexpression reduced the expression of NEAT1, while let-7e inhibition increased NEAT1 expression. This result suggested that NEAT1 and let-7e participate in a reciprocal repression feedback loop. PRRSV-2 could induce the expression of NEAT1, inhibiting the let-7 family, thereby reducing the anti-PRRSV effect of let-7 and setting up a beneficial environment for PRRSV replication. The overexpression of let-7 could also inhibit the replication of PRRSV-2 by inhibiting NEAT1. MiRNAs are first transcribed in the nucleus [41]. Therefore, ARID3A could affect the formation of pre-let-7 by binding to the promoter of let-7a-2/let-7f-2/let-7d in the nucleus. In addition, Western blot results showed that the expression of ARID3A was upregulated after PRRSV-2 infection. Together, PRRSV-2 could also evade the host’s immune response by increasing ARID3A expression to inhibit let-7 transcription. This phenomenon reveals how PRRSV infection regulates abnormal miRNA expression in host cells. In summary, the let-7 family is regulated by NEAT1 and ARID3A/NF-κB, which are necessary for PRRSV replication. Moreover, pEGFP-N1-let-7, which coexpressed let-7 family members, significantly reduced viral infection and pathological changes in PRRSV-infected piglets (Fig 8).
All animal procedures were approved (HZAUSW2015-018) by the Scientific Ethics Committee of Huazhong Agricultural University, Wuhan, China.
PAMs were isolated by lung lavage from 5-week-old Meishan (MS), Landrace (L), Pietrain (P) and Qingping (QP) pigs as described [42,43]. All pigs tested negative for anti-PRRSV specific antibody and PRRSV antigen by ELISA and RT–PCR assays. Marc-145 cells, a monkey kidney cell line highly permissive for PRRSV infection, were obtained from the State Key Laboratory of Agricultural Microbiology (Huazhong Agricultural University, Wuhan, China). PAMs and Marc-145 cells were cultured in RPMI 1640 medium (Invitrogen, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum (Gibco, Grand Island, NY, USA), 100 U/mL penicillin and 100 mg/mL streptomycin in a humidified 37°C/5% CO2 incubator. The PRRSV-2 strain WuH3 (GenBank accession NO. HM853673) was used to infect PAMs and Marc-145 cells. The virus was also taken from the State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, and Wuhan, China. Virus titers were determined via immunofluorescence staining of the PRRSV nucleocapsid protein in Marc-145 cells and calculated by the Reed-Muench method [44]. The titer of this pool was 105.7 TCID50.
In vitro experimental infection with the PRRSV-2 strain WuH3 was performed on PAMs isolated by bronchoalveolar lavages from MS, L, P and QP pig breeds, with a multiplicity of infection (MOI) of 0.1 PFU/cell. The PRRSV-infected PAMs were collected at 9 hpi, 36 hpi and 60 hpi, and the PAMs of 5 pigs of each breed were evenly mixed. The control group PAMs were mock-infected with culture medium and collected at 9 h, 36 h, and 60 h. Total cellular RNA was prepared using the TRIzol reagent (Invitrogen, Cashman, CA, USA) according to the manufacturer’s instructions.
All RNA samples were quantified and examined for protein contamination (A260 nm/A280 nm ratios) and reagent contamination (A260 nm/A230 nm ratios) by a Nanodrop ND 2000 spectrophotometer (Thermo Scientific, MA, USA). Twenty-four miRNA libraries were constructed. Each library was made from pooled equimolar amounts of total RNA from PAMs of 4 pig breeds at 3 time points. Total RNA was prepared for small RNA sequencing by synthesis according to the procedure and standards of the Illumina Sample Preparation Protocol. Deep sequencing was performed by the Illumina/Solexa Genome Analyzer (BGI, Shenzhen, China).
The raw sequence reads were filtered for composition, presence of adaptor dimers, length, sequence repetition, and copy numbers using SOAP V2.0 [45]. To determine conserved miRNAs, the filtered sequences were initially used to search miRBase with BLASTN, which allowed a maximum of two mismatches, and the gaps were counted as mismatches. The criterion was then implemented according to the reported miRNA protocol [46]. Comparison of the known miRNA expression between the two libraries was conducted to determine the DE-miRs. MiRNAs were first filtered to retain only those with a mean expression value of at least 28 read counts between the two groups [17]. The expression of miRNA was normalized and shown in two libraries by calculating fold-change and p-value [18,19]. A miRNA was labeled as differentially expressed when |log2 (fold change)| ≥1 and p-value ≤0.01. These DE-miRs were further verified by RT–qPCR analysis.
ViTa was used to predict miRNA binding sites in the PRRSV genome. For the conservative analysis of PRRSV, we aligned the potential target sequences in several representative PRRSV strains collected from GenBank. Potential target genes for the let-7 family were predicted by MiRanda, Target Scan, PicTarand, and RNA hybrid 2.2.
For each potential target gene of the let-7 family, miRNA binding sites were amplified from pig genomic DNA using gene-specific primers. The primer sequences are available in S1 Table. Using the Sac I and XhoI restriction sites within the vector, each PCR product was cloned into the pmirGLO vector (Promega, Madison, Wisconsin, USA) and named IL6 3’UTR-WT, PRRSV3’UTR-WT, NEAT1-WT1, NEAT1-WT2, and NEAT1-WT3. The theoretical let-7 family binding sequences in IL6, PRRSV, and NEAT1 were mutated as indicated (IL6 3’UTR-MUT, PRRSV3’UTR-MUT, and NEAT1-MUT3). Marc-145 cells were transfected with a mixture of luciferase reporter plasmids, miRNA mimics or miRNA inhibitors using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The sequences of let-7 family mimics/inhibitors are listed in S2 Table. Cells were maintained in a 24-well plate in DMEM with 10% FBS, penicillin (100 U/ml), and streptomycin (100 mg/ml) at 37°C with 5% CO2. At 24 h posttransfection, cells were lysed in passive lysis buffer (Promega, Madison, Wisconsin, USA), and firefly and Renilla luciferase activities were then measured using the Dual Luciferase Reporter Assay System (Promega, Madison, Wisconsin, USA) according to the manufacturer’s instructions.
Total RNA from Marc-145 cells, PAMs and supernatant PRRSV were extracted with TRIzol (Invitrogen, Carlsbad, CA, USA) following the manufacturer’s instructions, and then M-MLV Reverse Transcriptase was used for reverse transcription according to the manufacturer’s protocol (Promega, Madison, USA). RT–qPCR analysis was performed using a LightCycler 480 Real-Time PCR Detection System (Roche, Basel, Switzerland) and SYBR Green Real-Time PCR MasterMix (Toyobo, Osaka, Japan). The relative expression level was analyzed using the 2-ΔΔCT method. The PRRSV copy number within each sample was calculated using absolute (standard curve) quantification. Gene-specific forward and reverse primers are listed in S3 Table.
Marc-145 cells and PAMs were collected and lysed using RIPA lysis buffer supplemented with fresh protease and phosphatase inhibitors. The protein concentration was determined by the BCA Protein Assay kit (Solarbio, Beijing, China). Equal amounts of each sample were loaded and subjected to SDS–PAGE, transferred onto PVDF membranes (Millipore, Darmstadt, Germany), and then incubated for 12 h at 4°C with the following primary antibodies: IL6 (sc-323975, Santa Cruz, USA), PRRSV nucleocapsid protein (GTX129270, GeneTex, Alton Pkwy Irvine, CA, USA), NF-κB p65 (A11201, Abclonal, Wuhan, China), ARID3A (A7668, Abclonal, Wuhan, China), β-actin (AC026, Abclonal, Wuhan, China), anti-β-tubulin (GB11017B, Servicebio, Wuhan, China), and H3 (A2348, Abclonal, Wuhan, China). After incubation, the PVDF membrane was washed with Tris-buffered saline Tween 20 (TBST) three times and then incubated with HRP-conjugated secondary antibodies (G1213, Servicebio, Wuhan, China). The protein on this membrane was visualized using enhanced chemiluminescence (ECL) (Servicebio, Wuhan, China) in a Western Blotting Detection System.
The pCDNA3.1-IL6 and pCDNA3.1-ARID3A eukaryotic expression plasmids were constructed. Using cDNA as a template, the coding sequences of the IL6 and ARID3A genes were amplified with gene-specific primers. The PCR products were digested with Hind III and EcoR I (Thermo Scientific, MA, USA) and cloned into the pCDNA3.1 vector (Promega, Madison, USA) using T4 DNA Ligase (Takara, Japan). The let-7 family expression plasmid pEGFP-N1-let-7 was constructed in accordance with previous studies. [47,48] The precursor and flanking sequences of the let-7 family were obtained from NCBI. Then, the sequences of pre-let-7a-1, pre-let-7a-2, pre-let-7c, pre-let-7d, pre-let-7e, pre-let-7f-1, pre-let-7f-2, pre-let-7g, pre-let-7i, and pre-mir-98 along with their flanking sequences were amplified from genomic DNA by PCR using specific primers (containing sequences of 20 bp each of adjacent miRNA), and fusion PCR was used to connect pre-let-7a-1, pre-let-7a-2, pre-let-7c, pre-let-7d, pre-let-7e, pre-let-7f-1, pre-let-7f-2, pre-let-7g, pre-let-7i, and pre-mir-98 into miRNA clusters of 1686 bp. The purified PCR product was digested with relevant restriction enzymes (BigI II and Pst I) and inserted into the pEGFP-N1 vector. A stop codon was added between the EGFP gene and multiple cloning sites to stop the translation of EGFP. Nine let-7a-2/let-7f-2/let-7d promoter deletion fragments (D1-D9) were amplified with specific primers. PCR products were digested with SacI and XhoI (Thermo Scientific, MA, USA) and then subcloned into the luciferase reporter vector pGL3-Basic (Promega, Madison, Wisconsin, USA). The ARID3A binding sequences in let-7a-2/let-7f-2/let-7d were mutated as indicated. The primer sequences for plasmid construction are listed in S1 Table. The pCDNA3.1-NEAT1 plasmid was stored in our laboratory.
Nuclear extracts were prepared from PAMs with the Nuclear Extraction Kit (Beyotime, Jiangsu, China). EMSA was performed as described previously. Oligos corresponding to the ARID3A-binding sites of the let-7a-2/let-7f-2/let-7d core promoter were synthesized and annealed into double strands. The DNA-binding activity of the ARID3A protein was detected by a Light-Shift Chemiluminescent EMSA Kit (Thermo Fisher Scientific, Waltham, MA, USA). The probe sequences for EMSA are listed in S4 Table.
The ChIP experiments were conducted to assess the binding of endogenous ARID3A to the let-7a-2/let-7f-2/let-7d promoter in PAMs using a ChIP Assay Kit (Beyotime, Jiangsu, China). Precleared chromatin was incubated with the ARID3A antibody (Abclonal, Wuhan, China) or the nonimmune IgG (Beyotime, Jiangsu, China) control overnight at 4°C. The immunocomplexes were isolated on Protein A agarose beads with a ChIP Assay Kit (Beyotime, Jiangsu, China). The chromatin complexes were eluted from the beads, and DNA cross-linking was subsequently reversed. Purified DNA from the samples and the input controls was analyzed for the presence of let-7a-2/let-7f-2/let-7d promoter sequences containing putative ARID3A response elements using PCR, and the primers are listed in S5 Table.
Marc-145 cells cultured in 10-cm-diameter dishes were collected and lysed in nondenaturing lysis buffer (Sangon, Shanghai, China) supplemented with protease and phosphatase inhibitor cocktails. An equal mass of lysate was incubated overnight with 2 μg of anti-ARID3A (A7668, Abclonal, Wuhan, China), anti-p65 (A11201, Abclonal, Wuhan, China) or anti-IgG (Beyotime, Jiangsu, China) together with 25 μl of Protein A+G Agarose beads (Beyotime, Jiangsu, China). After centrifugation, the beads were washed with 1 mL of lysate buffer three or four times. Then, 15 μl of 2×SDS loading buffer was added to the beads, boiled for 10 min, and loaded onto an SDS–PAGE gel for western blot analysis.
Marc-145 cells were immediately fixed with 4% paraformaldehyde for 30 min. For immune detection, the cells were permeabilized in 0.1% Triton X-100 (Sigma–Aldrich, St. Louis, MO) for 20 min at room temperature and incubated with 10% normal goat serum for 1 h. After blocking nonspecific binding, the coverslips were incubated overnight with mouse monoclonal anti-ARID3A antibody (sc-398367, Santa Cruz, CA, USA) and anti-PRRSV N protein (GTX129270, GeneTex Inc., Irvine, CA, USA) at 4°C. The cells were then incubated with the corresponding secondary antibody (Servicebio, Wuhan, China) in PBS for 2 h at room temperature. The coverslips were then stained with DAPI (Servicebio, Wuhan, China). The stained cells were subsequently observed using an Olympus BX-51 fluorescence microscope (Olympus, Tokyo, Japan).
ARID3A immunohistochemical staining was evaluated in fixed lungs of uninfected pigs and PRRSV-infected pigs. Inflation-fixed lungs were washed in phosphate-buffered saline (PBS) three times and separated for paraffin embedding. The paraffin-embedded lungs were sectioned at 6 μm for immunohistochemical staining of ARID3A, and tissue sections were deparaffinized by washing in xylene three times for 10 min each, followed by rehydration through a series of ethanol washes from 100% to 70% ethanol. Slides were placed in methanol containing 0.5% hydrogen peroxide for the removal of endogenous peroxidase activity. Nonspecific binding was blocked by incubation of the slides for 1 h at room temperature in 5% BSA. Lung sections were incubated with anti-ARID3A antibody (A7668, ABclonal, Wuhan, China) overnight at 4°C. Sections were rinsed in 0.1 M PBS (pH 7.2–7.4) five times for 5 min each and incubated for 30 min at room temperature with secondary antibody. Sections were washed with PBS five times for 5 min each, incubated with diaminobenzidine for 6 min, washed with running water for 6 min, stained with hematoxylin for 40 s and washed with running water for 5 min. In addition, the primary antibody was substituted with PBS, and the controls were performed under the same conditions described earlier.
Six four-week-old piglets were divided into two groups: the pEGFP-N1-let-7 treatment group and the pEGFP-N1 control group. PEGFP-N1-let-7 or pEGFP-N1 (2.5 mg/kg of body weight per dose) was mixed with D5W solution to finally obtain a 3-ml mixture solution. This 3-mL solution was administered to piglets through intramuscular injection. At 5 h post-intramuscular injection, 1.5 mL of the PRRSV-2 strain WuH3 (105.2 TCID50) was administered to piglets. The rectal temperature was measured twice a day. On day 10, we performed pathological dissection and collected all the lungs and PAMs of the piglets. The sacrificed pigs were removed, and the animal experiments were performed by random and blinded methods. In the in vivo experiment, there were three replicates for each of the two groups. All experiments were performed at least three times in triplicate, excluding average rectal temperatures.
All experiments were performed at least three times. Data are presented as the mean ± SD. Statistical analyses between different groups were performed using the t-test. The nonparametric Mann–Whitney statistical test was used in the in vivo experiment due to the small number of animals available. A p value of less than 0.05 was considered statistically significant, and a p value of less than 0.01 was considered highly statistically significant.
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PMC9550178 | 36170207 | Govind Kunduri,Si-Hung Le,Valentina Baena,Nagampalli Vijaykrishna,Adam Harned,Kunio Nagashima,Daniel Blankenberg,Izumi Yoshihiro,Kedar Narayan,Takeshi Bamba,Usha Acharya,Jairaj K. Acharya | Delivery of ceramide phosphoethanolamine lipids to the cleavage furrow through the endocytic pathway is essential for male meiotic cytokinesis | 28-09-2022 | Cell division, wherein 1 cell divides into 2 daughter cells, is fundamental to all living organisms. Cytokinesis, the final step in cell division, begins with the formation of an actomyosin contractile ring, positioned midway between the segregated chromosomes. Constriction of the ring with concomitant membrane deposition in a specified spatiotemporal manner generates a cleavage furrow that physically separates the cytoplasm. Unique lipids with specific biophysical properties have been shown to localize to intercellular bridges (also called midbody) connecting the 2 dividing cells; however, their biological roles and delivery mechanisms remain largely unknown. In this study, we show that ceramide phosphoethanolamine (CPE), the structural analog of sphingomyelin, has unique acyl chain anchors in Drosophila spermatocytes and is essential for meiotic cytokinesis. The head group of CPE is also important for spermatogenesis. We find that aberrant central spindle and contractile ring behavior but not mislocalization of phosphatidylinositol phosphates (PIPs) at the plasma membrane is responsible for the male meiotic cytokinesis defect in CPE-deficient animals. Further, we demonstrate the enrichment of CPE in multivesicular bodies marked by Rab7, which in turn localize to cleavage furrow. Volume electron microscopy analysis using correlative light and focused ion beam scanning electron microscopy shows that CPE-enriched Rab7 positive endosomes are juxtaposed on contractile ring material. Correlative light and transmission electron microscopy reveal Rab7 positive endosomes as a multivesicular body-like organelle that releases its intraluminal vesicles in the vicinity of ingressing furrows. Genetic ablation of Rab7 or Rab35 or expression of dominant negative Rab11 results in significant meiotic cytokinesis defects. Further, we show that Rab11 function is required for localization of CPE positive endosomes to the cleavage furrow. Our results imply that endosomal delivery of CPE to ingressing membranes is crucial for meiotic cytokinesis. | Delivery of ceramide phosphoethanolamine lipids to the cleavage furrow through the endocytic pathway is essential for male meiotic cytokinesis
Cell division, wherein 1 cell divides into 2 daughter cells, is fundamental to all living organisms. Cytokinesis, the final step in cell division, begins with the formation of an actomyosin contractile ring, positioned midway between the segregated chromosomes. Constriction of the ring with concomitant membrane deposition in a specified spatiotemporal manner generates a cleavage furrow that physically separates the cytoplasm. Unique lipids with specific biophysical properties have been shown to localize to intercellular bridges (also called midbody) connecting the 2 dividing cells; however, their biological roles and delivery mechanisms remain largely unknown. In this study, we show that ceramide phosphoethanolamine (CPE), the structural analog of sphingomyelin, has unique acyl chain anchors in Drosophila spermatocytes and is essential for meiotic cytokinesis. The head group of CPE is also important for spermatogenesis. We find that aberrant central spindle and contractile ring behavior but not mislocalization of phosphatidylinositol phosphates (PIPs) at the plasma membrane is responsible for the male meiotic cytokinesis defect in CPE-deficient animals. Further, we demonstrate the enrichment of CPE in multivesicular bodies marked by Rab7, which in turn localize to cleavage furrow. Volume electron microscopy analysis using correlative light and focused ion beam scanning electron microscopy shows that CPE-enriched Rab7 positive endosomes are juxtaposed on contractile ring material. Correlative light and transmission electron microscopy reveal Rab7 positive endosomes as a multivesicular body-like organelle that releases its intraluminal vesicles in the vicinity of ingressing furrows. Genetic ablation of Rab7 or Rab35 or expression of dominant negative Rab11 results in significant meiotic cytokinesis defects. Further, we show that Rab11 function is required for localization of CPE positive endosomes to the cleavage furrow. Our results imply that endosomal delivery of CPE to ingressing membranes is crucial for meiotic cytokinesis.
Eukaryotic cells display high diversity in lipid species that are chemically and structurally distinct. They are classified into 8 major categories, each of which is further subdivided into classes and subclasses [1]. Lipids usually comprise of a polar head group that is linked by a structural backbone to a hydrophobic tail composed of acyl chains. Cellular lipid diversity arises from the large number of combinatorial chemical possibilities that the head and tail moieties can generate. Diversification of lipids to cope with evolving cellular complexity has resulted in thousands of lipid species with purported unique functions, most of which still remain unknown [2]. The head groups of each lipid class have been widely recognized for their biological function. For example, the inositol head group of phosphatidylinositol phosphates (PIPs) and its modifications play critical roles in cellular signaling [3]. However, even within each lipid class, there are molecularly distinct species that have identical head group but differ extensively in their acyl side chains, such as number of carbon atoms, number of double bonds, and the nature of the chemical linkage (e.g., ester or ether). An increasing number of studies are beginning to reveal the importance of acyl side chains by demonstrating that they selectively bind to target proteins and elicit distinct biological functions [4,5]. For example, a recent study showed that the acyl side chains of diacylglycerol significantly influence the recruitment of protein kinase C to the plasma membrane [6]. Similarly, the chain length of ceramide was shown to be critical for selective protein cargo sorting at endoplasmic reticulum (ER) exit sites in yeast [7]. The COPI machinery protein p24 bound specifically to N-stearoyl sphingomyelin (SM C18) and functioned as a cofactor to regulate COPI-dependent transport in the early secretory pathway. Further, this interaction depended on both the head group and the backbone of the sphingolipid [8]. Cytokinesis is the final step in cell division that divides 1 cell into 2 daughter cells. During cytokinesis, an actomyosin contractile ring is formed that is positioned midway between the segregated chromosomes. Narrowing of this ring with the addition of membrane in a spatiotemporally defined mode produces a cleavage furrow that physically divides the cytoplasm [9]. During somatic cytokinesis, the 2 daughter cells are interconnected via intercellular bridges prior to abscission. Although these structures are transient, they accumulate distinct lipid species to mediate correct cell division [10–12]. Unlike somatic cytokinesis, in testis, the developing spermatogonial cells divide synchronously with an incomplete cytokinesis where all the daughter cells remain interconnected by cytoplasmic bridges. Thus, the spermatogonial cells develop as a syncytium and become separated from each other only at the end of spermatogenesis during spermatid individualization [13]. Lipids have been shown to participate in cytokinetic furrow ingression, midbody structure stabilization, and abscission during cytokinesis [14,15]. The high degree of membrane curvature necessary for cleavage furrow ingression and stabilization of intercellular bridges (ICB)/cytoplasmic bridges necessitates lipid components with specific biophysical properties. While the importance of very long chain fatty acids (which are components of sphingolipids and glycosphingolipids) in cytokinesis has been shown, the relationship between membrane lipid composition, ring constriction, and furrow ingression is still underexplored [14,16]. Although sphingomyelins containing very long chain polyunsaturated fatty acids (VLC-PUFAs) have been identified in various mammalian testes including humans, their direct role in spermatogenesis, particularly in meiotic cytokinesis remains unknown [17,18]. Other lipids including PIPs, cholesterol, and phosphatidylethanolamine (PE) have been shown to be enriched at the cytokinetic furrow [14]. Midbodies also accumulate specific lipids including sphingolipids, phosphatidylserine (PS), phosphatidic acid (PA), and even unique triacylglycerols [12,15]. However, specific mechanisms involved in the delivery of these lipids to the cytokinetic furrow or midbodies remain poorly understood. Membrane traffic via exocytic and endocytic mechanisms has been shown to be essential for successful completion of cytokinesis [19–23]. However, only few studies have focused on individual lipid trafficking via exocytic pathways [24–26] and whether endocytic pathways play direct roles in delivering specific lipids to the cytokinetic furrow or midbody remain unknown. Ceramide phosphoethanolamine (CPE) is a structural analog of sphingomyelin (SM) in Drosophila melanogaster. CPE is synthesized in the luminal compartment of trans Golgi by ceramide phosphoethanolamine synthase (CPES) (Fig 1A). Previously, we have shown that cpes null mutants show significant late pupal lethality during development and only about 25% of mutants survive to adulthood. About 60% of cpes mutant adults have dorsal closure defects and all the mutant males are sterile. Aged cpes mutant adults display light inducible seizures and paralysis due to defective cortex glia [27]. In this study, we show that CPE has unique acyl chain anchors in spermatocytes and is essential for meiotic cytokinesis, spermatid polarity, and individualization. The head group of CPE is also important for spermatogenesis. CPES expression in transit amplifying to the spermatocyte stage is essential for successful completion of spermatogenesis. We show that aberrant central spindle behavior, but not mislocalization of PIPs at the cleavage furrows, is responsible for the meiotic cytokinesis defect in cpes mutants. Further, we show that endocytically retrieved CPE from the plasma membrane is enriched in Rab7 positive multivesicular bodies that dock to the ingressing membranes and release intraluminal vesicles in their vicinity. Our results demonstrate the importance of CPE-rich membrane addition at the cleavage furrow involving the endocytic pathway.
To investigate sphingolipid species diversity and their role in Drosophila tissues, we performed supercritical fluid chromatography coupled to mass spectrometry (SFC/MS/MS) on lipids from wild-type fly head, dissected ovary, and testis (S1 Data). As shown in Fig 1B, CPE is a more abundant sphingolipid compared to ceramides (Fig 1C) and hexosylceramides (HexCer) (Fig 1D). The amount of CPE was significantly higher in the testis compared to the head and ovary (Fig 1B). In contrast, hexosylceramides were significantly higher in heads compared to ovary and testis (Fig 1D). Closer examination of acyl chain composition revealed that head and ovary-derived CPEs are predominantly composed of sphingosine linked to saturated fatty acid (SPH_SFA) (Fig 1E and 1F). Interestingly, in addition to SPH_SFA, CPE in the testis is enriched in 2 distinct species with net 2 double bonds in their acyl chain composition including sphingosine (1 double bond) linked to monounsaturated fatty acid (SPH_MUFA) (Fig 1E and 1G) and a sphingadiene (2 double bonds) linked to saturated fatty acid (SPD_SFA) (Fig 1E and 1H). The fatty acid acyl chain lengths of these CPE species are predominantly C20, C22, C24, and therefore could be classified as very long chain (VLC) sphingolipids. The sphingoid base acyl chain length is d14 and d16 (Fig 1G and 1H). The corresponding ceramide precursors are also evident in the wild-type testis samples indicating acyl chain diversity is likely introduced during ceramide synthesis but not after CPE synthesis (Fig 1C and S1 Data). Remarkably, SPH_MUFA and SPD_SFA are also present in HexCer but at significantly lower levels in the testis compared to heads (Fig 1D versus Fig 1B). The fatty acid acyl chain length of HexCer_SPH_MUFA and HexCer_SPD_SFA showed that they are predominantly C18 and C20 while the sphingoid base is primarily d14 and d16 (S1B, S1D, and S1E Fig). HexCer with d14 sphingosine base and C22 PUFA (SPH-PUFA) is enriched in heads compared to testis (Figs 1D, S1C, and S1E). Taken together, these results suggest that CPE in the testis and HexCer in the central nervous system have a unique acyl chain composition.
To understand the biological significance of the unique CPE species in the testis, we reasoned that the cpes null mutant generated by us would serve as a suitable tool since cpes mutant males are sterile [27]. Immunostaining of cpes mutant testis with antibody to Vasa protein, a germ cell-specific conserved RNA helicase [28], showed accumulation of germ cells at the tip of the testis (Fig 2B) and DNA-specific staining with DAPI showed absence of mature sperm in seminal vesicles. To investigate cytological defects in cpes mutant testis, we performed live testis squash preparations followed by phase contrast microscopy. This method allows for easy identification of almost all of the major stages of spermatogenesis [29]. During meiotic divisions, chromosomes and mitochondria are equally partitioned to each of the 4 daughter cells. Immediately following meiosis, in the round spermatid stage, mitochondria in each daughter cell aggregate to form a large phase dark structure known as the nebenkern. Round spermatids (onion stage spermatids) are characterized by phase dark nebenkern and phase light nucleus at roughly equal size and at a ratio of 1:1 per daughter cell. The nuclear size of round spermatids is directly proportional to the chromatin content; hence, any errors in chromosome segregation during meiosis can lead to variability in nuclear size [30,31]. Similarly, defects in meiotic cytokinesis following normal chromosome segregation results in cells with 2 or 4 nuclei and an abnormally large nebenkern. This change can be easily visualized by phase contrast microscopy and is often used as a diagnostic to detect male meiotic defects [31–37]. As shown in Fig 2D, wild-type round spermatids contained an equal-sized phase light nucleus and a phase dark nebenkern at a ratio of 1:1 per cell within the cyst of 64 cells. In contrast, cpes mutant round spermatids showed 4 regularly sized nuclei (tetranucleate) and 1 abnormally large nebenkern, indicating a failure in cytokinesis in both meiosis I and II divisions (Fig 2E). Quantification of this defect suggested 80% of the round spermatids were tetranucleate and about 20% showed 2 nuclei (Fig 2M). We did not observe single nucleated round spermatids in cpes mutant testes (Fig 2M). This defect is unique to male meiotic cytokinesis since larval neuroblasts undergoing asymmetrical mitotic division did not show defects in cytokinesis (S1 Movie). Females were largely fertile indicating normal oogenesis. Also, during spermatogenesis, we did not observe any defect in the formation of 16 cell staged spermatogonia/spermatocytes indicating that mitotic cytokinesis, even in the testis of cpes mutants, was not compromised. Following the round/onion stage, the 64 interconnected haploid cells in the cyst become highly polarized with the nuclei localizing to one end and the sperm tails (axonemes) growing in the opposite side. These elongating spermatid nuclei face toward the seminal vesicles and the tails grow toward the germline stem cell hub/tip of the testis. As shown in Fig 2G, wild-type early elongating spermatids had all the nuclei facing one side and their axonemes growing to the opposite side indicating that they are highly polarized. In contrast, all the elongating spermatids in cpes mutant cysts appeared sickle cell shaped with the nuclei present in the middle-bulged area (occasionally throughout the cyst) and their tails growing on both sides of the cyst (Fig 2H). This data indicates that spermatid polarity is compromised in cpes mutants. Individualization is the final stage of spermatid differentiation wherein structures called the individualization complex (IC) containing actin cones assemble at the head/rostral end of elongated spermatids and start moving away from the nuclei toward the tail/caudal end of the cyst. As the IC travels, it removes the cytoplasmic contents of the cyst and individualizes each spermatozoon with its own plasma membrane. The extruded cytoplasmic content is collected into a sac-like structure called the “cystic bulge” that forms around the IC. As this process proceeds and the IC and cystic bulge reach the end of the flagella, the actin cones and cytoplasmic contents are extruded in a waste bag, the contents of which are degraded later [38]. Activated caspases have a non-apoptotic role in the cystic bulge and the waste bag of individualizing spermatids and are essential for successful spermatid individualization [39]. Immunostaining of wild-type testis with cleaved Drosophila Caspase 1 (DCP-1) antibody showed elongated spermatids undergoing individualization that contained cystic bulges and waste bags (Fig 2J). In contrast, cpes mutant testis showed defectively elongated spermatids and was devoid of cystic bulges and waste bags indicating failure in spermatid individualization (Fig 2K). The meiotic cytokinesis, spermatid polarity, and individualization defects of cpes mutants are fully penetrant (100%) and ubiquitous expression of wild-type cDNA copy of CPES completely rescued all male sterility phenotypes (Fig 2C, 2F, 2I, 2L and 2M). As shown in Fig 2F, phase contrast imaging of live testis squash preparations showed 1:1 nebenkern to nucleus ratio indicating rescue of meiotic cytokinesis defect. Further, immunostaining of testis squash preparations with tubulin antibody and DAPI showed that spermatid polarity was completely restored wherein all the nuclei faced one side and their tails faced the other side of the cyst (Fig 2I). DCP-1 staining showed individualizing spermatids with cystic bulges and waste bags indicating normal individualization (Fig 2L). To investigate the sphingolipid content in cpes mutant, we dissected wild type, cpes mutant, and germ cell-specific rescue (bam-Gal4> UAS-CPES) testes, sphingolipids were extracted and analyzed by SFC/MS/MS as described in the methods (S1 Data). The mutant and rescue samples were processed at the same time as the wild type for mass spectrometry; hence, the wild-type testis sample is the same as in Fig 1 (S1 Data). There was complete loss of CPE in cpes mutant testis (Fig 2N) and expression of CPES only in the germ cells was sufficient to restore CPE to near wild-type levels. Loss of CPE synthesis in cpes mutants caused concurrent accumulation of ceramides particularly SPH_MUFA and SPD_SFA species (Fig 2O) and expression of CPES in germ cells reduced ceramide levels. HexCer levels were also slightly increased in cpes mutant testis (Fig 2P). Interestingly, expression of CPES in germ cells did not reduce the HexCer levels indicating their levels did not correlate with the cpes mutant phenotypes in the testis.
To determine whether enzymatic activity of CPES is required for spermatogenesis, we generated an active site mutant of CPES. CPES has a conserved amino acid motif D(X)2DG(X)2 (A/Y)R(X)8-16G(X)3D(X)3D in the CDP-alcohol phosphotransferase (CAPT) domain [40]. The final aspartates of this motif were shown to be essential for catalysis of human choline/ethanolamine phosphotransferase CEPT1 [41,42]. We substituted the last 2 active site aspartates of CPES with alanine residues and subcloned into pUAST vector for generating transgenic flies. The UAS_CPES (DX3D to AX3A) mutant transgene was expressed in cpes mutant background using bam-Gal4 to test if spermatogenesis phenotypes could be rescued. As shown in S2A and S2B Fig, the active site mutant did not rescue spermatogenesis phenotypes suggesting a crucial role for CPES enzymatic activity in spermatogenesis. We next investigated whether accumulation of ceramide at the Golgi is responsible for the observed phenotypes. Ceramide is generated in the membranes of ER via the de novo biosynthetic pathway catalyzed by the rate-limiting enzyme serine palmitoyltransferase (SPT) (Fig 1A). Subsequently, ceramide is actively transported from ER to Golgi via ceramide transfer protein (DCERT) and thus absence of DCERT could prevent ceramide accumulation at the Golgi (Fig 1A) [43]. To investigate whether blocking ceramide transport from ER to Golgi could restore spermatogenesis, we generated cpes and dcert1 double mutants and their testes were analyzed for meiotic cytokinesis and spermatid polarity phenotypes. However, as shown in S2C and S2D Fig, cpes; dcert1 double mutants did not rescue meiotic cytokinesis and spermatid polarity indicating ceramide accumulation at the Golgi (due to lack of CPES activity in the Golgi) may not be responsible for cpes mutant phenotypes. In Drosophila, transgenic expression of neutral ceramidase was shown to reduce ceramide levels in vivo [44]. We overexpressed ceramidase (UAS CDase) in germ cells using bam-Gal4 in cpes mutant background and testes from the resulting progeny were analyzed for the rescue of mutant phenotypes. However, expression of CDase did not rescue meiotic cytokinesis and spermatid polarity (S2E and S2F Fig), suggesting that absence of CPE but not accumulation of ceramide is responsible for the phenotypes.
Spermatogenesis is a conserved process across various taxa that is facilitated by highly dynamic transcriptome. An earlier study leveraged single cell RNAseq and unsupervised clustering to identify all the major cell classes of the sperm lineage and validated them with previously studied marker genes [45]. To characterize cell type-specific transcriptional signatures in cpes mutants in vivo, we performed total RNA-seq with dissected testis from w1118, cpes mutant, and bam-Gal4>UAS CPES rescue. Using Gene Set Enrichment Analysis (GSEA), we compared our RNAseq results with the top 50 expressed genes from each cell type/cellular status that were previously classified to confirm the presence of germline stem cells (GSCs), spermatogonia, spermatocytes, and spermatids (germ cells) as well as cyst stem cells, terminal epithelial cells, and hub cells (somatic cells) [45]. We found that gene sets corresponding to GSC, early spermatogonia, and late spermatogonial cells were enriched in cpes mutants compared to wild type and rescue testis (S3 Fig). In contrast, gene sets corresponding to early and late spermatocytes, early, and mature spermatids were enriched in wild type and rescue testis compared to cpes mutant testis (S3 Fig). These results suggested that CPES might play important roles during late spermatogonial, early, and late spermatocyte stages for successful completion of spermatogenesis. To determine the stage of germ cell differentiation at which CPES expression is important, we performed cell type/stage-specific rescue experiments using UAS/Gal4 system in the cpes mutant background (Fig 3A). We first expressed UAS-CPES in cyst cells using C587-Gal4 to investigate a possible non-cell autonomous role. C587-Gal4 was expressed in all early somatic cells at the apical tip of the testis including somatic cyst stem cells and cyst cells (S4D and S4H Fig) [46]. As shown in Fig 3, expression of wild-type CPES in cyst cells did not rescue meiotic cytokinesis, spermatid polarity, or individualization defects (Fig 3B, 3F and 3J, respectively). We next expressed wild-type UAS-CPES in germ cells using 3 different Gal4 drivers that have been previously shown to be specifically expressed in stem cells (nos-Gal4), transit amplifying spermatogonial cells (bam-Gal4), and early spermatocytes (chif-Gal4) (Fig 3A). Nanos (nos) gene encodes for an RNA-binding protein involved in the formation of translational repressor complex. It is required for germ plasm organization, germline development, germline stem cell renewal, and neuronal morphogenesis [47–49]. nanos-Gal4-VP16 has been routinely used to specifically express a transgene of interest in male and female germline stem cells. This construct consists of 700 bp nos promoter, Gal4-VP16 ORF, nos 3′ UTR, and 500 bp of 3′ genomic nos transcription unit. In male germ line nos-Gal4 primarily expresses in GSC and early spermatogonial stages [50]. Bag of marbles (bam) gene encodes for a fusome (a germ cell-specific organelle)-associated protein. The Bam protein is required for activation of the switch from spermatogonia to spermatocytes. The bam-Gal4-VP16 construct has been successfully used to drive transgene expression in late spermatogonia and early spermatocytes in Drosophila. This construct consists of 900 bp bam promoter, 500 bp bam 5′UTR, Gal4:VP16 ORF, and HSP70 3′UTR. Although transgenes driven with bam-Gal4-VP16 express in late spermatogonia through early spermatocytes, the peak expression was shown to occur in spermatocytes [51]. Gene trap Gal4 insertion collection screen identified Chiffon-Gal4 to drive transgene expression specifically in early spermatocytes and somatic cysts cells [52]. To verify the expression pattern of these Gal4 drivers in our experimental settings, we have crossed nos-Gal4 (BDSC#4937) with various pUASP/pUAST-GFP-tagged proteins including pUASP-alpha-Tubulin-GFP, pUAST-EGFP, and pUAST-PLCδ-PH-EGFP. As expected, nos-Gal4 expression is restricted to early germ cells present at the tip of the testis including GSCs and early spermatogonial cells (S4A, S4E, and S4I Fig). On the contrary, bam-Gal4 expression is strong just below the testis tip where spermatogonia and early spermatocytes are expected to be present (S4B, S4F and S4J Fig). However, depending on the stability of the expressed protein, bam-Gal4-mediated expression is either restricted to spermatogonia and early spermatocytes (e.g., PLCδ-PH-EGFP, S4J Fig) or persisted through later stages including early, later spermatocytes, and even in spermatids (e.g., Alpha tubulin and EGFP, S4B and S4F Fig). Expression of chif-Gal4 was detectable in spermatocytes (S4C Fig) but more strongly in elongated spermatids (S4G and S4K Fig). Interestingly, as shown in Fig 3, we observed varying degree of rescue, depending on the germ cell differentiation stage at which UAS-CPES was expressed. The nos-Gal4-dependent expression of UAS-CPES partially rescued both meiotic cytokinesis (Fig 3C and 3N) and spermatid polarity (Fig 3G); however, individualizing spermatids lacked cystic bulges and waste bags indicating individualization was not fully rescued (Fig 3K). The bam-Gal4-dependent expression of UAS-CPES in transit-amplifying cells completely rescued meiotic cytokinesis (Fig 3D and 3N) and spermatid polarity and individualizing spermatids contained cystic bulges and waste bags (Fig 3H and 3L). In contrast, only partial rescue of meiotic cytokinesis was observed when UAS-CPES was expressed in spermatocytes using chif-Gal4 (Fig 3E and 3N). Although spermatid polarity was completely rescued, the individualizing spermatids largely lacked cystic bulges and waste bags indicating that individualization was defective (Fig 3I and 3M). To determine the extent to which male fertility was rescued by cell type-specific CPES expression compared to wild type, we performed male fertility tests. As shown in Fig 3O, expression of UAS CPE in transit amplifying spermatogonial cells and spermatocytes (bam-Gal4) rescued male fertility to wild-type levels. In contrast, partial rescue was observed when UAS-CPES was expressed only in stem cells (nos-Gal4) or in spermatocytes (chif-Gal4). Expression of UAS-CPES in cyst cells (C587-Gal4) did not rescue male sterility as all males were sterile (Fig 3O). To determine in vivo CPES localization more precisely at the protein level, we have generated a construct with a 6,437 bp extended CPES genomic fragment that was modified by recombineering to carry V5-tag at the C-terminus [27]. Transgenic flies expressing genomic CPES tagged with V5 at the C-terminus fully rescued lethality, photosensitive epilepsy, and all other phenotypes including spermatogenesis defects. Immunostaining followed by confocal imaging showed that CPES-V5 was highly expressed in the cells that are present just below the tip of the testis (Fig 3P and 3S). This area of the testis is known to be enriched in late spermatogonia and early spermatocytes [29]. Taken together, these results show that testis-specific CPE generation by CPES from late spermatogonia stage to spermatocyte stage is crucial for successful meiotic cytokinesis, spermatid polarity, and spermatid individualization.
Previously, we have shown that CPE has an important structural role in cortex glial plasma membranes [27]. The cortex glial plasma membranes are severely defective in cpes mutants leading to loss of cortex glia and neuronal cell body interactions during development and increased susceptibility to light inducible epilepsy in adults. Further, we have shown that overexpression of human sphingomyelin synthase 1 (hSMS1) that produces SM instead of CPE was sufficient to rescue cortex glia plasma membrane defects via establishment of detergent resistant membranes. We wondered whether overexpression of hSMS1 could also rescue the spermatogenesis phenotypes of cpes mutant. To this end, UAS-hSMS1 was ubiquitously expressed using tubulin-Gal4 in cpes, the adult male testes were dissected, and live testis squash preparations were observed using phase contrast microscopy. However, as shown in S5A Fig, hSMS1 overexpression did not rescue male meiotic cytokinesis. Further, immunostaining analysis showed that spermatid polarity was also not rescued (S5E Fig), suggesting an important role for the CPE head group in spermatogenesis. We next investigated whether expression of other insect-derived CPES could rescue cpes mutant phenotypes. To test this, we ubiquitously expressed Aedes aegypti (yellow fever mosquito, amino acid sequence shows 60% identity and 77% similarity) and Bombyx mori (domestic silk moth, amino acid sequence shows 43% identity and 58% similarity) derived UAS-CPES homologs in cpes mutant background using tubulin-Gal4. As shown in S5 Fig, mosquito and silk moth CPES were able to completely rescue defects in meiotic cytokinesis (S5B–S5D Fig) and spermatid polarity (S5F and S5G Fig, respectively). To investigate the nature of sphingolipid species synthesized by hSMS1, A. aegypti, B. mori derived CPES, we specifically expressed these transgenes in germ cells using vasa-Gal4, their male reproductive system was dissected, lipids were extracted and subjected to sphingolipid analysis using SFC/MS/MS as described in the methods section (S3 Data). As shown in S5H Fig, germ cell-specific expression of Drosophila CPES, B. mori CPES completely restored CPE to the wild-type amounts. A. aegypti CPES also synthesized significant amount of CPE but to a lower amount than Drosophila CPES. Still, all 3 distinct CPE species are synthesized by A. aegypti CPES and Bombyx CPES (S5H Fig). As anticipated, hSMS1 did not synthesize CPE, but produced significant amount of SM (S5K Fig). However, the amount of SM is relatively low compared to CPE, perhaps due to limited expression/stability of hSMS1 in germ cells (vasa-Gal4). Indeed, ubiquitous expression of hSMS1 using actin-Gal4 driver significantly increases the SM amounts (S5L Fig). However, expression of hSMS1 with ubiquitous drivers like actin-Gal4 and tubulin-Gal4 did not rescue the spermatogenesis defects (S5A and S5E Fig) suggesting the importance of the CPE head group. We next analyzed the ceramide content in these samples and found that ceramide levels were significantly higher in cpes mutants and hSMS1 rescue compared to Drosophila CPES rescue (S5I Fig). However, as discussed in S2 Fig, higher ceramide content might not contribute to the cytokinetic defects in cpes mutants. Similarly, higher amounts of HexCer in A. aegypti CPES rescue and B. mori CPES rescue also did not correlate with the rescue of spermatogenesis phenotypes (S5J Fig). Taken together, these results suggest that Drosophila spermatogenesis is strictly dependent on CPE and the head group of CPE plays an important role.
Precise organization of central spindle microtubules is not only required for initial cleavage furrow formation but also for maintenance of contractile structures during furrow ingression. Several microtubule interacting proteins including Fascetto, kinesin 6 family member MKLP1/Pavarotti (pav), Chromokinesin klp3A, Orbit, etc., are enriched in the central spindle midzone and are essential for cytokinesis [13,53]. To determine the transcriptional signatures relating to spindle organization and function in our RNAseq data, we performed GSEA pathway comparisons between w1118 (WT), cpes (KO), and rescue (RES) samples. As shown in S6A Fig, we found that several pathways including spindle organization, metabolism, endocytosis, signaling, male meiotic cytokinesis, spermatid differentiation, sperm individualization, etc., were significantly altered in cpes mutants (S6A Fig). Red bars in S6A Fig indicate gene sets enriched in cpes mutants and blue bars indicate gene sets enriched in WT and RES. GSEA showed many genes involved in spindle elongation and spindle organization were positively correlated with the mutant phenotype (S6B and S6E Fig). The heatmap comparison for genes involved in spindle organization and elongation are shown (S6B–S6H Fig). Several of the genes implicated in spindle organization have also been annotated under those for spindle elongation and hence appear under both categories. However, as shown in S3 Fig, relative enrichment of earlier stages compared to later stages limits the accurate prediction of altered pathways in cpes mutants. Notably, immunostaining analysis of testis squash preparations with alpha tubulin antibody did not show consistent differences in astral spindle organization and chromosomal alignment in metaphase and anaphase spermatocytes (S7A–S7C, S7G and S7H Fig). However, spindle microtubules and central spindle (marked by feo-Cherry) were less dense and disorganized in early to late telophase spermatocytes indicating spindle behavior is affected in cpes mutants during cytokinesis (S7D–S7F and S7J–S7L Fig). To better study spindle behavior during male meiotic cytokinesis in vivo, we performed live imaging on isolated cysts. We first dissected the testis in M3 insect cell culture media and cut open the muscle sheath to release intact spermatocyte cysts into the media. Subsequently, we transferred spermatocyte cysts to poly-D-lysine-coated cover glass dishes and performed live imaging using Andor spinning disk confocal microscopy as described in the methods section. We chose mCherry tagged microtubule cross linking protein Feo (Ubi-p63E-feo-mCherry) as a marker for central spindle. Feo-mCherry was shown to accumulate at the anaphase B and telophase central spindle [54]. We also used spaghetti squash (sqh) gene encoding myosin II regulatory light chain (RLC) tagged to GFP (sqh-GFP-RLC) as a marker for the contractile ring, an actin-myosin-based structure, that assembles during late anaphase [55,56]. The actin and myosin ring positioned midway between 2 spindle poles is thought to drive the formation of the cleavage furrow during telophase. As shown in S2 Movie and Fig 4A, the actomyosin ring (sqh-GFP-RLC) quickly assembles around the central spindle during late anaphase and both simultaneously constrict through early to late telophase. At the end of late telophase feo-mCherry disassembles, however, sqh-GFP-RLC remains and becomes part of ring canal/cytoplasmic bridges between daughter cells (S2 Movie). Interestingly, in cpes mutants, the initial assembly of central spindle and actomyosin ring occurred normally (S3 Movie); however, central spindle and actomyosin ring constriction became uneven since there was barely any furrow ingression and led to substantial disengagement between the contractile ring and the central spindle during meiosis (Fig 4A, 4C and 4D). As a result, in the mutants the actomyosin ring either detached from the plasma membrane and/or the central spindle and actomyosin ring disassembled prematurely (S3 Movie). Quantification of this behavior in live cpes mutant spermatocytes suggested that more than 80% of the spermatocytes showed disengagement of the contractile ring and central spindle prior to contractile ring detachment from the plasma membrane (Fig 4B and S3 Movie). Other minor variations included contractile ring detachment from the plasma membrane prior to central spindle and contractile ring disengagement, contractile ring sliding and dumping to one end, and the contractile ring and central spindle being destabilized simultaneously at one end (Fig 4B). Under similar experimental settings in intact cysts, cytokinetic defects are negligible. Expression of UAS-CPES in germ cells was sufficient to rescue this phenotype (S4 Movie and Fig 4A, 4C and 4D). Previous studies have shown that phosphatidylinositols (PIP) play critical roles in somatic and meiotic cytokinesis [57]. Further, in mammalian (HeLa) cells undergoing mitosis, sphingomyelin-rich lipid domains in the outer leaflet of the cleavage furrow were required for accumulation of PI(4,5)P2 to the cleavage furrow which in turn was required for proper translocation of RhoA and progression of cytokinesis [10]. We wondered whether the distribution of PIP at the plasma membrane or at the cleavage furrow is altered in cpes mutants during meiosis. To investigate PIP distribution in cpes mutant membranes, we used PI(4,5)P2 reporter UAS-PLCδ-PH-EGFP (UAS regulatory sequence drives expression of EGFP fused to the PH domain of human PLCdelta 1) and PI(3,4,5)P3 reporter tGPH (an alphaTub84B promoter drives the expression of EGFP fused to the PH domain of Steppke) [58–60]. The PI(4,5)P2 reporter PLCδ-PH-EGFP was shown to uniformly localize to the entire membrane including cleavage furrow in Drosophila spermatocytes [61]. Indeed, we have seen similar uniform distribution in both control and cpes mutant spermatocyte plasma membranes indicating normal distribution of PI(4,5)P2 (S5 and S6 Movies and Fig 4E). Live imaging analysis on cpes mutant spermatocytes expressing PLCδ-PH-EGFP revealed normal cleavage furrow initiation, but progression of furrow failed due to the disconnect between central spindle and the furrow (S6 Movie and Fig 4E). Expression of wild-type CPES rescued this phenotype (S7 Movie and Fig 4E). Of note, PLCδ-PH-EGFP localization to spermatocyte plasma membrane was significantly reduced upon loss of cyst cells although this acute reduction did not prevent spermatocytes from completing cytokinesis during meiosis 1. Fluorescence intensity measurements for PLCδ-PH-EGFP localization showed no significant difference between control, and cpes mutant cysts suggesting PI(4,5)P2 localization was not affected in cpes mutants (Fig 4F). Although, rescue cysts showed reduction in PI(4,5)P2 levels, it did not correlate with the rescue phenotype. We next investigated the PI(3,4,5)P3 distribution in control meiotic spermatocytes using tGPH. Interestingly, we found that tGPH localized to plasma membranes and became significantly enriched at cleavage furrows (S8 Movie and Fig 4G). Of note, even here, we have observed that plasma membrane localization and cleavage furrow enrichment of tGPH strictly depended on the intact cyst. While it is currently unknown if PI(3,4,5)P3 localization to the spermatocyte cleavage furrows has any impact on cytokinesis, a recent study has shown that cytohesin Steppke reduces tissue tension by inhibiting the actomyosin activity at adherens junctions and actomyosin network assembly is necessary and sufficient for local Steppke accumulation in Drosophila embryos [62]. Next, we wondered if cleavage furrow enrichment of PI(3,4,5)P3 is altered in cpes mutants. However, as shown in S9 Movie and Fig 4G, PI(3,4,5)P3 localization to the cleavage furrow was not altered but again there was a disconnect between cleavage furrow and central spindle during cleavage furrow ingression. Expression of wild-type CPES rescued this phenotype (S10 Movie and Fig 4G). Further, fluorescence intensity measurements showed no significant difference between control and cpes mutant cysts, suggesting PI(3,4,5)P3 distribution is not compromised in cpes mutants (Fig 4H). Overall, these observations suggest that aberrant spindle behavior, but not the localization of PIPs to the plasma membrane or cleavage furrow, is responsible for meiotic cytokinesis defect in cpes mutants.
To determine how CPE promotes the synergy between central spindle constriction and cleavage furrow ingression during cytokinesis, we have utilized a recombinant CPE-binding protein tagged with mCherry as a reporter for visualizing CPE on spermatocyte plasma membranes. The mushroom-derived protein of the aegerolysin family pleurotolysin A2 (PlyA2) was shown to specifically bind to CPE and was demonstrated to be a versatile tool for visualizing CPE in live Drosophila tissues [63]. We have reevaluated the efficacy of recombinant PlyA2-mCherry protein in detecting endogenous CPE on live spermatocyte membranes. The wild type and cpes mutant spermatocytes were treated with 10 μg/ml of PlyA2-mCherry in M3 insect media for 1 h at room temperature, washed with fresh M3 media, and imaged on an Andor spinning disk confocal microscope. As shown in Fig 5A–5D, PlyA2-mCherry specifically bound to the plasma membranes of wild-type spermatocytes but not to the cpes mutant spermatocytes showing specificity of this protein binding to CPE. Interestingly, we found that PlyA2-mCherry was endocytosed in wild-type spermatocytes (Fig 5A). To determine the nature of the endosomes where CPE is enriched, we performed live imaging on spermatocytes expressing endogenous EYFP-MYC-tagged Rab proteins [64]. The small GTPases Rab4, Rab7, and Rab11 were shown to mark early, late, and recycling endosomes, respectively [65–67], while Rab6 was shown to be associated with the Golgi membranes [68]. The spermatocytes expressing individual EYFP-Rab proteins were treated with recombinant PlyA2-mCherry and imaged. As shown in Fig 5G, 5M and 5P, PlyA2-mCherry colocalized with Rab4, Rab7, and some of the Rab11 endosomes, respectively. Colocalization coefficient measurements further support these observations (Fig 5Q). However, PlyA2-mCherry containing structures did not colocalize with Rab 6 positive Golgi membranes (Fig 5J and 5Q). These results suggested that CPE on spermatocyte plasma membranes is actively targeted to the endocytic pathway. We next wondered whether endosomes carrying CPE migrate to cleavage furrows during meiotic cytokinesis. EYFP-Rab 7 and EYFP-Rab11 were strongly expressed in spermatocytes undergoing meiosis compared to Rab4 and therefore we followed their dynamics during meiotic cytokinesis. Strikingly, as shown in Fig 6A–6G and S11 Movie, PlyA2-mCherry containing Rab7 positive endosomes were actively targeted to cleavage furrows. Similar EYFP-Rab7 localization was seen in intact cysts (Fig 6H–6J). PlyA2-mCherry also colocalized to some of the EYFP-Rab11 recycling endosomes which in turn localized to ingressing membranes at the cleavage furrow (Fig 6K–6Q and S12 Movie). Overall, the endocytosis of CPE and targeting to the ingressing cleavage furrow via Rab7 and Rab11 marked endosomes indicates their importance in delivery of lipids to the ingressing membranes of the furrow. To further verify the functional significance of endosome mediated CPE trafficking in cytokinesis, we performed genetic experiments involving conditional expression of EYFP-Rab11DN (BDSC#23261) protein, rab35 and rab7 mutants [69]. Rab11 null mutants die early during development [22]. In that study, it was demonstrated that when spermatocytes enter meiosis 1 and as the Golgi disassembles, Rab11 associated with the ER compartment. Rab11 also localized to vesicles at the cell poles during anaphase and early telophase and at the cell equator during mid- and late telophase. Larval gonads of escaper flies carrying Rab11 semilethal transheterozygote alleles showed abnormal constriction of the contractile rings and a failure of cytokinesis in 10% to 30% of the flies. We chose to conditionally express dominant negative EYFP-Rab11S25N ubiquitously using Gal80ts and tub-Gal4 to study cytokinetic defects in spermatocytes. The expression of EYFP-Rab11S25N (Rab11 DN) in late third instar larvae was induced by incubation at 30°C for 4 days. The late pupal testes were dissected, and cytological analysis was performed to measure cytokinetic defects. Consistent with previously published results [22,24], we found significant increase in cytokinetic defects in Rab11DN expressing gonads (S8B and S8F Fig), confirming important roles for Rab11 mediated membrane trafficking during cytokinesis. To further investigate CPE positive endosome behavior during cytokinesis, we treated Rab11 DN expressing spermatocytes with PlyA2-mCherry and performed live cell imaging. Interestingly, compared to control spermatocytes (S9A–S9C and S9M Fig and S13 Movie), Rab11 DN expressing spermatocytes showed significant reduction in CPE positive endosome localization to cleavage furrow (S9D–S9F and S9M Fig and S14 Movie). Further, cleavage furrow regressed following ingression in Rab11 DN expressing spermatocytes (S14 Movie). These results suggest that normal Rab11 function is required for furrow-specific localization of CPE containing endosomes. Cleavage furrow regression after complete ingression in Rab11 DN expressing spermatocytes indicates endosome mediated CPE addition may play an important role in late steps of cytokinesis perhaps by providing stability to the ingressed membranes. Rab35 is another recycling endosomal marker that was shown to be essential for cytokinesis in mitotic cells [70]. A recent study showed that Rab35 mutant flies are semilethal and mutant male escapers were observed [71]. We performed cytological and immunostaining analysis on Rab35 mutant testes and found significant cytokinetic defects, spermatid polarity, and individualization defects (S8C and S10A–S10D Figs). Earlier studies have shown that Rab35 localizes to the plasma membrane and endosomal compartments in mitotic cells [70]. However, EYFP-Rab35 did not show clear plasma membrane or endosomal localization in immunostained spermatocytes, instead it was predominantly localized to cytosol (S10E Fig). However, we did see its enrichment on endosomal compartment in cyst cells (S10E and S10F Fig). Interestingly, in the live spermatocytes EYFP-Rab35 shows mitochondria-like localization pattern in spermatocytes undergoing cytokinesis and nebenkern in round spermatids (S10G and S10H Fig, respectively). Nevertheless, we have investigated CPE positive endosome behavior in Rab35 mutant spermatocytes and found no significant difference in endocytosis and localization of CPE containing endosomes to the cleavage furrow (S9G–S9I and S9M Fig and S15 Movie). These results suggest that Rab35 may not be involved in cleavage furrow-specific localization of CPE positive endosomes. However, we cannot rule out the possibility that Rab35 could act after CPE positive endosome translocation to the cleavage furrow, i.e., lipid recycling at the furrow. Another possibility could be that Rab35 is required for delivery of other lipids and or protein cargo such as phosphatidylinositol 5 phosphatase (OCRL), oxidoreductase (MICAL1), etc., [23], independent of CPE, to facilitate late steps of cytokinesis in spermatocytes. We next investigated the role of Rab7 in CPE positive endosome localization to the cleavage furrow and cytokinesis. Rab7-null mutant flies generated by imprecise excision of P-element resulted in a 1,025 bp deletion that removed most of the protein coding exon and the 5′ untranslated region (UTR) [69]. The mutants displayed late pupal lethality and western blotting with Rab7 antibody confirmed the absence of Rab7 protein in the mutant pupae (S8D Fig). To investigate meiotic cytokinetic defects in Rab7 mutants, we performed testis squash preparations followed by phase contrast microscopy. Interestingly, we found significant increase (15%) in meiotic cytokinesis defects in Rab7 mutants (S8E and S8F Fig) compared to wild-type controls where cytokinetic defects are virtually zero [22,24] (S8A Fig), suggesting a significant role for Rab7 in male meiotic cytokinesis. Previous studies have shown that Rab7 protein is required downstream of late endosomes or multivesicular bodies (MVBs) for transfer of cargo to lysosomes [72]; therefore, formation and migration of late endosomes to the cleavage furrow might not be affected in Rab7 mutants. Consistent with this possibility, we observed that PlyA2-mCherry continued to be endocytosed and targeted to cleavage furrow in Rab7 mutants (S9J–S9L and S9M Fig and S16 Movie). However, presence of significant cytokinetic defects in Rab7 mutants indicate that normal Rab7 function is required for proper dynamics of CPE positive endosomes via as yet unknown mechanisms during cytokinesis. Taken together, these genetic analyses indicate that Rab7, Rab11, and Rab35 functions are required for normal male meiosis cytokinesis; however, Rab7 and Rab11 functions are more directly linked to CPE positive endosome behavior during cytokinesis.
We performed correlative light and focused ion beam scanning electron microscopy (CLEM/FIB-SEM) to gain structural insight into the endosomes that are enriched at the cleavage furrow/midbody during cytokinesis. Spermatocytes expressing EYFP-Rab7 were labeled for endocytosed CPE with PlyA2-mCherry and allowed to progress to meiosis 1. Cysts showing PlyA2-mCherry and EYFP-Rab7 colocalization at the cytokinetic furrow were fixed, imaged by light microscopy, then stained, resin embedded, and prepared for FIB-SEM. Fig 7A–7C shows CLEM-FIB-SEM of a cyst undergoing cytokinesis showing colocalization of Rab7 with endocytosed CPE at the furrow. 3D correlation of the LM and FIB-SEM image volumes allowed us to localize the Rab7/PlyA2 double positive signals to endosomes that appeared as spherical-shaped structures ranging from 300 to 800 nm in diameter. The lumen of these endosomes was filled with intraluminal material which at FIB-SEM resolutions could be discerned, but not definitely resolved, as vesicles packed into the lumenal volume. Although we were able to capture endosomes in the cytokinetic furrow, it was technically difficult to visualize and arrest them in physical association with the ingressing furrow membranes using these flies (S17 Movie). Therefore, we decided to examine cytokinesis in cysts where the contractile ring is in proximity to the ingressing membrane, and the endosomes could be visualized during live imaging. We examined spermatocytes expressing tubulin-Gal4>mRFP-Anillin that labels the contractile ring and endogenously expressing EYFP-Rab7 that marks late endosomes to capture membrane proximal endosomes (S18 Movie). Anillin (also known as scraps) encodes for a conserved pleckstrin homology domain containing protein that was shown to bind actin, microtubules, and nonmuscle myosin II and required for stabilization of contractile ring [53]. Dividing cysts were imaged, fixed, and cysts with Rab7-Anilin colocalization at the cytokinetic furrow were prepared for FIB-SEM imaging (Fig 7D and 7E). Using CLEM/FIB-SEM, we were able to capture multiple Rab7 positive endosomes docked at the ingressing furrow (Fig 7E–7M). S19 Movie shows the 3D reconstruction of the vesicles captured at the furrow seen in Fig 7K. We observed multiple instances of this docking of endosomes in dividing spermatocytes (Fig 7N). S20 Movie is a sub-volume reconstruction of the dividing cells seen in Fig 7N. While we observed docking of the endosomes to the ingressing membrane in the samples we studied, we were unable to visualize the fusion of vesicles to the ingressing membrane or to the proteinaceous structure that was anchoring the endosomes (Fig 7 and S20 Movie). To visualize the endosomes at the furrow at higher resolution, we carried out CLEM-SEM-TEM of the dividing meiotic spermatocytes and examined vesicles that appeared to be in close proximity to the cleavage furrow (Fig 8). Drosophila spermatocyte cysts expressing tubulin-Gal4>mRFP-Anillin and EYFP-Rab7 undergoing meiotic cytokinesis were identified, fixed, and resin embedded (Fig 8A). Serial sectioning of the correlated cysts followed by TEM imaging revealed the structures as MVB-like organelles, filled with intraluminal vesicles varying in size between 20 to 50 nm in diameter (Fig 8B–8D), consistent with previously described multivesicular endosomes (MVEs) or MVBs [73]. Again, rather than seeing evidence of fusion, we found that the outer membrane of several of these endosomes was discontinuous (Fig 8C). Interestingly, the MVBs that showed significant loss of outer membrane integrity appeared to have released intraluminal vesicles in the vicinity of the ingressing membranes (Fig 8D, top left), possibly providing a proximal source of lipid laden vesicles for membrane biogenesis (Fig 8E).
Plasma membrane expansion and ingression of the cytokinetic furrow still remain one of the least understood horizons in the field of cell division [74]. We are only beginning to appreciate the involvement of lipids in structural integrity, membrane expansion, and transmission of signals during cytokinesis. PI(4,5)P2 is the most studied lipid in cytokinesis and has been shown to localize to the cleavage furrow during ingression. In addition to PI(4,5)P2, cholesterol, very long chain fatty acids, and sphingolipids have also been associated with cytokinesis [10,12,75]. In mitotic HeLa cells, PI(4,5)P2 accumulation at the inner leaflet and subsequent recruitment of RhoGTPase (RhoA) was shown to be coordinated with sphingomyelin rich domains on the outer leaflet [10]. However, it is unknown if a similar mechanism exists in germ cells that have different characteristics and different lipid composition. While mitotic cells were shown to accumulate classical sphingolipids with long to very long acyl chains at intercellular bridges [12], male germ cells accumulated complex sphingolipids with very long/ultra-long chain polyunsaturated fatty acids (VLC-PUFAs) [17]. These differences in sphingolipid composition with distinct biophysical properties between mitotic cells and male meiotic cells point toward distinct underlying mechanisms. In this study, we show the sphingolipid composition of the major species in Drosophila testis for the first time and demonstrate significant enrichment of unique CPE species containing SPH_MUFA and SPD_SFA. Unlike mammalian testis, the Drosophila testis lacks significant amounts of VLC-PUFA containing sphingolipids. However, due to conserved unsaturation in acyl chains, it is likely that SPH_MUFA and SPD_SFA containing CPE could substitute for VLC-PUFA functions in Drosophila male germ cells. Glycosphingolipids with VLC/ULC PUFAs have been shown to be required for mammalian male meiotic cytokinesis but their actual role has not been delineated [17,76,77]. It is interesting to note that CPE mimics certain physical properties of galactosylceramide (GalCer), a major sphingolipid in myelin sheath [78]. Previous studies have shown that CPE has an essential role in axonal ensheathment and cortex glial plasma membrane expansion in Drosophila [27,79]. It was hypothesized that the axonal ensheathment in mammals and Drosophila is based on similar physical process with different lipids [78]. We have previously shown that sphingomyelin, a structural analog of CPE, could rescue cortex glial membrane defects in cpes mutants, suggesting the head group is not as important as the tail in glial membranes. However, here we show that sphingomyelin could not rescue spermatogenesis defects in cpes mutants alluding to the importance of the ethanolamine head group in spermatocytes. Taken together, we could suggest that Drosophila CPE would have evolved to have both the properties of mammalian glycosphingolipids and sphingomyelin to promote spermatogenesis and glial ensheathment of neurons. Phosphoinositides play critical role in cytokinesis. In particular, PI(4,5)P2 was shown to be enriched at the furrows and directly binds to several proteins such as anillin, septins, and MgcRacGAP to mediate furrow stability [23,80]. Unlike mitotic cells, PI(4,5)P2 in male meiotic cells does not show selective accumulation at cleavage furrows. Instead, it is uniformly distributed throughout the plasma membrane including at furrows ([61] and Fig 4C and S5, S6, and S7 Movies). Interestingly, PI(4,5)P2 hydrolysis and calcium release were shown to be required for cytokinesis in Drosophila spermatocytes [61]. These observations suggests that in meiotic cells, PI(4,5)P2, has a broader role at the plasma membrane and at furrows to promote cytokinesis. Intriguingly, we show that the PI(3,4,5)P3 binding PH domain of Steppke (tGPH) localizes to cleavage furrows indicating a potential role for PI(3,4,5)P3 during male meiotic cytokinesis. However, the accumulation of PI(3,4,5)P3 to the cleavage furrows occurs only in the intact cysts, i.e., 16 interconnected spermatocytes wrapped up by 2 somatic cyst cells suggesting the need for certain mechanical force. The role of PI(3,4,5)P3 accumulation in the male meiotic cleavage furrows is an open question and warrants future investigation. Notably, recently it was shown that cytohesin Steppke reduces tissue tension by inhibiting the actomyosin activity at adherens junctions in embryos [62]. Although broad accumulation of PI(4,5)P2 to the plasma membranes and PI(3,4,5)P3 accumulation at the cleavage furrows were not altered in cpes mutants, their specific localization to membrane microdomains and their inability to signal robustly cannot be ruled out. Sphingadienes with Δ4,6 conjugated double bonds were previously identified in Drosophila, Manduca sexta, and B. mori [81–83], although their enrichment in the testis was not known until now. However, normal sphingolipid synthesis and their degradation are shown to be required for spermatogenesis [84,85]. The sphingadiene sphingolipids were shown to have inhibitory effects on AKT-dependent signaling [86] and down-regulate Wnt signaling via a PP2A/Akt/GSK3β pathway [87]. Thus, accumulation of sphingadiene with saturated fatty acid containing sphingolipids in the testis could have a role in regulation of PI(4,5)P2/PI(3,4,5)P3 mediated signaling in vivo. Apart from CPE_SPD_SFA, the Drosophila testis is also enriched in CPE_SPH_MUFA suggesting they could mediate distinct functions. Lipids with unsaturated fatty acids mediate a number of biological functions [88]. It is widely known that phospholipids with unsaturated fatty acids promote membrane fluidity and elasticity [89,90]. Sphingolipids with unsaturated fatty acids could thus provide unique biophysical properties necessary for the membrane curvature requirements during meiotic cytokinesis. DES-1 codes for dihydroceramide desaturase enzyme in the de novo biosynthetic pathway in Drosophila. des-1 mutants (also called infertile crescent, ifc) were described before the gene product was identified as a homolog of dihydroceramide desaturase. The primary spermatocytes of the des-1 mutants undergo degeneration without initiating chromosome condensation at the beginning of meiosis [91]. A P-element insertion allele showed that DES-1 colocalized with mitochondria and was intimately associated with the central spindle of dividing meiotic spermatocytes. Its deficiency leads to failure of central spindle assembly in these dividing cells leading to several phenotypes including cytokinetic defects. It was proposed that DES-1 could be part of an anchoring mechanism that linked membrane bound cellular compartments to components of the cytoskeleton [84]. Considering that DES-1 is a dihydroceramide desaturase homolog, it would be worth revisiting the mutant phenotype to evaluate if it too contributes to membrane assembly at the cytokinetic furrow due to lack of CPEs. In correlative live imaging and electron microscopy studies, we find that MVBs target CPE laden vesicles to the cleavage furrow. MVBs are by definition spherical organelles that are typically 250 to 1,000 nm in diameter with a single outer membrane that enclose a variable number of smaller spherical vesicles within. Originally, they were believed to be involved in neurosecretion because of their close association with the Golgi stacks [92]. Further work established a primary role in endocytosis and subsequent degradation of proteins [93–95]. Other works have highlighted the important role of MVBs in recycling function [96]. The last decade or so has seen the emergence of a role for MVBs in autophagy and secretion via the exosomes [97,98]. Our work has surprisingly unraveled a possible new function for MVBs in transporting the endocytosed vesicles rich in lipids to the vicinity of expanding membranes. Interestingly, CPE is not required for localization of MVBs to the cleavage furrow (S21 Movie), instead, our data suggests that CPE loaded MVBs are required in the vicinity of expanding membranes to mediate cytokinesis. Consistent with this possibility, our genetic analysis showed that ablation of Rab11 function prevents cleavage furrow-specific localization of CPE positive MVBs which in turn could partly explain increased cytokinetic defects in Rab11 mutants or in Rab11 DN expressing genetic background. Rab11 and Rab35 are small GTPases whose roles in membrane recycling during late steps of cytokinesis have been well established [22–24,70,99]. In mammalian system, it was shown that FIP3 (Rab11 family interacting proteins), an effector of Rab11 binds simultaneously to Rab11 and Arf6 (small GTPase) through distinct sites [100]. Rab11-FIP3 endosomes move in and out of intercellular bridge with the help of microtubule-based motors kinesins (KIF5B) and dynein that are regulated by Arf6 and KIF5B-dynein scaffolding protein JIP4 [101]. In Drosophila, Nuclear fallout, a FIP3 homologue was shown to bind Rab11 and regulate actin cytoskeleton remodeling during early furrow formation in embryos [99]. Membrane trafficking transport protein particle (TRAPP) II complex component brunelleschi (bru) was shown to genetically interact with Rab11 and is required for cleavage furrow localization of Rab11 in Drosophila spermatocytes [102]. Phosphatidylinositol 4 phosphate (PI (4)P) effector protein Golgi phosphoprotein 3 (GOLPH3) was shown to be essential for contractile ring formation and Rab11 localization to cleavage furrow in Drosophila spermatocytes [26]. Further, recruitment of Rab11 to the cleavage site also depends on wild-type functions of exocyst complex subunits Exo84 and sec8 [21]. Taken together, these studies suggest that Rab11 localization to cleavage furrow is regulated by multiple proteins including microtubule motors, transport proteins, Golgi components, and exocyst components. Therefore, it is likely that Rab11 complexed with yet other unknown proteins could mediate trafficking of CPE positive MVBs to the cleavage furrow, it could mediate docking via interaction with exocyst components and mediate fusion via SNAREs on target membranes [23]. Although Rab35 mutants show cytokinetic defects, we were unable to localize Rab35 to the endosomal compartment in fixed spermatocytes. We show Rab35 is not required for localization of CPE positive MVB to the cleavage furrow; however, we cannot rule out if Rab35 plays a role after CPE localization to furrow membranes. How Rab35 mediates cytokinesis in spermatocytes remains an open question. Similarly, absence of Rab7 does not prevent endocytosis and targeting of CPE positive MVBs to cleavage furrow. However, presence of cytokinetic defects in Rab7 mutants indicates certain dynamics of CPE positive MVBs could be compromised. Future studies should throw light on the role of this CPE positive MVB pathway in membrane and protein accumulation in newly synthesized membranes as in the case of meiotic cytokinesis in the testis. The human genome encodes more than 60 Rab proteins and several of them including Rab1, Rab8, Rab10, Rab14, Rab21, Rab24, and Rab35 were shown to localize to intercellular bridges [23]. Currently, it is unknown if these endosomes are also involved in delivery of specific plasma membrane-derived lipids to the cleavage furrows. Our study shows that there is an increased localization of CPE to the endosomal compartments in spermatocytes. The CPE containing MVBs are selectively docked on the ingressing membranes at the cytokinetic furrow and release intraluminal vesicles, suggesting delivery of CPE rich membranes to the growing furrows. Future investigations focusing on these CPE-enriched endosomes and their dynamics during male meiotic cytokinesis, spermatid polarity, and individualization will provide novel insights into membrane expansion and or their role as a signaling center to mediate spermatogenesis.
tubulin-Gal4 (BDSC#5138), UAS-PLCδ-PH-EGFP (BDSC#39693), tGPH (BDSC#8163), Sqh-GFP.RLC (BDSC#57145), Sqh-mCherry.M (BDSC#59024), p(Ubi-p63E-Feo-mCherry)3 (BDSC#59277), bam-Gal4 [51], nos-Gal4 (BDSC#4937), chif-Gal4 (BDSC#13134), C587-Gal4 (BDSC#67747), EYFP-Rab4 (BDSC#62542), EYFP-Rab6 (BDSC#62544), EYFP-Rab7 (BDSC#62545), EYFP-Rab11(BDSC#62549), UAS-EGFP (BDSC#5430), tub-Gal80ts (BDSC#7108), UASP-Rab11.S25N (BDSC#23261), UAS-mRFP-Anillin (BDSC#52220), rab7 mutant [69], Rab35 mutant [71], genomic CPES_V5tag [27], cpes mutants [27], UAS-hSMS1 [27], dcert1[43], UAS CDase [44], UAS-CPES active site mutants, UAS-Aedes CPES, UAS-Bombyx CPES (this study).
All Drosophila stocks were raised on standard fly food and maintained 25°C unless otherwise mentioned. Due to increased lethality, cpes mutants were raised at 18 to 21°C. Certain genetic backgrounds increased pupal death in cpes mutants such as overexpression of UAS CDase, UAS-PLCδ-PH-EGFP, cpes; dcert1 double mutants. In such cases, we have separated third instar larvae of cpes mutants and allowed them to develop into pupae. The testes were dissected before the death of pupae and analyzed.
The coding sequence for A. aegypti CPES (XM_021851518.1) and B. mori CPES (XM_004923146.3) were codon optimized and synthesized by GenScript and subcloned into pUAST vector. The clones were sent to BestGene for embryo injection service. The transgenic flies were balanced and crossed with Gal4 drivers to conduct rescue experiments.
Two conserved aspartates in CPES active site were mutated to alanine using PCR-based site directed mutagenesis method as described by [103]. PCR was performed using pBluescript SK+ CPES_V5 clone as template with appropriate sense and antisense primers (S1 Table) and Phusion polymerase (NEB). The PCR product was digested with DpnI to remove templates followed by transformation into DH5α competent cells. Plasmids were isolated from colonies grown in LB media and screened by restriction digestion with appropriate restriction enzymes (S1 Table) and sequencing. The pBluescript SK+ CPES DD-AA clone was used as template to PCR amplify the insert using appropriate primers (S1 Table), restriction digested and cloned into pUAST vector. The clones were confirmed with restriction digestion followed by DNA sequencing.
Mushroom-derived aegerolysin PlyA2 was cloned, expressed, and purified as described by [104]. Briefly, the coding sequence of PlyA2 (accession number AB777517) fused to mCherry at the C-terminus was synthesized by GenScript. The linker amino acid sequence between PlyA2 and mCherry was VDGTAGPGSIAT. This clone was used as template to PCR amplify using appropriate forward and reverse primers (S1 Table) and cloned into p24a vector at appropriate restriction sites (S1 Table). The clones were transformed into Escherichia coli strain BL-21 (DE3) and single colony was inoculated in to 5 ml of LB broth containing 50 μg/ml kanamycin and grown overnight in orbital shaker (200 rpm) at 37°C, and 2 ml of overnight culture was inoculated into 250 ml of fresh LB broth containing kanamycin and grown at 37°C until the optical density reached to 0.6. Subsequently, the culture was incubated in cold (4°C) for 2 h, followed by induction with 0.3 mM isopropyl-B-D-thiogalactopyranoside, and grown at 25°C in orbital shaker (200 rpm) overnight. The cells were harvested by centrifugation at 5,000g for 10 min at 4°C, and the pellet was resuspended in binding buffer (20 mM sodium phosphate buffer (pH 7.4), 500 mM NaCl, 20 mM imidazole) containing EDTA free protease inhibitor cocktail (Sigma, P8340). The cell suspension (50 ml) was sonicated at 4°C (Cole-Parmer ultrasonic processor model CP130,) with microprobe at an amplitude of 30 and on and off cycles of 10 s each for about 30 min to 1 h. The lysate was centrifuged at 10,000g for 10 min to remove insoluble proteins and debris. To the supernatant, 1 ml of 50% Ni-NTA agarose (Thermo Scientific) was added and incubated on end-to-end rotor for 3 h and the beads were collected on a column and washed with 30 ml of binding buffer and eluted with binding buffer containing 200 mM imidazole. The fractions were dialyzed in 20 mM sodium phosphate buffer 3 times (1 L each), and the final protein was concentrated with Amicon centriprep filter devices for volumes up to 15 ml. The protein concentration was determined using Bradford assay. The proteins were resuspended in 20% glycerol, aliquoted (100 μl), and stored at −80°C for future use.
Drosophila testis squash preparations for phase contrast microscopy and immunostaining were performed as described by [29]. Briefly, young male (0 to 2 days old) testes were dissected (5 pairs) in phosphate-buffered saline (PBS, 130 mM NaCl, 7 mM Na2HPO4, 3 mM H2PO4). The testes were torn open on a slide at appropriate location with a pair of black anodized steel needles (tip diameter 0.0175 mm) and a cover glass was gently placed without air bubbles. The slides were directly observed under phase contrast microscopy or snap frozen in liquid nitrogen for immunostaining. After freezing, the cover glass was removed from the slide with razor blade and immersed in cold 99.5% ethanol and incubated in −20°C for 10 min. The slides were then fixed with 4% paraformaldehyde (PFA) in PBS containing 0.1% Triton-X-100 (PBST) for 15 min. Subsequently, the slides were washed with PBS and the area of squashed tissue was circled with a hydrophobic barrier pen, permeabilized with PBST (30 min), and blocked with 5% normal goat serum in PBST (1 h at RT). Squashed tissues were incubated with primary (1 μg in 100 μl) and secondary antibody (1:100 dilution) (8 to 12 h each at 4°C in a moist chamber). Slides were washed with PBST (3× 10 min each) after each antibody treatment, finally incubated with DAPI solution (1:2,000 dilution from 5 mg/ml stock, Molecular Probes) and mounted with Vectashield H1000 mounting media.
Five pairs of testes were dissected for each experiment, live testis squashes were prepared, and round spermatids were observed using 40× Ph2 Plan-Neofluor objectives on Axioplan 2 microscope as described above. All round spermatid cyst in the sample were imaged and their cell number was counted manually (250 to 500) for each genotype. Percentage of round spermatids with 2, 3, or 4 nuclei were calculated by dividing the total spermatid number including spermatids with 1, 2, 3, or 4 nuclei. More than 5 independent experiments were carried out for each genotype.
Male fertility assay was performed by setting up individual crosses with 1 male and 3 wild-type females. Each replicate involved 30 males and 3 independent replicates (total of 90 males) were performed for each experiment.
Drosophila tissues were dissected and immunostained as described previously [27]. Briefly, dissected testes were fixed with 4% PFA in 0.3% PBST for 1 h at RT, washed (3× 10 min each), permeabilized in 0.3% PBST (1 h), blocked with 5% NGS (1 h), and incubated with primary antibody (1:100 dilution or 1 μg in 100 μl of 5% NGS in PBST) overnight (8 to 12 h). Testes were washed with 0.3% PBST (3× 10 min each) and incubated with secondary antibody (1:100 dilution in 5% NGS in PBST) overnight (8 to 12 h). Testes were washed with PBST (3× 10 min each), stained with DAPI (1:2,000 dilution of 5 mg/ml solution in PBST) for 15 min, and mounted with Vectashield H1000 mounting medium. The slides were imaged on ZEISS confocal laser scanning microscope LSM 780 or LSM880.
About 15 to 20 pairs of young (0 to 2 days old) Drosophila testes were dissected in 600 μl of insect cell culture media (M3 media supplemented with heat inactivated FBS, Pen/Strep) in a glass well plate. Testes were transferred to a fresh well with 400 μl of media and torn open with a pair of black anodized steel needles (tip diameter 0.01 mm) to release the cysts into media. This was repeated until all the testes were torn open. They were gently agitated so that all the cysts were released into the media followed by removal of empty testis or debris from the media. The cysts were gently washed with fresh 400 μl media (2×), then transferred via pipetting into the middle of 35-mm cover glass bottom dish (Poly D-Lysine coated) and fresh media (max. 200 μl) was gently added to the cleft formed between cover glass and the dish. The cysts tend to move while handling but remain settled on the cover glass and ideally remain in position while imaging. The intact cysts and cysts that have lost their cyst cells could be distinguished in bright field view. The cysts that are beginning to undergo meiosis could be identified in bright field view by looking at cell morphology and differences in nucleus and spindle appearance. Cells beginning to undergo meiosis could also be identified by Feo-mCherry that is localized to nucleus in interphase but translocate to cytosol during prophase to anaphase. Prophase to anaphase cysts were identified using 25× water objective and subsequently imaged using 63× water objective on a Leica Andor spinning disk confocal microscope. The time lapse imaging was done at 2 min intervals with the z stacks (about 80 slices, 0.5 μm per slice) at each time point for 60 to 90 min for completion of meiotic I cytokinesis. Laser power and exposure times were preferably kept low to prevent bleaching and aberrant effects on cytokinesis due to generation of free radicals.
About 10 to 15 pairs of testes were dissected from newly eclosed male flies in M3 or S2 insect cell culture media. Testes were transferred to fresh M3 media (400 μl) in a glass spot plate (PYREX 722085) and torn open with a pair of black anodized steel needles and gently agitated to release the cysts into media. Subsequently, testis debris were removed from the well. The cysts were gently washed with fresh 400 μl media (2×) and incubated with PlyA2-mCherry protein (10 μg/ml) in 400 μl of M3 media for 1 h, on a rocker. The cysts were washed with fresh media without PlyA2-mCherry (1× with 400 μl media). About 5 to 10 cysts were transferred to cover glass bottom 96-well plate (Cellvis, Cat # P96-0-N) containing 100 μl of M3 media. The cysts in each well were observed under 25× water objective on an Andor spinning disk microscope using bright field and/or fluorescence. Cells undergoing division were identified by cell morphology changes such as cell rounding, nuclear membrane loss, microtubule appearance, cell elongation, and ingressing cleavage furrows. When spermatocytes at the appropriate stage of interest were identified, 100 μl of 8% PFA in M3 media was added to the well (4% PFA final concentration) and gently mixed with pipetting. The 96-well plate cover was removed after adding PFA to avoid its effect on other wells. Location of the well could be identified with the help of a torch light and/or illuminating the well with bright field or fluorescent light. The process was repeated until at least 5 to 10 cysts were identified and fixed. The sample in fixative could be stored up to 2 days at 4°C in the 96-well plate. The cysts in the 96-well plates were gently agitated with pipetting and transferred to a glass spot plate (the pipet tip was cut and conditioned with the media to avoid sticking of cysts to tip walls). At this stage, cysts were pooled from different 96 plate wells into a single glass well plate. The cysts were centered by gently flushing with pipetting. They were then washed with 1XPBS (3× 400 μl). Following washing, the cysts were pipetted into the center of a gridded covered glass bottom plate (MatTek, Part No. P35G-1.5-14-C-Grid). After the cysts settled on the coverslip, most of the PBS was removed by gentle pipetting. Subsequently, 4% low melting agarose (Invitrogen, REF 16520–100) (in 1xPBS) that was maintained at 80°C is cooled for 1 to 2 min and gently poured from the top, care must be taken to minimize movement of cysts. After the agarose had solidified, the cysts that were settled and embedded in the agarose were imaged on the Andor spinning disk confocal microscope using 25× and 63× water objectives. At this time, the cells were imaged at high magnification by transmitted light to record the location of regions of interest (ROI) with respect to the alphanumeric grid of the glass-bottom dish. Images were also taken at lower magnification to record the locations of other cells in the dish, which would later serve as landmarks in the correlative light-electron microscopy (CLEM) pipeline; images of the ROI at various points in this pipeline are shown in S11 Fig. The disc of solidified agarose containing the cysts was carefully removed from the glass-bottom dish. Not only are the cells embedded in situ typically within 10 microns of the bottom agarose surface, but also the alphanumeric gridded pattern is transferred to the agarose pad in relief, and both are visible in a dissection microscope. The agarose pad was rinsed with 0.1 M sodium cacodylate buffer (11652, Electron Microscopy Sciences) several times. It was then incubated in a solution containing 2% osmium tetroxide (19150, Electron Microscopy Sciences) and 1.5% potassium ferricyanide (20150, Electron Microscopy Sciences) in 0.1 M sodium cacodylate buffer for 1 h at room temperature. Afterwards, it was thoroughly washed with water for a minimum of 30 min. The sample was then incubated in 1% aqueous uranyl acetate (22400, Electron Microscopy Sciences) for 30 min followed by extensive water washes. This was followed by standard EM processing steps—the sample was dehydrated using a series of increasing ethanol concentrations ending in 100% ethanol and then washed with 100% propylene oxide. The sample was infiltrated with Epon (Embed 812) resin using increasing concentrations of hard resin formulation in propylene oxide, and finally embedment in a polypropylene dish, with curing in an oven at 60°C for 2 days. Once the resin was fully cured, it was separated from the dish and examined using a dissecting microscope. The heavy metal-stained cysts were dark and easily identified; the overall pattern of cysts was unchanged from previous steps (S11 Fig). ROIs for CLEM were identified and approximately 1 mm2 areas around each cyst were cut out from the larger disc of resin using a saw and razor blades. These were then re-embedded onto blank blocks for ultramicrotomy. The blocks were sectioned using an ultramicrotome (Powertome, RMC) until cysts were exposed at the resin surface as revealed by Toluidine Blue stain, taking care that the actual cleavage furrow itself was just below the surface and not sectioned. This positions the feature within approximately 10 microns of the top surface and therefore amenable to FIB-SEM imaging.
FIB-SEM imaging was done largely as previously described [105]. Briefly, the specimen was cut to approximately 2 mm height and mounted on an SEM stub using silver. The specimen was introduced into a Zeiss CrossBeam 550 (Zeiss), ROI located by SEM imaging, and protected by a patterned platinum and carbon pad. A trench was FIB milled until the profiles of both dividing cells were revealed but stopped before the cleavage furrow was milled away. Images were acquired at 3 nm or 5 nm pixel sampling in XY and step size of 9 or 15 nm in Z, respectively, in an automated FIB-mill-SEM-image cycle with SEM operated at 1.5 kV, 1.2 nA; FIB milling at 30 kV, 1.5 nA, and back-scatter detector grid voltage at 900 V. The image stack was registered, contrast inverted, and binned by 3 in the imaging plane to produce an isotropic 9 nm3 or 15 nm3 image volume reconstruction. For TEM imaging, the cysts were exposed using the same approach, but here, 60-nm serial sections were cut and collected onto TEM grids. STEM imaging was executed at a Zeiss Gemini II SEM 450 at 30 kV landing energy, and the TEM imaging was done on a Hitachi 1050 operated at 80 kV. In both cases, the grids were not post stained; however, approximately 4-nm carbon coat was applied using a sputter coater (Leica) before imaging.
There were 2 stages of correlation in these experiments. The correlation for relocation, i.e., imaging an ROI by LM and then locating the same ROI for EM, was performed by careful sample preparation and appropriate imaging at various stages (S11 Fig). Correlation for registration, i.e., aligning 2 image volumes to identify cellular features of interest, was done after LM and EM images were acquired. 3D correlation was done using eC-CLEM [106]. The confocal stack and FIB-SEM image stacks were imported, and multiple fiducials were placed at distributed locations on the plasma membrane of both dividing cells in the PlyA2-mCherry + eYFP-Rab7 expressing cysts. The plasma membrane was visualized easily in the FIB-SEM images, and more approximately in the lower resolution LM data, using the PlyA2-mCherry signal that localizes strongly at the cell membrane. The green channel (Rab7) was not used for registration. The skew transformed LM fluorescence was overlaid on the original FIB-SEM data and examined with the green channel added back, upon which the identity of the PlyA2 + Rab7 double positive features in the furrow were revealed (S17 Movie). In a second experiment using mRFP-Anillin: eYFP-Rab7 cysts (Fig 7E), the correlation in ecCLEM was performed using fiducial points on the furrow, as located by the “neck” in the FIB-SEM image volume (Fig 7F), and the mRFP-Anillin staining in the LM images (Fig 7G). As before, the Rab7 signal was not used for correlation. In both cases, the registration was limited by the relatively lower resolution of the LM image stack but was sufficient to consistently correlate large vesicles in the FIB-SEM data with Rab7-positive signals in the LM data. For TEM imaging, sequential sections were imaged and inspected manually until the features captured in the LM started to appear in the EM sections. The images were overlaid but not computationally correlated, as the identity of the features was readily apparent in the 2D EM image. The FIB-SEM image volumes were visualized, and volume rendered using Arivis (Arivis), with features of interest such as furrow, docked and undocked vesicles segmented either in 3DSlicer (www.slicer.org) or Arivis.
Sphingolipid estimation using supercritical fluid chromatography coupled to mass spectrometry (SFC/MS/MS) was performed as described previously [27]. Lipids were extracted from heads, ovary, and testis samples as described [107,108]. About 400 fly heads, about 250 pairs of ovaries and about 250 pairs of testes were used for each biological replicate. Three independent replicates were taken for each sample. For Figs 1 and 2, only testes samples were used, whereas for S5 Fig, whole male organ (testis, accessory glands, collecting ducts, and ejaculation bulb) were used for lipid extraction. Internal standards (ISTD) added to the tissues before extraction included 500 pmol (20 μl) of Cer/Sph Mixture I (Avanti Polar Lipids LM-6002) and 1 nmol of C12 Sphingosyl PE (C17:1/C12:0) (Avanti Polar Lipids). Lipids from all samples were normalized to carbon content (100 μg/ml) and 100 μg/ml sample was diluted 10 times before injection for SFC. We have used large-fragment MRM method for quantitation of amount per 100 μg of carbon.
Three independent biological replicates were performed for each sample and about 200 pairs of w1118 (WT 1–3), cpes mutant (KO 1–3), and bam-Gal4>UAS-CPES rescued (RES 1–3) fly testes were dissected for each replicate. The testes were dissected in S2 cell culture media, washed with PBS, and RNA was extracted. Total RNA was extracted using Trizol method followed by DNAase I treatment and purification using RNA Clean and Concentrator-5 kit (Zymoresearch). A total of 2 μg of RNA was submitted to Novogene for total RNA seq. The RNA seq data was further analyzed for differential gene expression and pathway analysis using GSEA. The gene sets specific for Drosophila were downloaded from http://www.bioinformatics.org/go2msig/ and http://ge-lab.org/gskb/. The gene sets specific for cell types in Drosophila testis are described in Witt and colleagues, 2019 [45].
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PMC9550241 | 36098705 | Weimin Luo,Yuefeng Liu,Hangying Qu,Xiangyu Luo,Liqiang Xu,Jia Zhang,Jiansheng Wang | CircKIF4A promotes non-small cell lung cancer proliferation and metastasis through MiR-1238/CLDN14 axis | 12-09-2022 | circKIF4A,non-small cell lung cancer,miR-1238,CLDN14,metastasis | As the leading cause of cancer-related death worldwide, non-small-cell lung cancer (NSCLC) is still in need of improved therapeutic strategies. CircKIF4A has been found to be involved in the progression of multiple cancers while its role in NSCLC remains unclear. To investigate the functions of circKIF4A, we assessed the expression of circKIF4A in NSCLC cells and tissues and performed experiments to determine the detailed functions of circKIF4A in NSCLC, including migration and proliferation. We found CircKIF4A expressed more heavily in the cells and tissues of NSCLC patients, and functional studies showed that inhibition of circKIF4A reduced NSCLC cells metastasis and proliferation. Furthermore, we seek to identify the underlying regulatory effect of circKIF4A in NSCLC. Studies revealed that circKIF4A sponged miR-1238 to promote NSCLC progression by up-regulating claudin14 (CLDN14) expression. In conclusion, circKIF4A is a potential diagnostic and therapeutic target in the circKIF4A/miR-1238/CLDN14 axis that plays an important role in NSCLC progression. | CircKIF4A promotes non-small cell lung cancer proliferation and metastasis through MiR-1238/CLDN14 axis
As the leading cause of cancer-related death worldwide, non-small-cell lung cancer (NSCLC) is still in need of improved therapeutic strategies. CircKIF4A has been found to be involved in the progression of multiple cancers while its role in NSCLC remains unclear. To investigate the functions of circKIF4A, we assessed the expression of circKIF4A in NSCLC cells and tissues and performed experiments to determine the detailed functions of circKIF4A in NSCLC, including migration and proliferation. We found CircKIF4A expressed more heavily in the cells and tissues of NSCLC patients, and functional studies showed that inhibition of circKIF4A reduced NSCLC cells metastasis and proliferation. Furthermore, we seek to identify the underlying regulatory effect of circKIF4A in NSCLC. Studies revealed that circKIF4A sponged miR-1238 to promote NSCLC progression by up-regulating claudin14 (CLDN14) expression. In conclusion, circKIF4A is a potential diagnostic and therapeutic target in the circKIF4A/miR-1238/CLDN14 axis that plays an important role in NSCLC progression.
Lung cancer is still major burden of death around the world, mainly because of high metastasis rate [1]. Among of all lung cancers, non-small-cell lung cancer (NSCLC) occupies nearly 85%. Despite improvements in overall survival of patients by a variety of treatment strategies especially targeted therapy and immunotherapy, NSCLC still has a bleak prognosis. In order to develop novel and useful therapeutic tools to better control this disease, a further understanding of the mechanisms of NSCLC progression is urgently needed. Deregulation of non-coding RNAs (ncRNAs) has been reported involved in lung cancer progressions [2, 3]. CircRNAs play key roles in lung cancer tumorigenesis, progress, invasion and metastasis and might be promising diagnosis and therapeutic targets [4, 5]. Previous studies have found that circKIF4A (hsa_circ_0007255) is vital in multiple cancer progressions. In ovarian cancer, circKIF4A was highly expressed and enhanced cell proliferation and migration [6]. In glioma, circKIF4A promoted tumor development through the miR-139-3p/Wnt5a axis [7]. Besides, circKIF4A regulated KIF4A expression to affect TNBC progression via sponging miR-375 [8]. However, it remains unclear how circKIF4A impacts upon NSCLC. In this study, circKIF4A was found over-expressed in NSCLC cell lines and tissues. Besides, inhibition of circKIF4A decreased NSCLC metastasis and cell proliferation. CircKIF4A was found sponged miR-1238 to increase the expression of CLDN14, which promotes NSCLC progression. CircKIF4A might be an underlying therapeutic target for NSCLC treatment.
We performed qRT-PCR in NSCLC cell lines. Figure 1A showed that it over-expressed compared with normal cell line. Next, we collected 42 pairs of NSCLC tissues and normal tissues. The results further confirmed our conclusion (Figure 1B).
We used siRNAs to knockdown circKIF4A and si-circKIF4A#1 was chosen for the further experiments (Figure 2A). The result of CCK-8 assay showed that the inhibition of circKIF4A suppressed cell proliferation (Figure 2B). Besides, circKIF4A inhibition restrained the colony formation ability of NSCLC cells (Figure 2C, 2D). Additionally, transwell assay indicated that knockdown of circKIF4A decreased NSCLC cells metastasis (Figure 2E, 2F). Finally, we used xenograft models to explore the functions of circKIF4A. We found that knockdown of circKIF4A suppressed tumor growth in NSCLC (Figure 2G, 2H).
circRNAs could regulate gene expression by acting as microRNA decoys. Here, we explored the sub-location of circKIF4A in NSCLC cells. Figure 3A revealed circKIF4A was mostly located in cell cytoplasm. Next, Circular RNA Interactome was devoted. Figure 3B showed the predicted interaction and binding sites for miR-1238 in circKIF4A sequence. Therefore, luciferase reporter assay was conducted and the result showed that the co-transfected cells with wild type luciferase reporter and miR-1238 mimics led to the reduction of luciferase intensity (Figure 3C). We also performed RIP assay and found that MS2bs-circKIF4A group was enriched in miR-1238, suggesting that circKIF4A could directly bind with miR-1238 to sponge miR-1238 (Figure 3D).
Next, we assessed miR-1238 expression in NSCLC cell lines and the result showed miR-1238 was down-regulated (Figure 4A). We conducted CCK-8 assay and found that miR-1238 could suppress NSCLC cell proliferation (Figure 4B). Additionally, we observed that miR-1238 suppressed the colony formation ability of NSCLC cells (Figure 4C, 4D). Finally, we conducted transwell assay and found that miR-1238 decreased the metastasis ability of NSCLC cells (Figure 4E, 4F).
We searched TargetScan to explore if circKIF4A sponges miR-1238 to regulate downstream target, and claudin14 (CLDN14) was predicted (Figure 5A). Next, we explored CLDN14 expression in NSCLC cell lines and tissues and CLDN14 was up-regulated (Figure 5B, 5C). Luciferase reporter assay revealed that co-transfection with miR-1238 mimics and wild type luciferase reporter decreased the intensity of luciferase, while co-transfection with miR-1238 inhibitor and wild type luciferase reporter increased (Figure 5D). Figure 5E showed that miR-1238 could reduce CLDN14 expression, and miR-1238 inhibitor had a opposite effect on CLDN14. We conducted Subsequent RIP assay on Ago2 and found that circKIF4A, CLDN14, and miR-1238 were basically concentrated in Ago2 (Figure 5F). Moreover, the result of Figure 5G showed circKIF4A functioned as a ceRNA to compete with CLDN14 for binding miRNAs. Moreover, inhibition of circKIF4A lowered the expression of CLDN14, which was contrary to the result of co-transfection with miR-1238 inhibitor. The result of Figure 5H indicated that circKIF4A sponged miR-1238 to regulate CLDN14 expression in NSCLC. Finally, CLDN14 expression in mouse xenograft models has been measured, the result showed that circKIF4A inhibition lowered the expression of CLDN14 in vivo (Figure 5I).
NSCLC remains major burden worldwide [9]. Despite various treatments have occurred, the mortality rate remains high [10]. There are still many problems to be solved urgently. Exploring the underlying mechanisms of NSCLC proliferation and metastasis could help develop individual therapeutic strategies. Non-coding RNAs are associated with lung cancer progressions and could serve as predictive biomarkers [11]. CircRNAs are vital in NSCLC generation and progression [12, 13]. For instance, circRNA_102481 contributed to EGFR-TKIs resistance via the miR-30a-5p/ROR1 axis, which could be an underlying target in NSCLC [14]. CircKIF4A is a promotor in multiple cancers. CircKIF4A facilitated tumor malignant progress via the miR-1231/GPX4 axis in papillary thyroid cancer [15]. CircKIF4A sponged miR-375/1231 accelerates tumor progression via up-regulating NOTCH2 expression in bladder cancer [16]. Besides, circKIF4A promoted metastasis and reduced cell apoptosis by miR-152/ ZEB1 axis in breast cancer [17]. However, it has not been reported that how circKIF4A functions in NSCLC. Here, we assessed circKIF4A expression of NSCLC cell lines (Figure 1). Moreover, inhibition of circKIF4A caused the suppression of proliferation and metastasis, suggesting a vital role of circKIF4A in NSCLC progression (Figure 2). miR-1238 is reported as a suppressor in multiple cancers [18–20]. CircRNAs has the ability to sponge miR-1238 to enhance tumor progressions. circ0070934 promotes cell metastasis by sponging miR-1238/1247-5p in cutaneous squamous cell carcinoma, [21]. In osteosarcoma, circular RNA circ_0000502 accelerates cell proliferation and invasion via sponging miR-1238 [22]. In NSCLC, miR-1238 also suppressed tumor cells by targeting LHX2 [23]. Besides, the results also indicated that miR-1238 was lower expressed in NSCLC cell lines, and miR-1238 suppressed NSCLC cell proliferation and metastasis (Figure 4). Besides, circKIF4A could combine miR-1238 and serve as a sponge for miR-1238 (Figure 3). It has been confirmed that Claudins (CLDNs) were up-regulated in multiple cancers [24]. Among them, CLDN14 could promote tumor proliferation, and invasion through the PI3K/AKT/mTOR pathway [25]. CLDN14 was also found up-regulated in gastric cancer tissues and was related to E-cadherin expression and lymph node metastasis [26]. However, the functions of CLDN14 in NSCLC are still unclear. Here, we assessed CLDN14 expression and found it up-regulated in NSCLC. Acting as a downstream target, CLDN14 could be regulated by miR-1238. Further experiments showed that circKIF4A served as a ceRNA for miR-1238 to enhance CLDN14 expression of NSCLC (Figure 5). In conclusion, we showed that the circKIF4A/miR-1238/CLDN14 axis was involved in NSCLC proliferation and metastasis. Targeting circKIF4A is promising for NSCLC treatment.
Cell lines included Beas2b (normal lung cell line), A549, PC9, H1975 and H1299 (NSCLC cell lines). All of them were purchased from ATCC. DNA fingerprinting was performed to ensure cell authenticity. We also performed the detection for mycoplasma infection routinely. The transfection was done with Lipofectamine 3000 (Invitrogen, USA). miR-1238 mimics and inhibitors, circKIF4A siRNAs, and circKIF4A shRNAs were purchased from GeneCopoeia (USA). Corresponding siRNA sequences of si-NC, si-circKIF4A#1, #2, and #3 were UUCUCCGAACGUGUCACGUTT, GCCUGGAUCUAUAACGUAUTT, GAUCUAUAACGUAUUAAUATT, and UAACGUAUUAAUAUUAACCTT, respectively.
TRIzol (Invitrogen) was utilized to extract total cellular RNA. Cytoplasmic Extraction Reagents (Thermo Fisher Scientific, USA) and NE-PERTM Nuclear were used to extract nuclear and cytoplasmic RNA fractions. An All-in-OneTM miRNA qRT-PCR Detection Kit (GeneCopoeia) and SYBR Premix Ex TaqTM (Takara Bio, Japan) were applied to execute qRT-PCR assay. We synthesized the qRT-PCR primers by GeneCopoeia as follows: Forward of circKIF4A: GAGGTACCCTGCCTGGATCT; Reverse of circKIF4A: TGGAATCTCTGTAGGGCACA; Forward of 18S: TTAATTCCGATAACGAACGAGA; Reverse of 18S: CGCTGAGCCAGTCAGTGTAG; Forward of GAPDH: GGAGCGAGATCCCTCCAAAAT; Reverse of GAPDH: GGCTGTTGTCATACTTCTCATGG; Forward of CLDN14: AGCGGCATGAAGTTTGAGATT; Reverse of CLDN14: CCCGATTGTCTTTGTAGGCAG.
We collected 42 pairs of primary NSCLC and adjacent normal lung tissues from the First Affiliated Hospital, Xi’an Jiaotong University and immediately frozen into liquid nitrogen. We extracted and submitted total RNA to qRT-PCR analysis. We got approval of this study by the Ethics Committee of the First Affiliated Hospital, Xi’an Jiaotong University and performed based on the Declaration of Helsinki. All patients have provided written informed consents.
We resuspended cells (1 × 103) were and titrated into 96-well plates after transfection. Cells were incubated for 48 h at a temperature of 37°C before adding 10 μl CCK-8 solution (Dojindo Laboratories, Japan). We measured the absorbance at 450 nM after incubation for 2 h at 37°C, with microtiter plate reader (Bio-Tek EPOCH2, USA).
We totally resuspended 1 × 103 cells and seeded in 6-well plates. By 14-days incubation at 37°C, methanol fixed with colonies and stained with 0.1% crystal violet. We used ImageJ software to enumerate the colony number.
We resuspended a total of 1 × 104 cells and seeded in the upper migration chambers (BD Biosciences, USA). Simultaneously, we added 10% FBS which was a chemoattractant to the lower chamber. The upper chambers were collected and the cells were further fixed with methanol after one day. Then, 0.1% crystal violet were applied for staining. The cells under the upper chamber were imaged and calculated by ImageJ software.
We got approval of animal experiments and the experiments were performed following the guidelines of Institutional Animal Care and Use Committee of the First Affiliated Hospital, Xi’an Jiaotong University. We subcutaneously injected a total of 2 × 106 A549 cells into 5 male nude mice (4-week-old). We excised the xenograft tumors with the condition of anesthesia to measure the weights of tumors.
The cells were seeded in 96-well plate with the amount of 3 × 104 cells per well. Mutation was made in the predicted miR-1238 binding sites of circKIF4A and 3′-UTR of CLDN14. The miRNA mimics, inhibitors and constructed reporting vectors (circKIF4A-wt/mut or CLDN14 3′-UTR-wt/mut) were co-transfected into cells for 48 h. The relative luciferase signal was further detected using dual-luciferase reporter assay (Promega, USA).
We transfected cells with different treatment included MS2bs-Rluc, MS2bs-circKIF4A-mt, and MS2bs-circKIF4A. We used Magna RIP RNA-Binding Protein Immunoprecipitation Kit (Millipore, USA) to conduct RIP assay after incubating for 48 h. The expression of miR-1238 was assessed as RNA complexes purification. We performed RIP assays for AGO2 with Millipore. Relative abundance of circKIF4A, CLDN14 and miR-1238 was measured later.
The tissues on the slides were incubated in 3% H2O2 solution for 15 minutes after deparaffinization and rehydration at room temperature. The antigen retrieval was further performed using citrate buffer in a cooker at 96°C for 4 min. After blocking by goat serum, antibody against CLDN14 (dilution 1:200, Affinity, USA) were used for incubation overnight at 4°C. The slides were incubated at room temperature for 10 minutes with biotinylated secondary antibody, and finally HRP-Streptavidin. The slides were imaged after DAB staining.
We conducted statistical analysis with SPSS 25.0. T tests were applied to make comparisons between groups. We set P < 0.05 as a significant value. Unless specific description, we presented data as the mean ± 3 S.D. | true | true | true |
PMC9550459 | Dongsheng He,Jun Hu,Yuhai Lu,Weikun Jia,Minxue Wei,Xiaofei Zeng,Hong Wang | The Effect of miR-505-5p on Inhibition of Serum Uromodulin Ameliorates Myocardial Inflammation and Apoptosis Induced by Ischemia-Reperfusion | 03-10-2022 | Background It has been found that miR-505-5p is closely related to cardiovascular metabolic risk factors. Nonetheless, there is little research analyzing miR-505-5p for its role as well as molecular mechanism in myocardial injury caused by ischemia-reperfusion (I/R). Methods This work utilized quantitative reverse transcriptase PCR (qRT-PCR) for detecting miR-505-5p and serum uromodulin (sUmod) levels. sUmod, interleukin-1beta (IL-1β), IL-6, IL-10, caspase7, caspase9, tumor necrosis factor-alpha (TNF-α), Bax, and Bcl-xL expression was detected by western blot. Bioinformatics database was used for target prediction and miR-505-5's target was determined by luciferase reporter gene assay. Results Relative to sham group, sUmod was highly expressed within myocardial I/R injury (MIRI), whereas sUmod silencing significantly decreased the heart weight/body weight ratio, reduced serum myocardial enzymes expression, ameliorated I/R-mediated myocardial apoptosis, and inflammation. TargetScan bioinformatics database and luciferase reporter genes confirmed that sUmod was miR-505-5p's direct target gene, besides, miR-505-5p overexpression significantly improved the myocardial injury score, increased IL-10, decreased TNF-α, IL-1β, IL-6 expression, decreased caspase7, caspase9, Bax expression, and increased Bcl-xL expression. More importantly, overexpression of sUmod abolished miR-505-5p overexpression's role in I/R-mediated myocardial apoptosis and inflammation. Conclusion miR-505-5p can improve I/R-mediated myocardial apoptosis and inflammation by targeting sUmod. In this study, miR-505-5p is related to MIRI pathogenesis, which provides the new possible targeted therapy in patients with MIRI. | The Effect of miR-505-5p on Inhibition of Serum Uromodulin Ameliorates Myocardial Inflammation and Apoptosis Induced by Ischemia-Reperfusion
It has been found that miR-505-5p is closely related to cardiovascular metabolic risk factors. Nonetheless, there is little research analyzing miR-505-5p for its role as well as molecular mechanism in myocardial injury caused by ischemia-reperfusion (I/R).
This work utilized quantitative reverse transcriptase PCR (qRT-PCR) for detecting miR-505-5p and serum uromodulin (sUmod) levels. sUmod, interleukin-1beta (IL-1β), IL-6, IL-10, caspase7, caspase9, tumor necrosis factor-alpha (TNF-α), Bax, and Bcl-xL expression was detected by western blot. Bioinformatics database was used for target prediction and miR-505-5's target was determined by luciferase reporter gene assay.
Relative to sham group, sUmod was highly expressed within myocardial I/R injury (MIRI), whereas sUmod silencing significantly decreased the heart weight/body weight ratio, reduced serum myocardial enzymes expression, ameliorated I/R-mediated myocardial apoptosis, and inflammation. TargetScan bioinformatics database and luciferase reporter genes confirmed that sUmod was miR-505-5p's direct target gene, besides, miR-505-5p overexpression significantly improved the myocardial injury score, increased IL-10, decreased TNF-α, IL-1β, IL-6 expression, decreased caspase7, caspase9, Bax expression, and increased Bcl-xL expression. More importantly, overexpression of sUmod abolished miR-505-5p overexpression's role in I/R-mediated myocardial apoptosis and inflammation.
miR-505-5p can improve I/R-mediated myocardial apoptosis and inflammation by targeting sUmod. In this study, miR-505-5p is related to MIRI pathogenesis, which provides the new possible targeted therapy in patients with MIRI.
Acute myocardial infarction (AMI) represents a common factor leading to disability and mortality in patients globally. In emergency situations, timely thrombolytic treatment or surgical coronary artery bypass grafting (CABG) and direct percutaneous coronary intervention (PPCI) can effectively limit myocardial infarction (MI) size and improve heart function as well as patient prognosis [1]. However, myocardial reperfusion sometimes results in myocardial ischemia-reperfusion (I/R) injury (MIRI). MIRI will reverse certain benefits of blood flow restoration. MIRI has the features of cardiomyocyte edema, myofibrillar rupture, sarcolemmal destruction, and the appearance of calcium and phosphorus granules in mitochondria [2, 3]. Some previous studies have demonstrated that mitochondrial dysfunction [4, 5], oxidative stress [6, 7], intracellular calcium overload [8], inflammation [9, 10], and apoptosis [11] were related to MIRI. Up to date, targets for these harmful mediators aye the focus of treatment to guard against MIRI. However, within the complicated clinical environment, MIRI can not be effectively prevented. Therefore, it is a focus of the current research to find a new treatment for protecting cardiac MIRI. Serum uromodulin (sUmod), called Tamm-Horsfall protein (THP) as well, represents the glycoprotein that has a 80-90 kDa molecular weight (MW). Its expression can be detected within epithelial cells in Henle ring thick ascending branch (TAL), but less in the early distal convoluted duct [12]. sUmod is a new biomarker for renal activity as well as renal tubular integrity, which is considered to be related to cardiovascular diseases (CVDs) together with the overall mortality among cardiovascular high-risk cases. A study has shown that sUmod is negatively related to CVDs and overall mortality among cases undergoing coronary angiography [13]. sUmod is negatively correlated with several cardiovascular risk factors, including diabetes and arterial hypertension, which may be one of the reasons why sUmod has cardiovascular protective effects [14]. As reported, sUmod significantly decreased within diabetic nephropathy (DN), acute tubular necrosis, as well as inflammatory cytokine-induced hyperprostaglandin E syndrome [15]. Meanwhile, lower sUmod levels were associated with higher cardiac mortality, increased systemic reactive oxygen species, and increased susceptibility to type 2 diabetes with decreased glucose metabolism [16].Moreover, sUmod promoted the proliferation and phagocytic activity of mononuclear macrophages, and the loss of sUmod aggravated the immune response in renal I/R injury [17] . microRNAs are a small, noncoding family of RNA molecules that have critical effects on cell growth, differentiation together with organ development. miRNAs can directly bind to target mRNA's 3′-untranslated regions (3′-UTR) for regulating gene expression, thereby inducing cleavage or translation inhibition. miRNAs have crucial effects on various inflammatory diseases. miR-505 was initially subject to transcription to the 84-BP pre-mir-505, and later processing to the mature miRNA, which included miR-505-3p and miR-505-5p [18]. miR-505 shows abnormal expression within prostatic cancer (PCa), breast cancer (BC), bladder cancer, colorectal cancer (CRC), and hepatocellular carcinoma (HCC) [19–21]. A study has found that miR-505 decreased HMGB1expression to inhibit autophagy activation of BoDV-1, and ultimately lead to fatal encephalitis in humans [22]. miR-505 was abnormally upregulated in mice with laser-induced choroidal neovascularization, and miR-505 inhibitor inhibited neovascularization and expression of vascular endothelial growth factor (VEGF) [23]. Additionally, miR-505-5p, which is an oncogene, can enhance lung cancer cell growth and inhibit their apoptosis by targeting apoptosis inducing TP53AIP1 [24]. Meanwhile, miR-505-5p also has the tumor suppressive effect on cervical cancer via the target of cyclin dependent kinase 5 [25]. However, it is not clear whether sUmod is miR-505-5p's direct target gene, and whether miR-505-5p can improve I/R-mediated myocardial apoptosis and inflammation by inhibition of sUmod. This work focused on investigating miR-505-5p's effect on myocardial I/R injury (MIRI) as well as its possible mechanism. First, sUmod and miR-505-5p expression was analyzed within I/R myocardium. Secondly, bioinformatics database and luciferase reporter gene were conducted to predict miR-505-5p's target gene. Finally, function of overexpression of miR-505-5p and sUmod in I/R-mediated myocardial inflammation and apoptosis was analyzed.
H9C2 cardiomyocytes (ATCC, Manassas, VA, USA) were cultivated within DMEM (Gibco, USA) that contained 1% penicillin/streptomycin (PS) and 10% fetal bovine serum (FBS; Hyclone, Logan, USA) under 37°C and 5% CO2 conditions within the humid incubator. Medium change was carried out at 3-day intervals and cell passage was performed after achieving 70-80% density.
After reaching 0%-70% density, his work cultured H9C2 cells at 1 day prior to transfection. GenePharma (Shanghai, China) was responsible for preparing miR-505 mimics, miR-505 inhibitor (anti-miR-505), scrambled miRNA (miR-control), and empty control (vector). This work utilized lipofectamine 2000 reagent (Invitrogen, USA) for transfection in line with specific instructions.
GenePharma (Shanghai, China) was also responsible for preparing mutant (MUT) and wild-type (WT) 3′-UTR in sUmod. Thereafter, MUT or WT 3′-UTR that contained mutations of sUmod binding sites was cloned in downstream luciferase within the empty pMIR vectors (Promega, USA) for producing the recombinant constructs (MUT- or WT-sUmod, separately). Afterwards, by adopting lipofectamine 2000, these constructs were cotransfected into VSMCs with miR-control or miR-505 mimics. In addition, cells were cotransfected with pRL-TK vector (Promega, USA) as well as Renilla luciferase gene for control. At 48 h later, dual luciferase assay (Promega, USA) was utilized to measure Renilla and firefly luciferase activities in line with specific protocols.
This work obtained forty aged 6-8-week-old male healthy C57BL/6 mice weighing 22-24 g in Beijing Vital River Laboratory Animal Technology Limited Company in China. All mice were then housed in cages at specific temperature and 12 h/12 h light/dark cycle, and they were allowed to drink water and eat chow freely. Each animal experiment was carried out following Guidelines of the Use and Care of Laboratory Animals for Biomedical Research released by National Institutes of Health (No. 85-23, revised 1996). All animals were randomized as the sham and I/R groups. All experimental protocols gained approval from ethics committee.
Construction of MIRI model according to previous description [26]. In brief, a 7-0 silk thread was utilized to ligate the left anterior descending branch to establish a mouse myocardial I/R model. Following isoflurane anesthesia, each mouse was intubated and mechanically ventilated, followed by thoracotomy to ligate the left anterior descending branch for a 30 min period. After 3 weeks of reperfusion, the mice were killed for analysis. Except that the left anterior descending branch was not ligated, all steps in the sham group were the same as those in the experimental animals, with the exception of nonligation of left anterior descending branch.
Following this experiment, mouse serum and heart were collected. Briefly, all animals were anesthetized intraperitoneally using 2% sodium pentobarbital (No.57-33-0, Shanghai Rongbai Biological Technology Company, China) at 1.5 ml/kg. The pleural were opened and the heart was collected. The part of heart tissues in every group was immersed in 10% formalin buffer (No.G2161, Solarbio, China) for pathological examination. The other heart tissues in every group were used for mRNA and protein analysis.
The whole blood of mice was placed in the collecting vessel for 30 minutes, 3000 rpm, centrifuged for 10 min, and the serum was taken. The levels of serum BNP, cTnI, CK, and LDH were detected by Hitachi automatic biochemical analyzer 3500.
The part of heart tissues in every group were fixed in 10% formaldehyde (No. G2161, Solarbio, China), followed by paraffin embedding with the Leica Microsystem tissue processor (ASP 300S, Germany). Thereafter, 3-5 μm thickness sections were prepared with the Leica Microsystem microtome (Model RM 2265, Germany) to analyze tissue histology by hematoxylin and eosin (H&E) staining.
This work utilized TRIzol reagent (Life Technologies, USA) to extract total tissue RNA, which was then collected to prepare the first-strand cDNA using SuperScript II RT Kit (Invitrogen, USA) Reverse Transcription of miR-505-5p was done using miScript Reverse Transcription Kit (Qiagen, Germany) .. Subsequently, SYBR Green Real-time PCR kit was used to measure miR-505-5p level using the ABI Prism7500 sequence detection system (Applied Biosystems, USA). Shengke Company (Guangzhou, China) was responsible for preparing primers used in qRT-PCR. miR-505-5p, forward (F): 5′-GTAATCGGGAGCCAGGAAGT-3′, reverse (R): 5′-GTGTCGTGGAGTCGGCAAT-3′; U6 (F): 5′-ATTGGAACGATACAGAG AAGATT-3′; (R): 5′-AGGAACGCTTCACGAATTTG-3′. PCR program is 5 min under 95°C; 15 s under 95°C and 60 s under 60°C for altogether 40 cycles. 2−ΔΔCt was utilized to determine fold change (FC) of miR-505-5p by normalizing to GAPDH.
This work utilized tissue protein extraction kit (No. FD0889, Hangzhou Fude Biological Technology Company, China) to extract total tissue proteins. Thereafter, the BCA protein assay kit (No. FD2001, Hangzhou Fude Biological Technology Company, China) was utilized to measure protein content. Subsequently, proteins were separated by 10%SDS-PAGE after 5 min sample boiling and denaturation, followed by transfer onto 5% defatted milk PBST buffer for a 1 h period under ambient temperature. After washing by PBST thrice, membranes were incubated with primary antibodies shown in Table 1 under 4°C overnight. After further washing by PBST thrice, membranes were incubated with appropriate secondary antibody for 1.5 h. The Clarity™ Western ECL Substrate (No.170-5061, Bio-Rad Laboratories, USA) was utilized for protein visualization using the Tanon 5200 chemiluminescence image analysis system (Tanon Science and Technology Co., Ltd., Shanghai, China). The absorbance (OD) ratio of target protein to GAPDH was used as the relative expression level of the target protein.
Results were represented by mean ± SD and examined by SPSS20.0 (Chicago, IL, USA). Student's t-test was conducted to compare 2 groups, while one-way ANOVA combined with Tukey's test was adopted to compare several groups. P < 0.05 stood for statistical significance.
As observed from Figure 1(a), the symmetrical gene expression distribution within diverse samples were consistent with others, which indicated the absence of interference within samples and valid cross-comparison. Through analyzing GEO2R in GEO database, the data showed that sUmod was abnormally highly expressed in MIRI relative to sham group (Figure 1(b)). As revealed by western blot and qRT-PCR, sUmod showed abnormally high expression within MIRI group (Figures 1(c)–1(e)). Moreover, relative to I/R group, sUmod silencing remarkably declined the ratio of heart weight to body weight (BW) (Figure 1(f)), and reduced serum expression of BNP, LDH, cTnl, and CK (Figures 1(g)–1(j)).
HE staining and WB assays were conducted to detect effects on I/R-mediated myocardial apoptosis and inflammation. Our data showed that I/R led to myocardial degeneration/necrosis, inflammatory cells infiltration, whereas sUmod silencing effectively improved MIRI score (Figures 2(a) and 2(b)), decreased TNF-α, IL-1β, IL-6 levels, but increased IL-10 expression (Figures 2(c)–2(g)). Moreover, relative to sham group, I/R dramatically enhanced caspase7, caspase9 and Bax expression, and decreased Bcl-xL expression, whereas sUmod silencing effectively decreased caspase7, caspase9 and Bax levels, and elevated Bcl-xL level (Figures 2(h)–2(l)).
Target was predicted by TargetScan bioinformatics database, and the potential regulatory factor miR-505-5p of sUmod was obtained (Figure 3(a)). According to luciferase reporter gene assay, miR-505-5p overexpression in cardiomyocytes H9C2 significantly suppressed luciferase activities in wild-type-sUmod group (Figure 3(b)). miR-505-5p plasmid transfection significantly upregulated miR-505-5p level within H9C2 cells (Figure 3(c)). Moreover, miR-505-5p upregulation remarkably inhibited sUmod level in H9C2 cells, and sUmod overexpression offset the effect of miR-505-5p upregulation (Figures, 3(d)–3(f)), indicating that miR-505-5p targeted regulation of sUmod expression.
miR-505-5p showed low expression within MIRI, and miR-505-5p upregulation significantly upregulated miR-505-5p level, and was reversed by overexpression of sUmod (Figure 4(a)). According to qRT-PCR and WB assays, miR-505-5p upregulation inhibited sUmod induced by MIRI. Meanwhile, sUmod upregulation remarkably offset decrease of sUmod expression induced by miR-505-5p overexpression (Figures 4(b)–4(d)). Moreover, relative to I/R group, miR-505-5p upregulation significantly inhibited the heart weight/body weight ratio, and reduced serum BNP, LDH, cTnl, and CK expression, whereas the overexpression of sUmod counteracted miR-505-5p overexpression's impact on heart weight/body weight ratio, serum BNP, LDH, cTnl, and CK (Figures 4(e)–4(i)).
Our data showed that I/R caused cardiomyocyte degeneration and necrosis, inflammatory cell infiltration, miR-505-5p overexpression effectively improved MIRI score, whereas sUmod upregulation significantly counteracted miR-505-5p overexpression on MIRI score (Figures 5(a) and 5(b)). Moreover, relative to sham group, I/R-mediated increases in TNF-α, IL-1β and IL-6 levels, whereas declined IL-10 expression, and miR-505-5p overexpression effectively decreased TNF-α, IL-1β and IL-6 levels, but increased IL-10 expression, whereas sUmod upregulation remarkably offset miR-505-5p overexpression's impact on myocardial I/R-induced inflammation (Figures 5(c)–5(g)). Furthermore, I/R remarkably upregulated caspase7, caspase9, and Bax levels, and declined Bcl-xL expression, and miR-505-5p upregulation effectively suppressed the expression of caspase7, caspase9 and Bax, and increased Bcl-xL expression, whereas sUmod upregulation remarkably counteracted miR-505-5p overexpression's impact on myocardial I/R-induced apoptosis (Figures 5(h) –5(l)).
It has been found that miR-505-5p is closely related to cardiovascular metabolic risk factors [27]. In this study, our data showed that sUmod was miR-505-5p's direct target gene. Meanwhile, miR-505-5p and sUmod showed high expression within MIRI, which were associated with increased serum myocardial enzyme level. miR-505-5p or sUmod silencing effectively improved MIRI score and inhibit myocardial apoptosis and inflammation. sUmod upregulation can counteract the miR-505-5p overexpression's effect on inhibiting MIRI-mediated apoptosis and inflammation. Based on the results, miR-505-5p improve myocardial I/R-mediated apoptosis and inflammation through inhibiting sUmod. Up to date, according to the report, I/R leads to inflammation, apoptosis, iron death and fibrosis, and even cardiac arrest, and inflammation and apoptosis have an indispensable effect on MIRI genesis [28]. The inflammatory response is supported by macrophages in the heart and white blood cells in circulation, which can easily enter the stroma through damaged vascular endothelial cells. Moreover, if the ischemic period is long enough, the death process of parenchyma cells and cardiomyocytes is activated, mainly because of cell necrosis, followed by apoptosis and autophagy [29]. The role of leukocytes and mitochondria during MIRI plays a key effect on the I/R-induced inflammatory mechanism. Macrophages can show different phenotypes according to the state and phase of inflammation. M1 macrophage represents proinflammatory characteristics, while M2 macrophage can promote wound healing, and downregulate several cytokines. M1 macrophages activate NF-κB signaling pathway by binding to MyD88, thus transcribing TNF-α, IL-1β, IL-6, and IL-12 expression. Macrophages polarize M2 phenotypes by stimulating glucocorticoid receptors, IL-10 receptors, IL-3, and IL-14 distributed within B cells, T cells, macrophages, and mast cells. Our data showed that sUmod showed high expression within MIRI, which was associated with increased serum myocardial enzyme level. Meanwhile, sUmod silencing can effectively promote MIRI score, inhibit myocardial inflammation and apoptosis. sUmod was reported to interact with myoloid dendritic cells (DCs), monocytes, and neutrophils through toll-like receptor 4 (TLR4), and has an effect on the regulation of inflammation as well as innate immunity [30], and the immunosuppressive effect of sUmod was achieved by binding to TNF-α and interleukin-1 [31]. In addition, sUmod stimulated extrarenal tissue, and caused strong inflammatory response, which was characterized by obviously recruiting inflammatory monocytes and neutrophils [32]. sUmod induced the secretion of TNF-α and the expression of tissue factors in human monocytes, triggered DC maturation through activating NF-κB and TLR4, and activated protease release, respiratory burst, degranulation, and phagocytosis of neutrophils [33]. Intravenous injection of sUmod caused systemic inflammation, and the proinflammatory effect of sUmod was also described [34]. In contrast, sUmod limited inflammation by inhibiting proinflammatory cytokines and chemokines, which negatively regulated granulocyte production and neutrophil homeostasis in the system [35, 36]. Furthermore, sUmod was also reported to inhibit the activation of nonselective calcium channel TRPM2 in mice and reduce the increase of reactive oxygen species in kidney and systemic acute renal injury [37]. sUmod enhanced the expression of CXCL8, inhibited the expression of human granulocyte CD62L [38], stimulated NLRP3 inflammatory bodies within human monocytes, causing IL-1β production and cell apoptosis [39]. The results suggest that sUmod can improve myocardial I/R-mediated apoptosis and inflammation. miRNAs were related to MIRI through altering apoptosis, inflammation, and fibrosis. According to our results, miR-505-5p was expressed highly during myocardial I/R injury, and altered serum myocardial enzyme expression. miR-505-5p silencing can effectively improve MIRI score, apoptosis, and inflammation. miR-505-5p shows low expression in breast cancer and is one of the most valuable biomarkers to identify breast cancer [40]. miR-505-5p promoted lung cancer cell growth via TP53AIP1 and plays the role of oncogenes [24]. Furthermore, miR-505-5p level in osteosarcoma significantly elevated, whereas inhibiting miR-505-5p upregulated RASSF8, thus inhibiting osteosarcoma cell proliferation and promote their apoptosis [41]. More importantly, miR-505-5p targeted SRSF1 (splicing factor 1 rich in serine/arginine), while SRSF1 thus regulated enoglin, tissue factors and vascular endothelial growth factor A (VEGFA), and controled the endothelial cell molecular aging process, causing age-related vascular disease [27, 42]. Besides, miR-505-3p is another member of the miR-505 family, whose expression also increased in osteoarthritis, whereas overexpression of circFAM160A2 improved mitochondrial dysfunction and chondrocyte apoptosis through inhibiting miR-505-3p. These results suggest that circFAM160A2 can decrease chondrocyte apoptosis in osteoarthritis via miR-505-3p [43]. Collectively, miR-505-5p improved myocardial I/R-mediated inflammation and apoptosis. miR-505 is a critical regulating factor for chronic inflammation in mammals [44]. Our data demonstrated that sUmod is miR-505-5p's direct downstream target, and sUmod overexpression counteract miR-505-5p konckdown's impact on I/R-induced myocardial apoptosis and inflammation. As discovered in a similar study, miR-505 level within lipopolysaccharide-induced endometritis dramatically decreases. Overexpression of miR-505 can significantly decrease TNF-α, IL-1β, IL-6 levels, whereas inhibition of miR-505 can get the opposite result. Moreover, double luciferase analysis confirmed that miR-505 targets noncoding region in HMGB13′ and regulates NF- κB signaling activation mediated by lipopolysaccharide, thus reducing the production of proinflammatory cytokines [45]. In addition, oxidized low density lipoprotein was reported to induce miR-505expression, and inhibit sirt3 expression through activating NF-κB pathway, which leads to neutrophils releasing reactive oxygen species (ROS) [46]. Such results help to understand miR-505-5p for its effect against apoptosis and inflammation during MIRI, and the miR-505-5p/sUmod axis may help to limit myocardial ischemic injury. In short, this study identifies sUmod as miR-505-5p's direct downstream target gene. miR-505-5p overexpression can effectively improve I/R-mediated myocardial apoptosis and inflammation by targeting inhibition of sUmod expression. | true | true | true |
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PMC9550508 | Qi Sun,Zhifu Gui,Zhenguo Zhao,Wenlong Xu,JunJia Zhu,Chundong Gao,Wei Zhao,Hao Hu | Overexpression of LncRNA MNX1-AS1/PPFIA4 Activates AKT/HIF-1α Signal Pathway to Promote Stemness of Colorectal Adenocarcinoma Cells | 03-10-2022 | Purpose The purpose of this study was to explore the role of the lncRNA MNX1-AS1 and its related downstream signaling pathways in colorectal adenocarcinoma (COAD). Methods COAD tissues and cells were prepared and treated with sh-MNX1-AS1, pcDNA-MNX1-AS1, sh-PPFIA4, LY29004, and their controls. CCK8 and colony formation assays were undertaken for evaluating cell proliferation. Tumor cell migratory ability was detected by transwell assay. Apoptosis detection was processed by YO-PRO-1/PI Staining. The regulated relationship between lncRNA MNX1-AS1 and PPFIA4 was confirmed by RIP-ChIP assay. Q-PCR was applied to detect genes related to tumor cell stemness, proliferation, migration, and apoptosis in each group. Finally, a xenograft tumor model was constructed to verify the result in vivo. Results COAD patients with high expression of the lncRNA MNX1-AS1 have poor prognosis. LncRNA MNX1-AS1 promotes the stemness of COAD cells. PPFIA4 mediates lncRNA MNX1-AS1 expression and affects COAD cell stemness. LncRNA MNX1-AS1 accelerates proliferation and migration, while it suppresses apoptosis. LncRNA MNX1-AS1/PPFIA4 accelerates tumor growth in COAD model. LncRNA MNX1-AS1/PPFIA4 activates the downstream AKT/HIF-1α signaling pathway to promote COAD development. LY29004 significantly inhibits the tumorigenic ability of lncRNA MNX1-AS1 and PPFIA4. Conclusion LncRNA MNX1-AS1/PPFIA4 activates AKT/HIF-1α signal pathway to promote the stemness of COAD cells, which could be a new target for COAD treatment. | Overexpression of LncRNA MNX1-AS1/PPFIA4 Activates AKT/HIF-1α Signal Pathway to Promote Stemness of Colorectal Adenocarcinoma Cells
The purpose of this study was to explore the role of the lncRNA MNX1-AS1 and its related downstream signaling pathways in colorectal adenocarcinoma (COAD).
COAD tissues and cells were prepared and treated with sh-MNX1-AS1, pcDNA-MNX1-AS1, sh-PPFIA4, LY29004, and their controls. CCK8 and colony formation assays were undertaken for evaluating cell proliferation. Tumor cell migratory ability was detected by transwell assay. Apoptosis detection was processed by YO-PRO-1/PI Staining. The regulated relationship between lncRNA MNX1-AS1 and PPFIA4 was confirmed by RIP-ChIP assay. Q-PCR was applied to detect genes related to tumor cell stemness, proliferation, migration, and apoptosis in each group. Finally, a xenograft tumor model was constructed to verify the result in vivo.
COAD patients with high expression of the lncRNA MNX1-AS1 have poor prognosis. LncRNA MNX1-AS1 promotes the stemness of COAD cells. PPFIA4 mediates lncRNA MNX1-AS1 expression and affects COAD cell stemness. LncRNA MNX1-AS1 accelerates proliferation and migration, while it suppresses apoptosis. LncRNA MNX1-AS1/PPFIA4 accelerates tumor growth in COAD model. LncRNA MNX1-AS1/PPFIA4 activates the downstream AKT/HIF-1α signaling pathway to promote COAD development. LY29004 significantly inhibits the tumorigenic ability of lncRNA MNX1-AS1 and PPFIA4.
LncRNA MNX1-AS1/PPFIA4 activates AKT/HIF-1α signal pathway to promote the stemness of COAD cells, which could be a new target for COAD treatment.
Colorectal cancer (CRC) is a common malignant tumor with increasing morbidity and mortality [1]. According to the 2020 global cancer statistics, there are 555,000 new cases of CRC in China, ranking the third among malignant tumors [2]. The latest statistics from the National Cancer Center show that the number of new cases of CRC in China accounts for 9.9% of all new malignancies [3]. Colorectal adenocarcinoma (COAD) is the most common type of CRC [4]. The diagnosis of colorectal cancer involves imaging evaluation, pathological evaluation, and endoscopy, and the treatments are mainly surgery, chemotherapy, and radiotherapy [5]. Multidisciplinary comprehensive treatment model improves the level of colorectal cancer diagnosis and treatment. With the continuous development of biotechnology, lncRNA has been identified to be a common molecular mechanism associated with tumors [6, 7]. Several lncRNAs with critical roles in tumor progression have been identified in colorectal cancer [8]. For instance, LncRNA NEAT1 increases its stability by activating the AKT signaling pathway, which in turn promotes colorectal cancer progression [9]. Furthermore, downregulation of LncRNA HOXD-AS1 promotes cell proliferation and metastasis by reducing the repressor marker (H3K27me3) of the HOXD3 promoter region in COAD cells [10]. Besides, lncRNA MEG3 increases the sensitivity of colorectal cancer cells to oxaliplatin by targeting miRNA-141 to upregulate PDCD4 expression [11]. MIR100HG has also been shown to be a potent EMT inducer in colorectal cancer, possibly contributing to cetuximab resistance and metastasis by activating the MIR100HG/hnRNPA2B1/TCF7L2 feedback loop [12]. Therefore, the potential of lncRNAs as novel biomarkers for the diagnosis and treatment of colorectal cancer cannot be ignored. Development of novel biomarkers not only improves treatment efficiency, but also provides more personalized treatment plans for COAD patients. In recent years, lncRNA MNX1-AS1 was widely reported to be a cancer-promoting factor in various cancers, such as intrahepatic cholangiocarcinoma [13], ovarian cancer [14], and gastric cancer [15]. Cancer stem cells are the key to tumor self-maintenance, and its main sources are cancer progenitor cells [16, 17]. The genetic, epigenetic, and proliferation and division patterns of cancer stem cells regulate tumor proliferation and malignancy. Moreover, stem cells affect cancer metastasis by regulating EMT-related pathways [18]. Thereby, online databases, in vitro and vivo experiments were combined to research the role of lncRNA MNX1-AS1, its' downstream, and related pathways in COAD. PPFIA4 was reported to be the target of lncRNA MNX1-AS1. A bioinformatic analysis was performed by Fu et al. [19] and confirmed that the mRNA level of PPFIA4 was higher in CRC tissue samples than that in normal colon tissue. In 2021, Huang et al. confirmed that PPFIA4 enhanced colorectal cancer glycolysis, which in turn promoted cell proliferation and migration [20]. In addition, MNX1-AS1/PPFIA4 activates the downstream AKT/HIF-1α pathway to promote COAD development in this study. Phosphorylation of AKT regulates cell growth, proliferation, and glucose metabolism [21]. Moreover, the target genes of HIF-1α have been referred to be involved in energy metabolism and angiogenesis of cells [22]. In this study, the role and mechanism of lncRNA MNX1-AS1 in the occurrence and development of COAD were investigated. The regulated relationship between lncRNA MNX1-AS1/PPFIA4 and AKT/HIF-1α pathway was explored. The results of this study may provide a theoretical basis for COAD treatment.
The expression of MNX1-AS1 in COAD tissues was analyzed in 2 independent online TCGA databases, Gene Expression Profiling Interactive Analysis (GEPIA) [23] and The University of ALabama at Birmingham CANcer data analysis Portal (UALACN) [24]. The Starbase database [25] was applied to analyze the relationship between MNX1-AS1 expression and COAD prognosis.
Fifty patients with colorectal adenocarcinoma who underwent surgical resection in Department of General Surgery, Jiangyin People's Hospital Affiliated to Nantong University from April 2019 to May 2020 were collected. No radiotherapy, chemotherapy, or other tumor-specific treatments were received before surgery, and tumor tissues were collected from non-necrotic sites of the tumor. The study has been approved by the ethics committee of Jiangyin People's Hospital Affiliated to Nantong University (CD2019F13). The patients included 27 males and 23 females; the age ranged from 32 to 78 years old. All specimens were confirmed by postoperative pathological sections. Fresh surgical specimens of paracancerous and normal tissues were immediately cryopreserved. All patients were informed and gave their consents. Various COAD cell lines (HT29, HCT116, T84, SW480, LOVO, and SW620) and HCM460 cell line were purchased from ATCC, subcultured in RPMI1640 medium containing 10% FBS at 37 °C and 5% CO2-saturated humidity. Cells in logarithmic growth phase were taken for experiments. Suspension sphere culture was used to screen stem cells in HT29 and HCT116 cells. Briefly, tumor cells were incubated in a serum-free medium supplemented with growth factors, and stem cells therein proliferated to form dense spheres and maintain an undifferentiated state. HT29, HCT116, HT29 CSC, and HCT116 CSC cells were made into cell suspension and divided into shRNA-NC group and sh-MNX1-AS1 group. Referring to the instructions of the kit, Lipofectamine® 2000 was used to transfect sh-MNX1-AS1 and its control into cells, and the cells were cultured for 48 h. Cells were collected for RT-PCR detection of MNX1-AS1 expression levels in cells of each group. Sphere formation was observed and photographed by inverted microscope. Similarly, Bio-MNX1-ASA, pcDNA-MNX1-AS1, sh-PPFIA4, and their controls were also transfected based on the above steps. For pathway exploring, PI3K inhibitor LY29004 (LY, 20 mM) was used to treat cells in different groups. The same number of transfected tumor stem cells in each group were taken, seeded in 6-well plates, and treated with LY29004 for 48 h.
Total RNA from tissues and cells was isolated by TRIzol reagent. The total RNA was reversely transcribed according to the instructions of the cDNA reverse transcription kit, and the cDNA was used as the template. Amplification was performed according to the instructions of the Fast Start Universal SYBR Green Mastermix kit. The reaction was carried out for 40 cycles, and the conditions were predenaturation at 95 °C for 5 s, denaturation at 95 °C for 5 s, and annealing at 60 °C for 30 s. The relative expression of MNX1-AS1 was calculated by 2-ΔΔCt method with GAPDH as internal reference. Besides, stemness markers (OCT4, CD33, CD133, and SOX2), proliferation-related genes (cyclin A1 and B1), migration-related genes (E-cadherin and N-cadherin) and apoptosis-related genes (Bax and Bcl-2) were also detected by Q-PCR. Primers were designed as follows: MNX1-AS1, (F) 5′-CCCGCATTTTCAGATTCAC-3′, (R) 5′-GCTCTCAGCCTCGCCATA-3′; GAPDH, (F) 5′-GTCAACGGATTTGGTCTGTATT-3′, (R) 5′ -AGTCTTCTGGGTGGGCAGTGAT-3′, OCT4, (F) 5′-CCCCAATGCCGTGAAGTT-3′, (R) 5′-GAAAGGTGTCCCTGTAGCG-3′; CD33, (F) 5′-ATCCGCCTAAACTCACATGG-3′, (R) 5′-AGGAATGAACGTCAGGATGG-3′; CD133, (F) 5′-TTCTGCCTGTGTAACTTTGCA-3′, (R) 5′-TTGTTGTGCAACGTCTTTGCA-3′; SOX2, (F) 5′-CGAGATAAACATGGCAATCAAAAT-3′, (R) 5′-AATTGAGAAGCCTCTCCTT-3′; cyclin A1, (F) 5′-GCTTTCCCGCAATCATGTACCC-3 ′, (R) 5 ′-CTCAAATGCCATCCCCTCTCT-3′; cyclin B1, (F) 5′-GCCAATAAGGAGGGAGCA-3′, (R) 5′-AGCGGGGAGAAGCAGAAC-3′; E-cadherin, (F) 5′-TTACTGCCCCCAGAGGATGA-3′, (R) 5′-TGCAACGTCGTTACGAGTCA-3′; N-cadherin, (F) 5′-GACAATGCCCTCAAGTGTT-3′, (R) 5′-CCATTAAGCCGAGTGATGGT-3′; Bax, (F)5′-GTGAATGGAGCCACTGCGCA-3′, (R) 5′-CCCCATCCCGGAAGAGTTCA-3′; Bcl-2, (F) 5′-GGTGCCACCTGTGGTCCACCTG-3′, (R) 5′-GTTCACTGTTGGCCCCAGATAGG-3′.
A total of 100 ml of cell suspension with 2 × 103 cells per well were added in a 96-well plate. Three replicate wells were set in each group, and the culture plates were pre-incubated in an incubator for 24 h at 37 °C and 5% CO2. 10 ml of cells in the transfection group and control group were added to the culture plate. After the culture plate was incubated in the incubator, 10 mL of CCK-8 solution was added to each well, and the culture plate was further incubated in the incubator for 2 h. The cells were taken for CCK-8 assay at 12 h, 24 h, and 48 h after transfection, and their absorbance was measured at a wavelength of 450 nm using an enzyme-linked immunosorbent assay.
After transfection and treatment, cells were seeded in 6-well plates at a density of 200 cells per well, and three duplicate wells were set up. At the same time, 2 mL of 1640 medium containing 10% FBS was added to each well and cultured in an incubator at 37 °C, 5% CO2, and 95% saturated humidity for 2 to 3 weeks. When macroscopic clones appeared in the Petri dish, the culture was terminated, the supernatant was discarded, and the cells were carefully washed twice with PBS. Cells were fixed in 5 ml of 4% paraformaldehyde for 15 min. Then, the fixative solution was removed, and an appropriate amount of GIMSA staining solution was added to the sample for staining for 20 min. Then, the staining solution was slowly washed away with running water and dried in air. The number of clones greater than 50 cells was counted under the microscope.
The cells were digested with trypsin, washed twice with sterile phosphate buffer solution, and resuspended in 10 g/L FBS free medium to adjust the cell density to 1 × 105 cells/ml. A total of 150 μl of cell suspension was added to the upper chamber of the chamber precovered with Matrigel, and 500 μL of medium containing 200 ml/L serum was added to the lower chamber. After 48 h of incubation, the chamber was removed and rinsed with sterile PBS, and the cells in the inner layer of the microporous membrane were carefully wiped off with a cotton swab. Cells were fixed with 95% ethanol for 6 min, stained with 4 g/L crystal violet solution, counted, and photographed under an inverted microscope. The average value of 5 visual fields was randomly selected to analyze the differences between groups.
Cells were trypsinized and washed twice with precooled PBS. A mixed solution of 0.5 ml YP/PI was added, the final concentration of YP was 1 μmol/L, and the final concentration of PI was 2 μg/ml. The percentage of apoptotic cells in about 200 cells was counted under a fluorescence microscope after 15 min of reaction in the dark at room temperature. Each treatment was repeated 3 times.
The experiment was performed according to the instructions of the RIP test kit. Cells were grown to 90% confluence. The cell suspension was prepared, and RIP buffer was added. Anti-Bio or anti-PPFIA4 was incubated with cell suspension overnight at 4 °C. Proteinase K digestion was added. The precipitated PPFIA4 was analyzed by Western blot, using isotype IgG as a negative control and input as a total protein control.
The total protein in the samples was extracted separately. Protein samples were prepared and run on SDS-PAGE gels and then transferred to PVDF membranes. The blocking solution containing 5% BSA was added and blocked for 2 h at room temperature. An appropriate concentration of primary antibody was added and blocked overnight at 4 °C. The next day, the PVDF membrane was washed three times with buffer, and the secondary antibody was added. After incubating for 1 h at room temperature, the chromogenic solution was added for exposure and development.
Total 12 BALB/C nude mice were reared adaptively for 1 week and randomly divided into 4 groups (control, MNX1-AS1, MNX1-AS1 + sh-PPFIA4, and sh-PPFIA4 groups). Cells in each group were collected and adjusted to a cell concentration of 5 × 104/ml. 0.2 ml of cells were inoculated into the right armpit of BALB/C nude mice with a microsyringe and observed every 2 days to record the tumor formation in nude mice. Indications such as tumor nodules and hard texture at the site to be inoculated were identified as tumor formation. Vernier calipers were used to measure the largest diameter (length) and the two smallest diameters (width) of the transplanted tumor. The formula for calculating tumor volume is as follows: tumor volume (mm3) = length × width × width × 0.52. This experiment was approved by the Animal Ethics Committee of Chengdu Medical College.
SPSS 20.0 software was used for statistical analysis. If the measurement data were normally distributed, they were described as the mean ± standard deviation. For measurement data with normal distribution and homogeneous variance, t-test or one-way comparison analysis was used. P < 0.05 was regarded as statistically significant.
The expression of lncRNA MNX1-AS1 was analyzed by 2 online databases and detected in cells and patients' tissues. Based on TCGA databases, lncRNA MNX1-AS1 expressed higher in COAD tissue compared to normal tissues (Figures 1(a) and 1(b)). Moreover, Starbase database was used to detect the relationship betweenMNX1-AS1 expression and COAD prognosis. The patients were divided into 2 groups based on the median value of lncRNA MNX1-AS1. As is shown in Figure 1(c), patients with high ncRNA MNX1-AS1 expression were associated with poor overall survival. Then, the level of lncRNA MNX1-AS1 was detected in COAD tissue, COAD cells, and COAD CSC cells. The results were similar in the data of TCGA and Starbase databases. LncRNA MNX1-AS1 is expressed at a high level in COAD tissues and cells (Figures 1(d) and 1(e)). Among these COAD cell lines, HTC29 and HCT116 were with the highest lncRNA MNX1-AS1 level, which was used for further experiments. Interestingly, lncRNA MNX1-AS1 level in SCS group was higher than that in the corresponding COAD cell lines (Figure 1(f)). According to these results, lncRNA MNX1-AS1 was critical in COAD development, which also affects the stemness of COAD.
Sh-MNX1-AS1 was transfected into COAD SCS to explore its' function. After sh-MNX1-AS1 transfection in HT29 CSC and HCT116 CSC cells, the level of MNX1-AS1 was clearly lower than that in sh-Vector group, indicating that the transfection was successful (Figure 2(a)). Moreover, the sizes of the spheres were photographed and calculated. As is shown in Figures 2(b) and 2(c), sphere formation was significantly inhibited by sh-MNX1-AS1. Then, the stemness of COAD CSC related genes was detected by q-PCR. As we expected, sh-MNX1-AS1 decreased the levels of OCT4, CD33, CD133, and SOX2 (Figure 2(d)). These results confirmed that sh-MNX1-AS1 suppressed the stemness of COAD stem cells.
The proliferation and apoptosis ability affected by sh-MNX1-AS1 transfection were explored. After 24 h, the proliferation was inhibited significantly. The difference between the two groups gradually increased over time (Figure 3(a)). Similarly, the colony number in sh-MNX1-AS1 was clearly lower than that in sh-Vector group (Figures 3(b) and 3(c)). Proliferation-related genes (cyclin A1 and B1) were also detected by Q-PCR. The results were consistent with CCK8 and colony formation. Both cyclin A1 and B1 expressed lower in HT29 SCS and HCT116 SCS (Figure 3(d)). Migration and its' related genes (E-cadherin and N-cadherin) were monitored. Migration was inhibited by sh-MNX1-AS1 (Figures 3(e) and 3(f)). Furthermore, E-cadherin was upregulated, while N-cadherin was increased (Figure 3(g)). Then, apoptosis and its' related genes (Bax and Bcl-2) were detected. As shown in Figures 3(h)–3(j), sh-MNX1-AS1 promoted apoptosis, and the tendency of Bax and Bcl-2 levels was consistent with the result of apoptosis. Therefore, sh-MNX1-AS1 inhibited the development of COAD SCS.
Furthermore, the regulation relationship between lncRNA MNX1 and PPFIA4 was verified. RT-qPCR assay detected the expression of biotin-labeled (bio)-MNX1-AS1 in cancer stem cells. Relative lncRNA MNX1-AS1 level in bio-MNX1-AS1 was higher than that in control (Figure 4(a)). The interaction of Bio-MNX1-AS1 with endogenous PPFIA4 was detected by RIP-ChIP assay with anti-Bio or anti-PPFIA4. As shown in Figures 4(b) and 4(c), MNX1-AS1 interacted with PPFIA4 protein. After sh-MNX1-AS1 and pcDNA-MNX1-AS1 transfection, lncRNA MNX1-AS1 was regulated (Figure 4(d)), indicating that the transfection were successful. RT-qPCR and Western blot were used to examine the effect of knockdown or overexpression of lncRNA MNX1-AS1 in cancer stem cells. LncRNA MNX1-AS1 negatively regulated PPFIA4 expression (Figures 4(e) and 4(f)).
Then, the molecular mechanism of PPFIA4 in stemness was also researched. PPFIA4 significant inhibited PPFIA4 expression in HT29 and HCT116 CSCs, indicating that the transfection of sh-PPFIA4 was successful (Figure 5(a)). The spheroid formation of tumor stem cells was observed under the microscope. Interestingly, lncRNA MNX1-AS1 improved the spheroid forming ability, while sh-PPFIA4 transfection had negative effects (Figures 4(b) and 4(c)). RT-qPCR was used to detect the effect of lncRNA MNX1-AS1 and sh-PPFIA4 on the expression of tumor stemness markers. As shown in Figure 4(d), all stemness markers including OCT4, CD33, CD133, and SOX2 were upregulated by lncRNA MNX1-AS1, while they were decreased by sh-PPFIA4. These results showed that the stemness of COAD cells was clearly affected by lncRNA MNX1-AS1 and sh-PPFIA4.
The roles of LncRNA MNX1-AS1 and sh-PPFIA4 were further researched in COAD stem cells. Based on the transfection, the cells were divided into 4 groups, including control, MNX1-AS1, MNX1-AS1 + sh-PPFIA4, and sh-PPFIA4 groups. After 48 h, the cell proliferation was inhibited significantly in 3 groups (Figure 6(a)). Similarly, the colony number in MNX1-AS1 group was higher than controls, while sh-PPFIA4 inhibited the proliferation behavior (Figures 6(b) and 6(c)). Proliferation-related genes (cyclin A1 and B1) were also detected by Q-PCR. The results were consistent with CCK8 and colony formation. Both cyclin A1 and B1 were at a higher level in MNX1-AS1 group, and at the lowest level in sh-PPFIA4 group (Figure 6(d)). Migration was accelerated by MNX1-AS1, which was inhibited by sh-PPFIA4 (Figures 6(e) and 6(f)). Furthermore, E-cadherin was upregulated, while N-cadherin was increased after lncRNA MNX1-AS1 was upregulated (Figure 6(g)). Then, apoptosis and its' related genes (Bax and Bcl-2) were detected. As shown in Figures 6(h)–6(j), MNX1-AS1 inhibited apoptosis, and the tendency of Bax and Bcl-2 levels was consistent with the result of apoptosis. Sh-PPFIA4 rescued these effects. Therefore, sh-PPFIA4 transfection rescued the effect of upregulated lncRNA MNX1-AS1 on the behavior of COAD stem cells.
The roles of LncRNA MNX1-AS1 and sh-PPFIA4 in vivo were also detected. The changes of volume and weight of tumors in 4 groups were evaluated. As shown in Figures 7(a)–7(c), lncRNA MNX1-AS1 improved tumor growth, while sh-PPFIA4 decreased the tumorigenic ability. Q-PCR assay was used to detect the gene expression related to cancer cell stemness, proliferation, invasion and metastasis, and apoptosis in xenograft tissue. The results and tendency were consistent with the experiments in vitro (Figure 7(d)). These results suggested that sh-PPFIA4 significantly inhibited the tumorigenic effect of lncRNA MNX1-AS1 in vivo.
To detect the effect of lncRNA MNX1-AS1/PPFIA4 on AKT/HIF-1α signaling pathway, Western blot experiment was performed to detect the expressions of p-AKT, AKT, and HIF-1α proteins in the AKT/HIF-1α signaling pathway. The relative expressions of p-AKT/AKT and HIF1α were higher in MNX1-AS1 and PPFI4A groups, while they were lowest in LY20994 group (Figures 8(a) and 8(b)). These results indicated that lncRNA MNX1-AS1/PPFIA4 was involved in AKT/HIF-1α signaling pathway.
Finally, AKT-specific inhibitor (LY294002) was used to verify the effect of lncRNA MNX1-AS1/PPFIA4 on the proliferation and apoptosis of colorectal cancer in vivo. LY29004 significantly inhibited the tumorigenic ability of MNX1-AS1 and PPFIA4 (Supplementary Figures 1(a), 1(b), 1(d), and 1(e)). Q-PCR was used to detect the gene expression related to stemness, proliferation, migration, and apoptosis in each group in vivo. The results were consistent with the experiment in cells (Supplementary Figures 1(c) and 1(f)).
The progression of colorectal cancer involves multiple genetic mutations. The most widely studied in recent years is the role of long noncoding RNAs in the growth and development of colorectal cancer [26, 27]. Some studies have demonstrated that lncRNA plays an important role in the stemness and growth of colorectal cancer cells [28]. In this study, MNX1-AS1 and its related downstream signaling pathways were researched in colorectal adenocarcinoma (COAD). Interestingly, COAD patients with high expression of MNX1-AS1 have poor prognosis. Moreover, MNX1-AS1 promotes stemness and proliferation of COAD cells. The lncRNA MNX1-AS1 is located on chromosome 7, which can be transcribed to produce a product with 992 bps. MNX1-AS1 has been reported to promote cell proliferation and invasion in many malignancies [21, 29–31]. The expression of MNX1-AS1 in osteosarcoma tissues was higher than that in adjacent tissues [32]. The expression of MNX1-AS1 in osteosarcoma tissues was higher than that in adjacent tissues. Liu et al. reported that the high expression of MNX1-AS1 in tumor tissue in non-small cell lung cancer is closely related to tumor TNM stage and lymph node metastasis [22]. In this study, sh-MNX1-AS1 suppressed cell proliferation and migration, while it accelerated apoptosis. Importantly, MNX1-AS1 accelerated tumorigenic ability in vivo. Thereby, the role of MNX1-AS1 in COAD could not be ignored. Consistent with previous report [31], MNX1-AS1 is upregulated in COAD. Moreover, they also found that MYC, a high-frequent amplified oncogene, binds to the promoter of MNX1-AS1 and activated its transcription [31]. Furthermore, sh-MNX1-AS1 decreased the levels of OCT4, CD33, CD133, and SOX2 in this study, indicating that sh-MNX1-AS1 suppressed the stemness of COAD stem cells. In recent years, somatic cell reprogramming, dedifferentiation, and pluripotent stem cell origin have become the focus of stem cell research [33, 34]. Oct4 and Sox2 are the key core regulators for maintaining pluripotency and self-renewal of stem cells [35]. They can not only regulate the expression of multiple genes related to maintaining pluripotency, self-renewal, and multidirectional differentiation, but also participate in signaling transduction and epigenetics [36]. In addition, CD133 (Prominin-l) is one of the typical TSC surface markers, which is expressed in breast cancer, kidney cancer, colorectal cancer, and other malignant tumors [37]. It is currently considered a recognized TSC cell marker. Besides, CD33 induces rapid phosphorylation of tyrosine motifs [38]. When it is stimulated by an exogenous protein kinase, the cytoplasmic tail will undergo tyrosine phosphorylation, and then the immunoreceptor tyrosine-related inhibitory motif (ITIM) acts as a cell membrane molecule to transmit inhibitory signal into the cell. In this study, the expression of OCT4, CD33, CD133, and SOX2 were all inhibited by sh-MNX1-AS1 transfection, indicating that sh-MNX1-AS1 inhibited the stemness of COAD cells. Moreover, the results in this study also confirmed that MNX1-AS1 targets and positively regulates PPFIA4. In previous studies, PPFIA4 was confirmed to enhance colorectal cancer glycolysis, which in turn promotes cell proliferation and migration [17] Li et al. [39] performed a comprehensive integration of metastatic colorectal cancer (mCRC) genomics, proteomics, and phosphoproteomics and referred that the PPFIA4 gene has a higher mutation frequency in CCRC. It was worth noting that PPFIA4 mediates MNX1-AS1 and affects COAD cell stemness in this study. Sh-PPFIA4 suppressed proliferation and migration, while it accelerated apoptosis of tumor cells. MNX1-AS1/PPFIA4 accelerated tumor growth in COAD model. LncRNA MNX1-AS1/PPFIA4 acted as a promoting factor of COAD through the AKT/HIF-1α pathway. The active region of Akt protein induces conformational changes by regulating the binding of Akt to PI-3, 4, 5-P3 [40]. Apoptosis of tumor cells includes two pathways, p53-dependent and p53-independent [41]. Some studies suggested that hypoxia-induced apoptosis worked through a HIF-1α-mediated 53-dependent pathway [42, 43]. HIF-1α provides energy to tumor cells, thereby enhancing tumor cell viability [44]. In pancreatic, colon, and breast cancer, HIF-1α was positively correlated with proliferating cell nuclear antigen [45–47]. Similar results were also obtained in this study. P-AKT/AKT and HIF1α expressed at a high level in MNX1-AS1 and PPFI4A groups, while they were lowest in LY20994 group. The result indicated that MNX1-AS1/PPFIA4 was involved in AKT/HIF-1α signaling pathway. Importantly, LY29004 significantly inhibited the tumorigenic ability of lncRNA MNX1-AS1 and PPFIA4 in vivo. In conclusion, lncRNA MNX1-AS1/PPFIA4 activated AKT/HIF-1α signaling pathway to promote stemness of COAD cells, which could be a new target for COAD treatment. | true | true | true |
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PMC9550509 | Yuehong Wang,Zhilian Wang,Keyan Cheng,Qirong Hao | FAM201A Promotes Cervical Cancer Progression and Metastasis through miR-1271-5p/Flotillin-1 Axis Targeting-Induced Wnt/β-Catenin Pathway | 03-10-2022 | This study investigated the role of the family with sequence similarity 201-member A (FAM201A), as previously reported oncogenic, in cervical cancer (CC). FAM201A expression in CC was analyzed through bioinformatics analyses, and its distribution in CC tissues/cells was determined by in situ hybridization. CC cells were transfected/cotransfected with FAM201A/flotillin-1 (FLOT1) overexpression plasmids and miR-1271-5p mimics, followed by functional analysis on viability, migration and invasion. Pearson's correlation tests were performed to analyze the correlation between FAM201A and miR-1271-5p in CC tissues. The targeting relationship between miR-1271-5p and FLOT1 was confirmed by dual-luciferase reporter assay. The expressions of FAM201A, miR-1271-5p, FLOT1, matrix metalloproteinases (MMP)-9, MMP-2, E-cadherin, N-cadherin, and the Wnt/β-catenin pathway-related molecules (Wnt1, β-catenin and p-β-catenin) in CC cells or tissues were assessed by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and/or western blot. The results showed that FAM201A was abundantly expressed and miR-1271-5p expression was downregulated in CC. FAM201A was enriched in CC cell cytoplasm and negatively correlated with miR-1271-5p in CC tissues. FAM201A overexpression enhanced the cell viability, migration, invasion, and tumorigenesis of CC in vivo and increased FLOT1 expression. These trends were all reversed by upregulating miR-1271-5p, which induced opposite effects to FAM201A overexpression. MiR-1271-5p upregulation depleted the levels of MMP-9, MMP-2, N-cadherin, and the Wnt/β-catenin pathway-related molecules and upregulated E-cadherin expression. FLOT1 was a direct target of miR-1271-5p. FLOT1 overexpression induced effects contrary to the upregulation of miR-1271-5p and abolished miR-1271-5p upregulation-induced effects in CC cells. Overall, this study showed that FAM201A promoted cervical cancer progression and metastasis by targeting the miR-1271-5p/FLOT1 axis-induced Wnt/β-catenin pathway. | FAM201A Promotes Cervical Cancer Progression and Metastasis through miR-1271-5p/Flotillin-1 Axis Targeting-Induced Wnt/β-Catenin Pathway
This study investigated the role of the family with sequence similarity 201-member A (FAM201A), as previously reported oncogenic, in cervical cancer (CC). FAM201A expression in CC was analyzed through bioinformatics analyses, and its distribution in CC tissues/cells was determined by in situ hybridization. CC cells were transfected/cotransfected with FAM201A/flotillin-1 (FLOT1) overexpression plasmids and miR-1271-5p mimics, followed by functional analysis on viability, migration and invasion. Pearson's correlation tests were performed to analyze the correlation between FAM201A and miR-1271-5p in CC tissues. The targeting relationship between miR-1271-5p and FLOT1 was confirmed by dual-luciferase reporter assay. The expressions of FAM201A, miR-1271-5p, FLOT1, matrix metalloproteinases (MMP)-9, MMP-2, E-cadherin, N-cadherin, and the Wnt/β-catenin pathway-related molecules (Wnt1, β-catenin and p-β-catenin) in CC cells or tissues were assessed by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and/or western blot. The results showed that FAM201A was abundantly expressed and miR-1271-5p expression was downregulated in CC. FAM201A was enriched in CC cell cytoplasm and negatively correlated with miR-1271-5p in CC tissues. FAM201A overexpression enhanced the cell viability, migration, invasion, and tumorigenesis of CC in vivo and increased FLOT1 expression. These trends were all reversed by upregulating miR-1271-5p, which induced opposite effects to FAM201A overexpression. MiR-1271-5p upregulation depleted the levels of MMP-9, MMP-2, N-cadherin, and the Wnt/β-catenin pathway-related molecules and upregulated E-cadherin expression. FLOT1 was a direct target of miR-1271-5p. FLOT1 overexpression induced effects contrary to the upregulation of miR-1271-5p and abolished miR-1271-5p upregulation-induced effects in CC cells. Overall, this study showed that FAM201A promoted cervical cancer progression and metastasis by targeting the miR-1271-5p/FLOT1 axis-induced Wnt/β-catenin pathway.
Cervical cancer (CC) is one of the most common malignant tumors affecting women worldwide, second to breast cancer [1], and is the leading cause of cancer-related mortality in some developing countries [2]. The progression of CC is featured as a multistage and multistep process involving the activation of proto-oncogenes and (or) inhibiting tumor-suppressive genes [3]. Currently, the antitumor treatment for CC remains less effective owing to its late-appearing symptom, leading to unsuccessful disease diagnoses and advanced-stage disease by the time of diagnosis [4]. It is reported that the five-year survival rate for metastatic CC patients is 16.5%, compared to 91.5% for localized CC patients [5]. Therefore, metastasis is accountable for most unfavorable prognoses, recurrence and high morbidity of CC [6]. Long noncoding RNAs (lncRNAs), a type of transcripts constituted by over 200 nucleotides with no translation ability, have emerged as pivotal regulators for the carcinogenesis and progression of cancers, including CC [6]. Epithelial-mesenchymal transition (EMT), a highly conserved trans-differentiation program considered the major driver of cancer progression, is reported to facilitate metastasis of cancer cells by promoting migration and invasion and conferring an apoptosis-resistant property [7]. By directly or indirectly reversing EMT, lncRNAs can repress tumorigenesis, cancer progression, and metastasis, demonstrating their therapeutic potential [8]. The family with sequence similarity 201-member A (FAM201A) is a long nonprotein coding RNA derived from an open reading frame (ORF)-lacking RNA transcripts transcribed from a 2.9 Kbp-long gene that is located in genomic 9p13.1 [9]. Several studies exploring anticancer strategies have revealed the involvement of FAM201A in inducing carcinogenesis and promoting the progression of triple-negative breast cancer (TNBC) [10], lung squamous cell cancer (LSCC) [11], and lung adenocarcinoma (LUAD) [12]. Additionally, highly expressed FAM201A was reported to provoke short-term radio-resistance, leading to inferior survival in patients with esophageal squamous cell cancer [13] and nonsmall-cell lung cancer [14]. However, little is known about the biological roles and clinical significance of FAM201A in CC. Interactive analyses have identified FAM201A as a key regulator in cancer progression in a lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network, via which FAM201A was found to indirectly regulate the expression of messenger RNA (mRNA) by sponging its targeted microRNAs (miRNAs) [10, 14, 15]. Without lncRNA-directed sponging effects, miRNAs, a class of small noncoding RNAs with 18-24 nucleotides in length that are endogenous and evolutionarily conserved, can destabilize mRNAs or inhibit translation, thereby repressing mRNA expression by complementarily binding to the 3'-untranslated regions of the mRNAs [16, 17]. A large number of miRNAs have been implicated in CC-associated ceRNA networks. For instance, MiR-1271-5p expression was previously reported to be aberrantly downregulated in acute myeloid leukemia [18], colon cancer [19], multiple myeloma [20], and LUAD [21], indicating that it played a tumor-suppressive role in the progression of these cancers through related ceRNA networks. Meanwhile, upregulated miR-1271-5p expression was shown to induce oncogenic effects and associated with unfavorable prognoses in hepatocellular carcinoma (HCC) [22]. However, whether FAM201A regulates miR-1271-5p through the ceRNA network and thus participates in CC progression remains unconfirmed. In this study, we investigated the effects of FAM201A in CC progression using bioinformatics tools and determined the potential miR-1271-5p-targeted mRNA for identifying a FAM201A-miR-1271-5p-mRNA ceRNA regulatory network in CC, with the hope to propose an original molecular therapy for CC.
Written informed consent was obtained from all human participants. All animal experiments were performed following the guidelines of the China Council on Animal Care and Use [23]. The human and animal studies were approved by the Ethics Committee and the Committee of Experimental Animals of Nanfang Hospital (approval number: GD202004020/GD202007027), respectively.
CC tissues (n = 33) and adjacent normal tissues () were collected during surgical operation at the Second Hospital of Shanxi Medical University in 2020 from CC patients without preoperative chemotherapy, radiotherapy, or immunotherapy. Fresh samples were immediately frozen in liquid nitrogen and stored at -80°C.
Human cervical endometrial epithelial cells (HCerEpiC; CP-H058, Procell Life Science&Technology Co., Ltd, Wuhan, China) were cultured in EpiLife Media (MEPI500CA, ThermoFisher, Waltham, MA, USA) to reach a confluence around 75% within 10–14 days. CC cell lines, including HeLa (CCL-2), C33a (HTB-31), SiHa (HTB-35), and ME180 (HTB-33) purchased from American Type Culture Collection (ATCC, Manassas, VA, USA), were cultivated in high-glucose Dulbecco's Modified Eagle Medium complete media (DMEM; 11965092, ThermoFisher, USA) supplemented with 2 mM L-glutamine (25030081, ThermoFisher, USA), 10% Fetal Bovine Serum (FBS; 16140071, ThermoFisher, USA), and 1% penicillin-streptomycin (V900929, Sigma-Aldrich, St. Louis, MO, USA) at 37°C with 5% CO2.
The expression and subcellular location of FAM201A were determined by General/Fluorescent in situ hybridization using Digoxigenin-labeled Probe Detection kits (Boster Biological Technology, Wuhan, China). As per the manufacturer's instructions, CC tissues and adjacent normal tissues were fixed in 4% paraformaldehyde (16005, Sigma-Aldrich, USA), dehydrated by ethanol, and transparentized by xylene (95682, Sigma-Aldrich, USA). Then, the tissues were embedded in paraffin (1496904, Sigma-Aldrich, USA) and cut into 4 μm-thick sections, following which the sections underwent dewaxation with xylene and rehydration by ethanol. SiHa and ME180 cells were cultured to reach a concentration of 1 × 105 cells/mL and fixed in 4% paraformaldehyde for 4 hours (h). Afterward, the sections and cells were treated with a standard prehybridization buffer at 68°C for 20 h. Digoxigenin-labeled DNA probes complementary to FAM201A were denaturalized via boiling water bath for 10 minutes (min) and added into the standard prehybridization buffer to formulate prehybridization buffer. The prehybridization buffer was then incubated with the tissues and cells at 68°C for another 20 h. After washing using Wash Solution I, a biotin-labeled anti-Digoxigenin antibody was added to the tissues, followed by the 3,3'-Diaminobenzidine (DAB) treatment for the color-development of the tissues. The cells were supplemented with anti-Digoxigenin antibody (ab420, Abcam, Cambridge, MA, USA) and incubated with Goat anti-mouse IgG H&L (ab150115, Abcam, USA). The nuclei of the cells were dyed using 4',6-diamidino-2-phenylindole (DAPI; D21490, ThermoFisher, USA). Color and fluorescent color signals were observed by a confocal microscope (Raman DXR™3, ThermoFisher, USA) at the magnification of ×200.
The pcDNA™3.1/Hygro(+) mammalian expression vectors were used to construct overexpression plasmids of FAM201A and FLOT1, and the empty vector was set as negative control (NC). MiR-1271-5p mimic/mimic control (MC) (miR10005796-1-5/miR1N0000001-1-5) was purchased from RIBOBIO (Guangzhou, China). C33a or ME180 cells (4 × 104) were seeded in 96 well plates until 80% confluence was reached. Transfection working solutions (0.15 μL) were prepared by mixing Lipofectamine 3000 transfection reagents (L3000015, ThermoFisher, USA) and Opti-MEM media (31985062, ThermoFisher, USA). Subsequently, the above plasmids were (2 μg) added into Opti-MEM media (10 μL) together with a P3000 reagent (0.4 μL). Next, the processed plasmids were mixed with the transfection working solution at a ratio of 1 : 1 to obtain an RNA-lipid complex, of which 10 μL of the complex mixture was incubated with the cells at 37°C for 24 h or 48 h.
The viability of SiHa or ME180 cells was evaluated using a CCK-8 kit (96992, Sigma-Aldrich, USA). After transfection with FAM201A/FLOT1 overexpression plasmids or miR-1271-5p mimic alone or in combination, SiHa or ME180 cells were seeded into 96-well plates at a density of l × l04 cells/well supplemented with complete media and cultured. The cells in each well were treated with the CCK-8 reagent (10 μL) and incubated for 4 h, at 24-, 48- and 72-h post-transfection. The optical density at a wavelength of 450 nm was determined by a microplate reader (ELx808, BioTek, Winooski, VT, USA).
The targeting relation between FLOT1 and miR-1271-5p was predicted by Targetscan (http://www.targetscan.org/vert_71/).
Dual-Luciferase Reporter Assay System (E1910, Promega, Madison, WI, USA) was used to verify the targeting relationships between FAM201A and miR-1271-5p and between miR-1271-5p and FLOT1. SiHa or ME180 cells (4 × 104) were then cultured to attain 70% confluence. Sequences of wild type FLOT1 (WT) (5′-CCCCTCATCUCTCCTTGCCAAAT-3′) and mutant FLOT1 (MUT) (5′-CCCCTCATCUCTCCTGGACAAAT-3′) were cloned onto pMirGLO luciferase vectors (50 ng, E1330, Promega, USA). The cells were cotransfected with the pMirGLO cloned with FLOT1-WT or FLOT1-MUT (2 μg) and miR-1271-5p mimic (2 μg) using Lipofectamine 3000 transfection reagent for 48 h. After cotransfection, the cells were lysed by diluted Lysis Buffer (50 μL, 16189, ThermoFisher, USA) and added with Luciferase Assay Reagent II (100 μL). The activity of firefly luciferase, which was normalized to that of Renilla luciferase, was measured using a luminometer (GloMax®20/20, Promega, USA).
Transwell chambers (3428, Corning, Corning, NY, USA) were used to assess the migratory and invasive abilities of SiHa cells and ME180 cells after transfection with FAM201A/FLOT1 overexpression plasmids or miR-1271-5p M alone or in combination. The upper chamber was precoated by Matrigel (dilution: 1 : 3; 356234, Corning, USA) for cell invasion assay, while that without Matrigel was used for cell migration assay. The cells were cultured to prepare a cell suspension at a concentration of 5 × 105 cells/ml. Then, 100 μL of the cell suspension was poured into the upper chamber, and 600 μL of DMEM containing 10% FBS was added to the lower chamber. The whole Transwell set was incubated at 37°C for 24 h. Later, the lower chamber was washed twice with phosphate-buffered saline (P5493, Sigma-Aldrich, USA), fixed with 4% paraformaldehyde (P6148 Sigma-Aldrich, USA) and stained with 800 μL Giemsa (10092013, ThermoFisher, USA). After removing nonmigratory or noninvading cells, the remaining cells were observed under × 200 magnification using an inverted microscope (IX71; Olympus, Tokyo, Japan). Cells in five randomly selected fields were counted using ImageJ software and cell migration and invasion rates were calculated.
BALB/c nude mice (Male, 5–6-week-old) were purchased from the Vital River Laboratories (Beijing, China). The mice were maintained under a specific condition (22~ 24°C, 50% humidity, a 12 h:12 h circadian cycle), with free access to a standard mice chow and water. Then, the mice were randomized into four groups (n = 6 per group): NC+MC group, FAM201A+MC group, NC+miR-1271-5p M group, and FAM201A+miR-1271-5p M group. After transfection, SiHa cells (5 × 106) with stable expressions of FAM201A, miR-1271-5p or both were subcutaneously injected into the posterior flank of the mice. The size of subcutaneous xenografts (length and width) was measured by a caliper every 7 days, with 5 times in total, and the volume of the xenografts was calculated according to the formula: 0.5 × length × width2. Five weeks after the injection, the mice were sacrificed via spinal dislocation under anesthetization using pentobarbital sodium (P010, Sigma-Aldrich, USA), following which the subcutaneous xenografts were resected and weighed.
Total mRNAs and miRNAs from CC cell lines and HCerEpiC, as well as CC tissues and the adjacent normal tissues, were extracted by TRIzol lysis buffer (15596018, ThermoFisher) and Small RNA kits (9753Q, TaKaRa, Liaoning, China), respectively. Chloroform (48520-U, Sigma-Aldrich, USA) was used to extract the lysate of mRNA and miRNA. The extracted lysate was centrifuged (12000 × g) at 4°C for 15 min. Then, isopropanol (W292907, Sigma-Aldrich, USA) was applied to precipitate the lysate from water layers via centrifugation (12000 × g) at 4°C for 10 min, which was then washed with 75% ethanol (32205, Sigma-Aldrich, USA) and then isolated from the supernatant. Next, it was resuspended and centrifugated (7500 × g) at 4°C for 10 min and dissolved in 20 μL diethyl pyrocarbonate (DEPC; 40718, Sigma-Aldrich, USA). First-strand cDNAs of the isolated mRNA and miRNA were synthesized using a Synthesis Kit (K1621, ThermoFisher, USA). qPCR was performed on an Applied Biosystems 7500 FAST real-time PCR machine (Applied Biosystems, Foster City, CA, USA) with TB Green® Premix Ex Taq II (Tli RNaseH Plus, RR820Q, TAKARA, China). The primers used are shown in Table 1. The thermocycling conditions were set as follows: 95°C for 10 min, followed by 40 cycles of 95°C for 15 s, and 60°C for 1 min. The expressions of relative genes normalized to U6 or GAPDH were calculated using the 2−ΔΔCT method [24].
RIPA Lysis and Extraction Buffer (89901, ThermoFisher, USA) was used to harvest total protein from SiHa cells and ME180 cells. The protein concentration was quantitated by the bicinchoninic acid (BCA) Protein Assay Kits (23227, ThermoFisher, USA). The protein (40 μg) and marker (4 μL) (PR1910, Solarbio, Beijing, China) were separated by 10%-12% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels (P0670, P0672, Beyotime, Shanghai, China) and laid onto polyvinylidene fluoride (PVDF) membranes (FFP28, Beyotime, China). Afterward, the membranes were blocked with 5% skim milk in Tris Buffered Saline and Tween 20 (TA-999-TT, ThermoFisher, USA) at room temperature for 1 h. Primary antibodies against FLOT1 (ab133497, 47 kDa, 1 : 10000, Abcam, USA), matrix metalloproteinase (MMP)-9 (ab73734, 78 kDa, 1 : 1000, Abcam, USA), MMP-2 (ab37150, 72 kDa, 1 : 1000, Abcam, USA), E-cadherin (ab40772, 97 kDa, 1 : 10000, Abcam, USA), N-cadherin (ab18203, 130 kDa, 1 μg/ml, Abcam, USA), Wnt1 (ab15251, 41 kDa, 1 : 1000, Abcam, USA), β-catenin (ab16051, 95 kDa, 1 : 1000, Abcam, USA), p-β-catenin (ab27798, 92 kDa, 1 : 500, Abcam, USA), and GAPDH (ab8245, 36 kDa, 1 : 1000, Abcam, USA) were incubated with the membranes at 4°C overnight. Then, secondary antibodies, including Goat Anti-Rabbit IgG (ab205718, 1 : 2000, Abcam, USA) and Goat Anti-Mouse IgG (ab6789, 1 : 2000, Abcam, USA), were incubated with the membranes. The obtained protein was photo-developed using Enhanced Chemiluminescent (ECL) Substrate Reagent Kit (WP20005, ThermoFisher, USA) on an imaging system (iBright CL1500, ThermoFisher, USA). Analysis of the gray value of protein bands was conducted using the ImageJ software (version. 1.52 s, National Institutes of Health, Bethesda, MA, USA).
Measurement data with normal distribution were expressed as mean ± standard deviation (SD). All the experiments were conducted in triplicate. SPSS software (version 21.0, SPSS Inc., Chicago, IL, USA) was used for statistical analysis. The differences between CC tissues and the adjacent normal tissues were analyzed by paired t-test. Comparison between the other two groups was performed by independent t-test, and those between multiple groups were conducted by one-way analysis of variance (ANOVA) followed by Dunnett's or Turkey's post-hoc test. Pearson's correlation tests were used to analyze the correlation between FAM201A and miR-1271-5p in CC tissues. Statistics with P < 0.05 were considered statistically significant.
According to Gene Expression Profiling Interactive Analysis (GEPIA) based on Cancer Genome Atlas Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (TCGA-CESC) database, FAM201A expression level was higher in CC tissues than that in normal tissues (P < 0.05; Figure 1(a)). Then, we harvested 33 pairs of clinical samples including CC tissues and the adjacent normal tissues for the examination of FAM201A expression. The results showed that FAM201A was highly expressed in CC tissues compared with adjacent normal tissues (Figure 1(b)). Considering that miR-1271-5p has been widely reported as a regulator of tumor growth, in this present study, miR-1271-5p expression was downregulated CC clinical samples and compared with adjacent normal tissues (Figure 1(c)), which showed a negative correlation between miR-1271-5p and lncRNA FAM201A via Pearson's correlation analysis (Figure 1(d)). Meanwhile, fluorescence in situ hybridization assay confirmed that FAM201A was highly expressed in CC tissues compared with adjacent normal tissues (Figure 1(e)). Moreover, in comparison with HCerEpiC, FAM201A expression level was also highly expressed in CC (HeLa, C33a, SiHa, and ME180) cells, while miR-1271-5p expression was decreased (P < 0.01; Figures 1(f) and 1(g)). A relatively higher expression level of FAM201A was seen in SiHa cells and ME180 cells than in other cells above. Therefore, to investigate the role of FAM201A during the progression of CC, SiHa cells and ME180 cells were chosen as cell models in the following related experiments to achieve obvious overexpression of FAM201A. Subsequently, qRT-PCR and fluorescent in situ hybridization were performed to determine the subcellular localization of FAM201A. As shown in Figures 1(h) and 1(i) (qRT-PCR) and Figures 1(j) and 1(k) (fluorescent in situ hybridization), FAM201A was abundantly expressed in the cytoplasm rather than in the nucleus, suggesting a role of FAM201A in post-transcriptional regulation.
Here, functional experiments, including CCK-8, qRT-PCR, Transwell, and murine xenograft assays, were performed. Prior to these assays, the transfection efficiency of FAM201A overexpression plasmids and miR-1271-5p mimic was validated by qRT-PCR, through which we observed that the transfection of both FAM201A overexpression plasmid and miR-1271-5p mimic induced the upregulation of FAM201A and miR-1271-5p expression, respectively (P < 0.001; Figures 2(a) and 2(c)). Moreover, upregulation of miR-1271-5p via miR-1271-5p mimic decreased the level of FAM201A, and likewise, FAM201A overexpression caused a lower level of miR-1271-5p (P < 0.05; Figures 2(a)–2(d)). Meanwhile, FAM201A overexpression plasmid and miR-1271-5p mimic counteracted the effect of each other on the expressions of FAM201A and miR-1271-5p (P < 0.001; Figures 2(a)–2(d)). Then, assays for FAM201A functional examination were performed. CCK-8 assay revealed that FAM201A overexpression enhanced the viability of CC cells at 24, 48, and 72 h, while miR-1271-5p upregulation decreased the viability of CC cells at 24, 48, and 72 h (P < 0.05) (Figures 2(e) and 2(f)). Transwell assay demonstrated that CC cells transfected with FAM201A overexpression plasmid migrated and invaded to a greater extent, while the transfection with miR-1271-5p mimic led to repressed migration and invasion (P < 0.01; Figures 2(g)–2(i) and 3(a)–3(c)). In murine xenograft assay, the increased trends of tumor volumes and weight gain were found under the promotion of FAM201A overexpression but inhibited by miR-1271-5p upregulation (P < 0.05; Figures 3(e)–3(f)). FAM201A overexpression and miR-1271-5p upregulation mutually reversed the effects of each other (Figures 2(e)–2(i) and 3(a)–3(f)). Taken together, the above results suggested that FAM201A-directed sponging of miR-1271-5p was associated with CC progression.
Prediction using StarBase displayed the complementary binding sites of miR-1271-5p and FLOT1 (Figure 4(a)). Dual-luciferase reporter assay showed that transfection of miR-1271-5p mimic suppressed the luciferase activity of CC cells transfected with vectors inserted with FLOT1-WT (P < 0.001), but exerted no obvious effects on the luciferase activity of CC cells transfected with vectors inserted with FLOT1-MUT (Figures 4(b) and 4(c)). Furthermore, FLOT1 expression was found to be upregulated by FAM201A overexpression, but the mRNA and protein levels were knocked down by miR-1271-5p upregulation compared with those in the NC+MC group (P < 0.05; Figures 4(d)–4(g)). Also, FAM201A overexpression reversed the miR-1271-5p upregulation-induced FLOT1 knockdown (P < 0.01). This trend was further offset by miR-1271-5p upregulation (P < 0.001; Figures 4(d)–4(g)). We observed that no obvious change on miR-1271-5p expression in CC cells after transfection with FLOT1 overexpression plasmid (Figures 5(a) and 5(b)), but CC cells transfected with miR-1271-5p mimic still increased miR-1271-5p expression in cells transfected with the plasmid overexpressing FLOT1 (P < 0.001; Figures 5(a) and 5(b)). In addition, compared with miR-1271-5p mimic control, miR-1271-5p upregulation decreased FLOT1 mRNA and protein expressions in negative control-transfected and FLOT1 overexpression plasmid-transfected CC cells, while FLOT1 overexpression plasmid demonstrated the opposite results (P < 0.05). Moreover, the effects of miR-1271-5p upregulation and FLOT1 overexpression plasmid were mutually counteractive (P < 0.05; Figures 5(c)–5(f)).
The miRNA-mRNA networks are widely known to regulate CC progression [25]. Here, as FLOT1 was identified as a target mRNA of miR-1271-5p, we investigated FLOT1-miR-1271-5p network-delivered regulation on CC cell phenotypes. The results showed that CC cells transfected with plasmid overexpressing FLOT1 exhibited increased viability at 48 h and 72 h (P < 0.05; Figures 6(a) and 6(b)) and more aggressive migration and invasion (P < 0.001; Figures 6(c)–6(h)). Additionally, FLOT1 overexpression could counteract miR-1271-5p upregulation-induced effects on the viability of CC cells at 48 h and 72 h (P < 0.05), together with their migration and invasion (P < 0.05); in turn, miR-1271-5p upregulation also reversed the effects of FLOT1 overexpression on the viability at 48 h and 72 h, migration and invasion of CC cells (P < 0.05; Figures 6(a)–6(h)). EMT, a biological process, displays distinctive cellular phenotypes and plays vital roles in both cell growth and cancer progression [26]. Thus, the protein and mRNA levels of EMT-related markers were assessed by western blot and qRT-PCR. Both the protein and mRNA levels of MMP-9, MMP-2, and N-cadherin were upregulated by FLOT1 overexpression in CC cells compared with those in the NC+MC group (P < 0.05), while compared with those in the NC+MC group, miR-1271-5p upregulation depleted the expressions of these markers (P < 0.01) and abolished the FLOT1 overexpression-induced effects on the expressions of these markers (P < 0.05) (Figures 7(a)–7(e)). Additionally, the effects of miR-1271-5p upregulation on these EMT-related markers were counteracted by FLOT1 overexpression (P < 0.05) (Figures 1(f) and 7(a)). Conversely, E-cadherin, an EMT-related marker, and its protein and mRNA levels were downregulated by FLOT1 overexpression but elevated by miR-1271-5p upregulation (P < 0.05), compared with those in the NC + MC group (Figures 8(a)–8(f)). Furthermore, FLOT1 overexpression counteracted the effects of miR-1271-5p upregulation on E-cadherin expression, and miR-1271-5p upregulation also reversed the effects of FLOT1 overexpression (P < 0.05) (Figures 8(a)–8(f)). Collectively, these results indicated that FAM201A sponged miR-1271-5p to induce FLOT1 expression, thereby promoting CC progression.
The Wnt/β-catenin signaling pathway, a developmental pathway, is crucial in normal stem cell function and is frequently aberrantly activated in various types of cancer [27–29]. In this research study, the protein and mRNA levels of Wnt1, β-catenin and p-β-catenin were determined by western blot and qRT-PCR assays. The result showed they were uniformly upregulated by FLOT1 overexpression but downregulated by miR-1271-5p upregulation (P < 0.001), compared with those in the NC+MC group (Figures 8(a)–8(e) and 8(g)–8(h)). Moreover, when compared with the NC+MC group, the p-β-catenin/β-catenin ratio was also depleted by miR-1271-5p upregulation in CC cells but not significantly changed by FLOT1 overexpression (P < 0.01) (Figures 8(g) and 8(h)). Besides, FLOT1 overexpression resisted the miR-1271-5p upregulation-induced inhibitory effect in the protein and mRNA expressions of Wnt1 and β-catenin (P < 0.01). It also increased the p-β-catenin/β-catenin ratio in CC cells transfected with miR-1271-5p mimic and the increase in these markers expression levels by FLOT1 overexpression were reversed by miR-1271-5p upregulation (P < 0.01) (Figures 8(a)–8(e) and 8(g)–8(h)). Overall, these results indicated that FAM201A overexpression-mediated miR-1271-5p/FLOT1 axis promoted CC progression by activating the Wnt/β-catenin signaling pathway.
In 2003, the World Health Organization considered CC preventable in women [20]. However, due to metastasis, the median survival time of CC patients remains mediocre [30]. Metastasis is a distinctive malignant sign that can be subdivided into two types, hematogenous metastasis and lymphatic metastasis [6, 31], of which lymph metastasis is the leading factor for CC-associated poor prognosis and death [32]. Metastasis in most human cancers implicates both cellular and molecular alterations [33], identifying that the molecular mechanism in CC is very important for hindering the development of metastasis and other malignant phenotypes. LncRNA-mediated mechanisms have been widely unveiled in the carcinogenesis, progression, and therapy resistance of CC [34]. Numerous lncRNAs, including FAM201A, have been confirmed to function as an oncogene in multiple types of human cancers by suppressing malignant phenotypes such as cancer cell proliferation, migration, invasion, and in vivo tumorigenesis [10–12]. In line with these studies, our study newly identified FAM201A as a key player in promoting CC carcinogenesis and progression. Analysis of the TCGA-CESC database showed that FAM201A was highly expressed in CC. To increase the credibility of this study's results, CC tissues and cell lines (HeLa, C33a, SiHa, and ME180) were used to assess FAM201A expression. We detected a unanimous increase in FAM201A expression in all CC in vitro and in vivo samples, which was consistent with the FAM201A expression patterns in TNBC and lung cancer, where FAM201A played oncogenic roles [10–12]. The specific tumor-promoting role of FAM201A was illustrated in previous studies, which reported that knocking down FAM201A led to significantly suppressed proliferation, migration, and invasion of TNBC or LSCC cells [10–12]. In line with the role of FAM201A in TNBC and LSCC, our study discovered a positive association between FAM201A overexpression and the biological behaviors of CC, including cell viability, migration, invasion, and in vivo tumorigenesis, which suggested that this oncogenic role of FAM201A also existed in CC. Functional analyses of FAM201A-miRNA-mRNA ceRNA networks indicated that FAM201A could sponge miRNAs and unleash mRNAs from the binding of FAM201A, with miRNAs critical for the promotion of cancer progression [10]. Our study found that miR-1271-5p was negatively correlated with FAM201A in CC tissues, implying that FAM201A sponged miR-1271-5p in CC. Previous studies reported that miR-1271-5p expression was significantly downregulated and miR-1271-5p exerted a tumor-suppressive effect in several cancers [18, 35]. Preventing oncogene-directed sponging of miR-1271-5p led to the inhibition of cancer progression, as evidenced by Zhang et al. [35], who found that miR-1271-5p upregulation from the knockdown of lncRNA-ZFAS1 constrained in vitro development of glioma. In light of Zhang et al.'s evidence, our findings demonstrated that miR-1271-5p upregulation reversed the promotive effect of FAM201A overexpression on the progression of CC, suggesting that FAM201A facilitated the progression of CC by sponging miR-1271-5p. Furthermore, it was reported that miRNA-mRNA interaction emerged following the interaction between lncRNA and miRNA in ceRNA networks associated with the pathological conditions in cancer [36]. Wang et al. showed that the upregulation of miR-1271-5p by MALAT1 knockdown inhibited the growth and migration of ovarian cancer cells and simultaneously silenced its target mRNA E2F5 [37]. In our study, bioinformatics prediction theoretically identified FLOT1 as the target of miR-1271-5p, which was subsequently validated by our dual-luciferase reporter assay results. Similarly, our findings showed that FAM201A overexpression downregulated miR-1271-5p expression to elevate FLOT1 expression and concomitantly promoted in vitro CC progression, indicating that the overexpressed FAM201A-directed ceRNA network with the miR-1271-5p/FLOT1 axis promoted CC progression. FLOT1, a pivotal marker of lipid rafts that modulates membrane receptor signaling, has been reported to participate in membrane trafficking and affect cell adhesion and invasion, thereby displaying a role in tumorigenesis [38, 39]. The overexpression of FLOT1 has been previously discovered to promote migration and invasion and induce recurrence of bladder transitional cell carcinoma [38], activate oncogenic ALK signaling to drive malignant phenotypes of neuroblastoma [40], and sustain inflammatory signaling to facilitate the growth and invasion of esophageal squamous cell carcinoma cells [40, 41]. For CC, FLOT1 was shown to serve as the downstream target of miR-1294 to form a miR-1294/FLOT1 axis, and its expression can be repressed by the upregulation of miR-1294, thereby inhibiting the progression of CC malignant phenotypes [42, 43]. Likewise, in our in vitro experiments, miR-1271-5p upregulation decreased FLOT1 expression and offset FLOT1 overexpression-induced promotion. Meanwhile, FLOT1 overexpression could also counteract the inhibitory effects of miR-1271-5p upregulation on cell viability, migration and invasion. According to these findings, we concluded that targeting the miR-1271-5p/FLOT1 axis could be the underlying mechanism via which FAM201A induced CC progression. Accumulating evidence indicated that EMT, a hallmark of carcinogenesis, functionally contributed to tumor invasion, migration and metastatic dissemination [44]. The phenotype of EMT mainly involves the transformation of epithelial cells to mesenchymal-like cells, allowing them to invade surrounding tissues [45, 46]. Induction of EMT is accompanied by the loss of epithelial adhesion molecule E-cadherin [47] and an increase in mesenchymal marker N-cadherin [48]. Moreover, during EMT, MMPs, a family of zinc-dependent endoproteases, degrade the extracellular matrix to facilitate EMT [49]. Secretion of MMP-2 and MMP-9 was shown to break down the basement membrane and promote lymph node invasion and cancer metastasis, thus leading to poor prognoses [50, 51]. In this study, we found that E-cadherin levels in CC cells were decreased by FLOT1 overexpression but increased by miR-1271-5p upregulation, and an opposite trend was seen on the levels of N-cadherin, MMP-2, and MMP-9 when FLOT1 was overexpressed or miR-1271-5p expression was upregulated. Besides, we discovered that FLOT1 overexpression counteracted miR-1271-5p upregulation-induced effects on the expressions of these EMT-related markers and vice versa. Collectively, these findings indicated that FAM201A facilitated EMT and promoted CC progression by targeting the miR-1271-5p/FLOT1 axis. The Wnt/β-catenin pathway, which plays an essential role in embryogenesis, homeostasis, and stem cell regeneration and pluripotency, is activated in CC as a promoter of cancer progression [52, 53]. Likewise, our results demonstrated that the levels of Wnt1, β-catenin and p-β-catenin in CC cells were positively correlated with FLOT1 overexpression, while the levels of these markers were negatively correlated with miR-1271-5p upregulation. Besides, our study revealed that FLOT1 overexpression could also restore the expressions of Wnt1, β-catenin, and p-β-catenin in CC cells after the upregulation of miR-1271-5p, which indicated that FLOT1 overexpression counteracted the inhibitory effects induced by miR-1271-5p upregulation on the Wnt/β-catenin pathway, thus promoting the progression of CC. Considering that FAM201A was overexpressed in CC cells and acted through the FAM201A-miR-1271-5p-FLOT1 ceRNA network, they might be targeted and used to develop novel potential molecular target to improve CC treatment outcomes, with FAM201A as a potential diagnostic biomarker for CC and possible indicator of FAM201A-targeted treatment for individualized treatment of patients expressing high levels of FAM201A. However, considering limitations such as lack of survival analysis, no assessment to determine the association of FAM201A with pharmacological treatment, and others, these findings should be further verified in translational and clinical studies.
In conclusion, the current study revealed that FAM201A, which was highly expressed in CC, promoted CC progression via sponging miR-1271-5p to upregulate FLOT1 expression. Moreover, CC progression was also promoted via regulating the miR-1271-5p/FLOT1 axis by activating the Wnt/β-catenin pathway. Thus, this study proposed the FAM201A-miR-1271-5p-FLOT1 ceRNA network as an original molecular target for prevention against CC. | true | true | true |
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PMC9551088 | Tian-Chen Xiong,Ming-Cong Wei,Fang-Xu Li,Miao Shi,Hu Gan,Zhen Tang,Hong-Peng Dong,Tianzi Liuyu,Pu Gao,Bo Zhong,Zhi-Dong Zhang,Dandan Lin | The E3 ubiquitin ligase ARIH1 promotes antiviral immunity and autoimmunity by inducing mono-ISGylation and oligomerization of cGAS | 10-10-2022 | Pattern recognition receptors,Autoimmunity,Inflammation,Innate immunity | The cytosolic DNA sensor cyclic GMP-AMP synthase (cGAS) plays a critical role in antiviral immunity and autoimmunity. The activity and stability of cGAS are fine-tuned by post-translational modifications. Here, we show that ariadne RBR E3 ubiquitin protein ligase 1 (ARIH1) catalyzes the mono-ISGylation and induces the oligomerization of cGAS, thereby promoting antiviral immunity and autoimmunity. Knockdown or knockout of ARIH1 significantly inhibits herpes simplex virus 1 (HSV-1)- or cytoplasmic DNA-induced expression of type I interferons (IFNs) and proinflammatory cytokines. Consistently, tamoxifen-treated ER-Cre;Arih1fl/fl mice and Lyz2-Cre; Arih1fl/fl mice are hypersensitive to HSV-1 infection compared with the controls. In addition, deletion of ARIH1 in myeloid cells alleviates the autoimmune phenotypes and completely rescues the autoimmune lethality caused by TREX1 deficiency. Mechanistically, HSV-1- or cytosolic DNA-induced oligomerization and activation of cGAS are potentiated by ISGylation at its K187 residue, which is catalyzed by ARIH1. Our findings thus reveal an important role of ARIH1 in innate antiviral and autoimmune responses and provide insight into the post-translational regulation of cGAS. | The E3 ubiquitin ligase ARIH1 promotes antiviral immunity and autoimmunity by inducing mono-ISGylation and oligomerization of cGAS
The cytosolic DNA sensor cyclic GMP-AMP synthase (cGAS) plays a critical role in antiviral immunity and autoimmunity. The activity and stability of cGAS are fine-tuned by post-translational modifications. Here, we show that ariadne RBR E3 ubiquitin protein ligase 1 (ARIH1) catalyzes the mono-ISGylation and induces the oligomerization of cGAS, thereby promoting antiviral immunity and autoimmunity. Knockdown or knockout of ARIH1 significantly inhibits herpes simplex virus 1 (HSV-1)- or cytoplasmic DNA-induced expression of type I interferons (IFNs) and proinflammatory cytokines. Consistently, tamoxifen-treated ER-Cre;Arih1fl/fl mice and Lyz2-Cre; Arih1fl/fl mice are hypersensitive to HSV-1 infection compared with the controls. In addition, deletion of ARIH1 in myeloid cells alleviates the autoimmune phenotypes and completely rescues the autoimmune lethality caused by TREX1 deficiency. Mechanistically, HSV-1- or cytosolic DNA-induced oligomerization and activation of cGAS are potentiated by ISGylation at its K187 residue, which is catalyzed by ARIH1. Our findings thus reveal an important role of ARIH1 in innate antiviral and autoimmune responses and provide insight into the post-translational regulation of cGAS.
The innate immune system detects viral nucleic acids through pattern-recognition receptors (PRRs) including RIG-I-like receptors, Toll-like receptors (TLRs), and cytosolic DNA sensors to initiate antiviral immune responses. To date, multiple cytoplasmic DNA sensors have been identified, among which the cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) synthase (cGAS) is universally required for the recognition of viral DNA in distinct types of cells and thus serves as a major DNA sensor in the cytoplasm. Upon binding to DNA, cGAS is activated through conformational transitions, resulting in the formation of a catalytically competent and an accessible nucleotide-binding pocket for ATP and GTP. Structural and biochemical analyses have revealed that the binding of cGAS to DNA promotes cGAS oligomerization—a hallmark of cGAS activation—and efficiently catalyzes the conversion of ATP and GTP into cGAMP. Subsequently, cGAMP binds to and activates the adaptor protein mediator of IRF3 activation (MITA, also known as STING and ERIS), which induces the expression of an array of downstream genes including type I interferons (IFNs) and proinflammatory cytokines to elicit cellular antiviral immune responses. Consistently, cGAS deficiency abolishes the production of cGAMP and type I IFNs after HSV-1 infection and cytoplasmic DNA challenge, and mice deficient in cGAS are hypersensitive to HSV-1 infection. In addition to viral DNAs, cGAS also recognizes and is activated by self DNA derived from mitochondrial DNA (mtDNA) and endogenous retroelements-derived DNA. Such self-DNA molecules are normally degraded by multiple cytoplasmic DNase, including three prime repair exonuclease 1 (TREX1) and DNase II. Loss-of-function mutations of TREX1 and DNase II have been reported to be highly connected with autoimmune diseases such as Aicardi-Goutieres syndrome, systemic lupus erythematosus, and retinal vasculopathy with cerebral leukodystrophy in humans. Similarly, mice deficient in DNase II or TREX1 or mice carrying the loss-of-function TREX1 (Trex1D18N/D18N) produce overwhelming type I IFNs and ISGs and exhibit systemic lethal autoimmune phenotypes. Notably, these autoimmune phenotypes are fully eliminated by depletion of cGAS, suggesting an indispensable role of cGAS in autoimmune diseases triggered by self-DNA. Therefore, elucidating the regulatory mechanisms for cGAS activation would provide insight into the understanding of antiviral immunity and autoimmunity. Post-translational modifications such as ubiquitination and ubiquitin-like modifications have been reported to tightly control the activity and stability of cGAS and finely tune cGAS-mediated immune responses. TTLL4 and TTLL6 catalyze glutamylation of cGAS to impede the DNA binding activity and synthase activity of cGAS, which is relieved by CCP5- and CCP6-mediated deglutamylation. Mono-ubiquitination of cGAS mediated by E3 ubiquitin ligases RINCK and TRIM56 and K27-linked polyubiquitination of cGAS catalyzed by RNF185 have been shown to promote the synthesis of cGAMP and the expression of downstream genes after HSV-1 infection. In addition, an unknown E3 ubiquitin ligase constitutively catalyzes K48-linked ubiquitination of cGAS and promotes its degradation through the proteasome-dependent pathway in the resting cells and after HSV-1 infection, which is counteracted by the deubiquitinating enzyme USP29. Consequently, knockout of USP29 results in downregulation of cGAS in cells and organs that impairs antiviral immune responses and rescues autoimmune lethality caused by TREX1 deficiency. A recent study has shown that the E3 ubiquitin ligase TRIM38 targets cGAS for SUMOylation, which suppresses the K48-linked polyubiquitination of cGAS in a manner of physical hindrance and stabilizes cGAS in resting cells and early phase of HSV-1-infected cells. More recently, it has been reported that RNF111 mediates NEDDylation of cGAS, which leads to the dimerization and subsequent activation of cGAS. Such SUMOylation and NEDDylation of cGAS indicate that ubiquitin-like modifications regulate the activity and stability of cGAS. ISG15 is an IFN-inducible protein composed of two ubiquitin-like domains linked by a short hinge region and unconjugated ISG15 can regulate viral replication and host antiviral responses through non-covalent protein-protein interactions and its action as a cytokine. In addition, the mature ISG15 protein bares a C-terminal LRLRGG motif that can be covalently conjugated to the lysine residues of substrates by a three-step process known as ISGylation involving ubiquitin-activating enzyme E1 homolog (UBE1L, also known as UBA7), E2 (UBCH8, also known as UBE2L6), and E3 ligases. Mice lacking UBE1L exhibit hypersensitivity to viral infections. Isg15−/− mice are more susceptible to viral infections, which can be rescued by expressing wild-type ISG15, but not a mutant form of ISG15 that cannot form conjugates, from the virus genome. Similar to ubiquitination, ISGylation is a reversible process and counteracted by USP18. Consistently, USP18C61A/C61A knock-in mice (in which the deconjugating activity of USP18 is disrupted) exhibit elevated ISGylation and increased viral resistance, which is completely reversed by additional deletion of ISG15, indicating that ISGylation of substrates inhibits viral infections and promotes antiviral immunity. Proteomic studies have identified hundreds of host proteins that are ISGylated upon interferon stimulation. However, only a subset of proteins has been validated for ISGylation that has been investigated in the context of viral infections. For example, ISGylation of IRF3, STAT1, and PKR promote their stability or activity to increase the production of type I IFNs and ISGs, whereas ISG15 modification of RIG-I promotes its degradation to turn down cellular antiviral responses. Whether and how cGAS undergoes ISGylation to regulate antiviral immunity and autoimmunity are completely unknown. Ariadne RBR E3 ubiquitin protein ligase 1 (ARIH1, also known as HHARI) is a RING-between-RING (RBR)-type ubiquitin E3 ligase that associates with two E2 ubiquitin-conjugating enzymes UBCH7 and UBCH8. Early studies have shown that ARIH1 induces ubiquitination and ISGylation of the translation initiation factor 4E homologous protein (4EHP) in the presence of UBCH7 and UBCH8, respectively, suggesting that ARIH1 possesses dual catalytic activities in the presence of different E2 enzymes. Interestingly, recent structural analyses suggest that ARIH1 is a component of Cullin-RING ligases (CRLs) and forms a unique E3-E3 platform with Cullin-associated RBX1, and thereby preferentially catalyzes mono-ubiquitination of diverse substrates presented on various substrate receptors (such as F-box proteins and BTB proteins). Specifically, the NEDD8-Cullin-RBX1 complex activates auto-inhibited ARIH1 and the UBCH7-conjugated ubiquitin is firstly transferred to ARIH1 and then to the lysine residues of substrates. Subsequently, the substrates either leave the CRL complex or undergo further ubiquitination on the mono-ubiquitinated lysine residues by CRLs. However, whether and how ARIH1 mediates ISGylation of substrates through CRLs remain to be investigated. In this study, we identified ARIH1 as a cGAS-interacting E3 ubiquitin ligase that mediates mono-ISGylation of cGAS and promotes its oligomerization after HSV-1 infection. Knockout or knockdown of ARIH1 attenuates cellular antiviral responses against HSV-1 and knockout of ARIH1 leads to hypersensitivity to HSV-1 infection and alleviates the autoimmune phenotypes in Trex1−/− mice. Mechanistically, ARIH1 directly catalyzes mono-ISGylation at K187 of cGAS in vitro and in cells after HSV-1 infection, which relieves K187-mediated inhibitory effects on the oligomerization of cGAS. These findings highlight a regulatory mechanism of cGAS activation mediated by ARIH1 and provide potential targets for viral infection-caused diseases and autoimmune disorders.
cGAS is a cytosolic DNA sensor that critically mediates antiviral immunity and autoimmunity. The activity and stability of cGAS are strictly controlled by various posttranslational modifications. To identify cGAS-interacting E3 ligases that potentially regulate the modifications and functions of cGAS, we performed yeast-two hybrid screening with pGBT9-cGAS and ~200 pGADT7-E3 constructs in AH109 cells. This effort led to the identification of ARIH1 (also known as HHARI) as a cGAS-interacting E3 in yeast cells (Fig. 1a). Results from transient transfection and co-immunoprecipitation assays suggested that ARIH1 selectively interacted with cGAS but not with other proteins including RIG-I, MAVS, MITA, TBK1, or IRF3 in HEK293 cells (Fig. 1b). We next examined the endogenous association between cGAS and ARIH1 and found that cGAS interacted with ARIH1 constitutively in primary murine lung fibroblasts (MLFs) and bone marrow-derived dendritic cells (BMDCs) (Fig. 1c). The association between cGAS and ARIH1 was substantiated at early time points and then impaired at late time points after HSV-1 infection (Fig. 1c). In addition, results from Glutathione S-transferase (GST) pulldown assays revealed a direct interaction between the GST-tagged ARIH1 purified from bacteria and FLAG-cGAS obtained from an in vitro transcription and translation kit (Fig. 1d). Domain mapping analysis showed that multiple domains except for the N-terminal UBA domain of ARIH1 interacted with cGAS, while the C-terminal domain of cGAS (aa151-552) interacted with ARIH1 in HEK293 cells (Fig. 1e, f). Together, these data suggest that ARIH1 interacts with cGAS directly and constitutively under homeostatic conditions and after HSV-1 infection.
ARIH1 is a component of the CRL system and regulates cancer progression and xenophagy of cytosolic bacteria. Since ARIH1 interacts with cGAS that mediates innate antiviral responses, we investigated the role of ARIH1 in HSV-1- or cytoplasmic DNA-triggered immune signaling. We designed two shRNAs targeting ARIH1, both of which downregulated the protein levels of endogenous ARIH1 in HEK293 cells (Supplementary Fig. 1a). In addition, both of the shRNAs inhibited cGAS plus MITA- but not MITA-mediated activation of the ISRE enhancer in luciferase reporter assays in HEK293 cells (Supplementary Fig. 1b). We next chose shARIH1#1 for subsequent experiments and found that knockdown of ARIH1 significantly impaired HSV-1-induced expression of IFNB, ISG56, CCL5 and IP10 in THP-1 cells (Supplementary Fig. 1c). In addition, knockdown of ARIH1 substantially inhibited the expression of IFNB, ISG15, CCL5, and IP10 after transfection of various DNA, but barely affected cGAMP-induced expression of IFNB, IL6, CCL5, ISG15, and IP10 (Supplementary Fig. 1d, e). Consistent with these observations, HSV-1- but not cytoplasmic cGAMP-induced phosphorylation of IRF3, TBK1, and p65 was impaired by knockdown of ARIH1 in THP-1 cells (Supplementary Fig. 1f). These data together suggest that ARIH1 positively regulates DNA virus- or cytoplasmic DNA-triggered innate immune signaling at the level of cGAS.
The C. elegans ARI1s (homolog of human ARIH1) has been implicated in fertility and oogenesis during development. Germline knockout of ARIH1 in mice might affect the development and growth of mice. To further investigate the role of ARIH1 in antiviral immune responses in vivo, we generated Arih1fl/+ mice by CRISPR/Cas9- mediated genome editing (Supplementary Fig. 2a). Results from Southern blot analysis indicated that the targeting vector was successfully recombined with the wild-type allele (Supplementary Fig. 2b). Cre recombinase-mediated deletion of the exon 3 between flanking loxp sites would lead to early translational termination of ARIH1 to generate a 165 amino-acid peptide or result in Arih1 mRNA instability (Supplementary Fig. 2c, d). The Arih1fl/+ mice were then crossed with Lyz2-Cre mice to obtain the Lyz2-Cre;Arih1fl/fl mice. The differentiation of Lyz2-Cre;Arih1fl/fl bone marrow cells into BMDCs and BMDMs was similar to the Arih1fl/fl counterparts in the presence of GM-CSF and M-CSF cultures, respectively (Supplementary Fig. 2e). The number and composition of lymphocytes in multiple organs including thymus, inguinal lymph nodes, and spleen were comparable between the Lyz2-Cre Arih1fl/fl mice and the Arih1fl/fl mice (Supplementary Fig. 2f–h). In addition, the percentages and numbers of myeloid CD11b+ and CD11c+ populations in spleen from Lyz2-Cre;Arih1fl/fl mice were similar to those from Arih1fl/fl mice (Supplementary Fig. 2h). Together, these results suggest that ARIH1 in myeloid cells is dispensable for the in vitro differentiation of BMDCs and BMDMs and the in vivo development and homeostasis of various immune cells. We next examined the effect of ARIH1 deficiency on HSV-1- or cytoplasmic DNA-triggered signaling in primary murine BMDCs. We found that knockout of ARIH1 significantly impaired HSV-1- or cytoplasmic DNA- but not SeV-, poly(I:C)-, or cGAMP-induced expression of Ifnb, Il6, and Ip10 and production of IFN-β and IL-6 in BMDCs (Fig. 2a–c). Consistently, HSV-1- but not SeV-induced phosphorylation of TBK1, IRF3, and p65 was substantially inhibited in the Lyz2-Cre;Arih1fl/fl BMDCs compared to the Arih1fl/fl BMDCs (Fig. 2d), suggesting that ARIH1 selectively promotes HSV-1- and cytoplasmic DNA-triggered cGAS-dependent innate immune signaling. The virus-triggered expression of downstream genes plays a critical role in restricting the replication of viruses. Consistent with this notion, the replication of H129-G4 (a GFP-tagged HSV-1) and HSV-1 was significantly potentiated in Lyz2-Cre;Arih1fl/fl BMDCs compared to Arih1fl/fl BMDCs as revealed by the GFP signals determined by flow cytometry and fluorescent microscopy analyses, the expression levels of HSV-1 UL30 gene determined by qRT-PCR assays, and the HSV-1 titers in the supernatants determined by plaque assays (Fig. 2e, f). These data suggested that ARIH1 is required for optimal antiviral immune responses to restrict HSV-1 replication in myeloid cells. We also obtained ROSA26-CreERT2 (here referred to as Cre-ER) Arih1fl/fl mice by crossing the Arih1fl/fl mice and Cre-ER mice. Intraperitoneal injection of tamoxifen led to efficient deletion of ARIH1 in various organs including brain, lung, heart, and liver (Supplementary Fig. 3a), suggesting that the strategy to knockout Arih1 in mice is reliable and successful. Then we prepared the primary murine lung fibroblasts (MLFs) from Cre-ER;Arih1fl/fl and Cre-ER mice and treated these cells with 4-hydroxytamoxifen (4-OHT) followed by HSV-1 infection or transfection of various ligands. Results from qRT-PCR and ELISA assays revealed that HSV-1- or cytoplasmic DNA- but not SeV-, cytoplasmic poly(I:C)-, or cGAMP-induced expression of Ifnb, Ifna4 or Ccl5 and production of IFN-β and IL-6 were significantly lower in Cre-ER;Arih1fl/fl MLFs than in Cre-ER MLFs (Supplementary Fig. 3b, d). Consistently, HSV-1- but not SeV-induced phosphorylation of TBK1, IRF3, and p65 was markedly decreased in the Cre-ER;Arih1fl/fl MLFs compared to the Cre-ER MLFs (Supplementary Fig. 3e). As expected, the replication of H129-G4 and HSV-1 was potentiated in Cre-ER;Arih1fl/fl MLFs compared to Cre-ER MLFs (Supplementary Fig. 3f, g). Collectively, these data demonstrate that ARIH1 promotes cellular antiviral responses against HSV-1 in various types of primary murine cells.
We next examined the physiological role of ARIH1 in defense against HSV-1 infection in mice. The Cre-ER;Arih1fl/fl mice and the Cre-ER mice were intraperitoneally injected with tamoxifen (80 mg/kg body weight) for five successive days, and 5 days later the mice were infected with sub-lethal HSV-1 (1 × 107 PFU per mouse) via intraperitoneal (i.p.) route or HSV-1 (1 × 106 PFU per mouse) via intracranial (i.c.) route. As shown in Fig. 3a, the Cre-ER;Arih1fl/fl mice started to die at day 3 after HSV-1 infection and all the mice died at day 6 after HSV-1 infection. In contrast, the Cre-ER mice started to die at the fourth day after HSV-1 infection and 4 out of 7 mice survived at day 8 after HSV-1 infection (Fig. 3a). Moreover, the concentrations of IFN-β and IL-6 were significantly lower in the sera of Cre-ER;Arih1fl/fl mice than in Cre-ER mice at 12 h after HSV-1 infection (Fig. 3b). The levels of Ifnb and Ccl5 were decreased and the levels of HSV-1 UL30 gene were increased in the spleen or brain of Cre-ER;Arih1fl/fl mice compared to Cre-ER mice at day 3 after HSV-1 infection (Fig. 3c, d). In addition, the HSV-1 titers in the spleen or brain of Cre-ER;Arih1fl/fl mice were higher than in the spleen or brain of Cre-ER mice at day 3 after HSV-1 infection (Fig. 3e). Hematoxylin-eosin staining analysis of brain tissues showed that there were fewer infiltrated cells in the brains of Cre-ER;Arih1fl/fl mice than in the brains of control mice after HSV-1 infection (Fig. 3f). Similarly, deletion of ARIH1 by Lyz2-Cre led to increased susceptibility to sub-lethal HSV-1 infection (Fig. 3g), inhibited the production of IFN-β and IL-6 in the sera (Fig. 3h), and impaired the expression of Ifnb and Ccl5 in the spleen or brain (Fig. 3i, j). Consistently, the levels of HSV-1 UL30 gene and the HSV-1 titers in the spleen or brain of Lyz2-Cre;Arih1fl/fl mice were significantly higher than those of Arih1fl/fl mice (Fig. 3i–k). Finally, the infiltrated cells in the brains of Lyz2-Cre;Arih1fl/fl mice were fewer than in the brains of their littermates after HSV-1 infection (Fig. 3l). Together, these data suggest that ARIH1 is required for optimal antiviral immune responses in mice.
Since the Cys357 of ARIH1 is the active site for ligase activity, we investigated whether re-introduction of ARIH1C357S into ARIH1-deficient cells would restore the cellular antiviral responses. The Cre-ER;Arih1fl/fl MLFs were transfected with an empty vector (Vec), ARIH1 or ARIH1C357S followed by 4-OHT treatment and HSV-1 infection or transfection of various DNA. Results from qRT-PCR analyses suggested that reconstitution of wild-type ARIH1 but not ARIH1C357S into Cre-ER Arih1fl/fl MLFs restored- HSV-1- or cytoplasmic DNA-induced expression of Ifnb, Il6 and Isg56 (Supplementary Fig. 4a, b). In addition, the production of IFN-β and IL-6 in the supernatants and the phosphorylation of IRF3, TBK1, or p65 in cells were rescued by reconstitution of ARIH1 but not ARIH1C357S (Supplementary Fig. 4c, d). Consistent with this notion, the replication of H129-G4 or HSV-1 was significantly inhibited in Cre-ER;Arih1f/f MLFs reconstituted with ARIH1 but not with ARIH1C357S as revealed by the GFP signals determined by flow cytometry and fluorescent microscopy imaging analyses, the expression levels of HSV-1 UL30 gene determined by qPCR analysis, and the HSV-1 titers in the supernatants determined by plaque assays (Supplementary Fig. 4e, f). These data together suggest that ARIH1 promotes cellular antiviral responses dependently on its enzyme activity.
Because knockout of ARIH1 inhibited cytoplasmic DNA- but not the cGAMP-induced expression of type I IFNs and inflammatory genes in BMDCs or MLFs (Fig. 2b, c and Supplementary Fig. 3b, c), we reasoned that ARIH1 promoted cellular antiviral immune responses at the level of cGAS. To test this hypothesis, we performed the cGAMP activity assay by stimulating human foreskin fibroblasts (HFFs) or NCTC clone 929 clone of strain L (L929) mouse fibroblasts with the heat-resistant homogenates of ARIH1-sufficient or deficient cells that were transfected with DNA (Fig. 4a). Results from qRT-PCR analysis suggested that the homogenates from Cre-ER;Arih1fl/fl MLFs that were transfected with DNA120 failed to induce expression of IFNB, TNFA and ISG56 in HFF cells compared to those from Cre-ER MLFs (Fig. 4b). Similarly, the homogenates from DNA120-transfected Arih1fl/fl BMDCs induced significantly higher expression of Ifnb, Ifna4 and Ip10 in L929 cells than those from DNA120-transfected Lyz2-Cre;Arih1fl/fl BMDCs (Fig. 4c), indicating that knockout of ARIH1 compromises the cGAMP production in cells after transfection of DNA. In addition, the cGAMP activity was restored by reconstitution of ARIH1 but not ARIH1C357S into 4-OHT-treated Cre-ER;Arih1fl/fl MLFs (Fig. 4d). These data are consistent with the observations that reconstitution of ARIH1 but not ARIH1C357S into ARIH1-deficient cells restored cytoplasmic DNA-induced expression of downstream genes (Supplementary Fig. 4a–c). Collectively, these data indicate that ARIH1 facilitates cGAS-mediated cGAMP production after cytoplasmic DNA stimulation. Previous studies have demonstrated that HSV-1 infection or cytoplasmic DNA stimulation induces oligomerization of cGAS which represents a critical step for the activation of cGAS and the production of cGAMP. Interestingly, we found that the HSV-1-induced oligomerization of cGAS was substantially impaired by knockdown of ARIH1 in THP-1 cells or by knockout of ARIH1 in MLFs (Fig. 4e). In addition, reconstitution of ARIH1 but not ARIH1C357S into 4-OHT-treated Cre-ER;Arih1fl/fl MLFs restored the oligomerization of cGAS after HSV-1 infection (Fig. 4e). Taken together, these data suggest that ARIH1 facilitates the oligomerization of cGAS and cGAS-mediated cGAMP production in cells after cytoplasmic DNA challenge or HSV-1 infection.
In addition to viral DNA, self-DNA accumulated in cytosol activates cGAS to induce autoimmunity. Knockout or dysfunction of TREX1 leads to the accumulation of DNA in the cytosol and causes severe autoimmune symptoms that can be eliminated by ablation of cGAS. Since ARIH1 facilitated the activation and oligomerization of cGAS after cytoplasmic DNA challenge, we examined whether knockout of ARIH1 inhibited the autoimmune phenotypes in TREX1-deficient cells and mice. We obtained the Lyz2-Cre;Arih1fl/fl Trex1−/− mice by crossing Lyz2-Cre Arih1fl/fl mice with Trex1+/− mice and isolated the bone marrow cells from the mice for in vitro culture. Results from qRT-PCR analyses showed that the expression levels of Ifnb, Isg15, Isg56, and Ccl5 in BMDCs and BMDMs from Lyz2-Cre;Arih1fl/flTrex1−/− mice were significantly lower than those from the Trex1−/− counterparts, and were comparable to those from the wild-type counterparts (Fig. 5a). Consistently, the cGAMP activity was significantly decreased in Lyz2-Cre;Arih1fl/flTrex1−/− BMDCs and BMDMs compared to Trex1−/− counterparts (Supplementary Fig. 4g), suggesting that deletion of ARIH1 in Trex1−/− cells normalizes the basal expression of IFN-stimulated genes and the basal production of cGAMP. In addition, knockout of ARIH1 in myeloid cells in Trex1−/− background rescued the developmental retardation of Trex1−/− mice (Fig. 5b). Expectedly, knockout of ARIH1 in myeloid cells fully rescued the autoimmune lethality caused by TREX1 deficiency, suggesting that ARIH1 in myeloid cells sufficiently supports autoimmunity caused by dysfunction of TREX1 (Fig. 5c). In this context, it has been shown that TREX1 deficiency in DCs or Cx3cr1+ tissue macrophages is sufficient to trigger spontaneous IFN responses and autoimmune lethal phenotypes. We next analyzed the autoimmune phenotypes in various organs or tissues of Trex1−/− mice and Lyz2-Cre;Arih1fl/flTrex1−/− mice. Firstly, we observed that the sizes of spleens were significantly smaller, and the percentages and the numbers of GL7+FAS+ B cells and CD8+CD44+CD62L− T cells were substantially less in the spleens from Lyz2-Cre;Arih1fl/flTrex1−/− mice than those from Trex1−/− mice (Fig. 5d, e). Secondly, the expression levels of Isg15, Isg56, and Ccl5 in the kidney and liver of Lyz2-Cre;Arih1fl/flTrex1−/− mice were significantly lower than those of Trex1−/− mice (Fig. 5f). Thirdly, the infiltration of immune cells into the liver, heart or lung of Lyz2-Cre;Arih1fl/flTrex1−/− mice were substantially compromised compared to Trex1−/− mice as revealed by HE-staining analysis (Fig. 5g). Lastly, the levels of TNF, CXCL1, CCL5, and total IgG were significantly lower in the sera from Lyz2-Cre;Arih1fl/flTrex1−/− mice than those from Trex1−/− mice (Fig. 5h). Taken together, these data demonstrate that ARIH1 promotes self-DNA-triggered autoimmunity.
It has been reported that ARIH1 is a component of the human cullin-RING E3 ligases (CRLs) and could efficiently catalyze mono-ubiquitination of substrates dependently on the NEDDylation of CRL. Considering that ARIH1 interacts with cGAS and promotes cGAS activation dependently on its enzymatic activity, we examined whether ARIH1 catalyzed ubiquitination of cGAS. Unexpectedly, ARIH1 did not induce obvious ubiquitination of cGAS (Supplementary Fig. 5a). Previous studies have reported that cGAS undergoes NEDDylation and SUMOylation. However, neither ARIH1 nor ARIH1C357S affected the NEDDylation or SUMOylation in HEK293 cells in our transient transfection and denature-IP assays (Supplementary Fig. 5b, c). In addition to serving as a ubiquitin ligase, ARIH1 has been suggested as an ISG15 ligase to catalyze ISGylation of 4EHP, an mRNA 5′ cap structure-binding protein. Interestingly, we found that ARIH1 but not ARIH1C357S catalyzed robust mono-ISGylation of cGAS in HEK293 cells (Fig. 6a and Supplementary Fig. 5d). Moreover, cGAS was basally ISGylated in the presence of ISGylation machinery including UBE1L, UBCH8, and ISG15, which was substantially impaired by knockdown of ARIH1, indicating that endogenous ARIH1 mediates mono-ISGylation of cGAS in HEK293 cells (Supplementary Fig. 5e). As a component of CRLs, the ubiquitin ligase activity is activated by NEDD8 activating enzyme (NAE)-mediated NEDDylation on cullin proteins that is inhibited by the compound MLN4924. Interestingly, however, MLN4924 treatment did not affect ARIH1-mediated mono-ISGylation of cGAS in HEK293 cells (Supplementary Fig. 5f), supporting the notion that the ISG15 ligase activity but not the ubiquitin ligase activity of ARIH1 catalyzes the modification of cGAS. Results from in vitro ISGylation assays further confirmed that ARIH1 but not ARIH1C357S catalyzed mono-ISGylation of cGAS (Fig. 6b). In contrast, HSV-1 infection induced mono-ISGylaiton of cGAS which was completely diminished by knockout of ARIH1 (Fig. 6c). In addition, transfection of ARIH1 into 4OHT-treated Cre-ER;Arih1fl/fl MLFs increased the mono-ISGylation of cGAS after HSV-1 infection and promoted cGAMP activity after transfection of DNA120 in a dose-dependent manner (Fig. 6d, e). These data together suggest that ARIH1 serves as a primary ISG15 ligase E3 for mono-ISGylation of cGAS after HSV-1 infection.
We next identified the lysine residue(s) in cGAS to which ISG15 was attached by ARIH1 through liquid chromatography-mass spectrometry (LC-MS) assays (Supplementary Fig. 6a). These efforts led to the identification of the peptide “DDISTAAGMVK(GG)GVVDHLLLR”, indicating that the Lys187 of cGAS was modified by the Gly-Gly peptide (Supplementary Fig. 6a). We generated FLAG-cGASK187R mutant and found that mutation of Lys187 to arginine abolished ARIH1-mediated mono-ISGylation of cGAS in HEK293 cells or in vitro (Fig. 6f, and Supplementary Fig. 6b). In addition, HSV-1 induced mono-ISGylation of cGAS but not cGASK187R when reconstituted into cGas−/− MEFs (Supplementary Fig. 6c), indicating that Lys187 is the ISGylated site of cGAS after HSV-1 infection. Sequence alignment analysis indicated that the Lys173 residue of murine cGAS exhibited homology with the Lys187 residue of human cGAS (Supplementary Fig. 6d). Consistent with this notion, ARIH1 catalyzed mono-ISGylation of mcGAS but not mcGASK173N in HEK293 cells and in vitro (Fig. 6g and Supplementary Fig. 6d). In addition, HSV-1 induced mono-ISGylation of mcGAS but not mcGASK173N when reconstituted into cGas−/− MEFs (Fig. 6h). These data together demonstrate that ARIH1 catalyzes mono-ISGylation on Lys187 of hcGAS and Lys173 of mcGAS, respectively.
We next investigated whether and how mono-ISGylation of cGAS affected cGAS-mediated innate immune response against DNA viruses. The cGas−/− MEFs were stably transfected with an empty vector, cGAS or cGASK187R followed by HSV-1 infection and various analyses. Interestingly, however, we found that reconstituted cGASK187R significantly promotes HSV-1-induced expression of Ifnb, Ip10, and Ccl5 compared to wild-type cGAS (Fig. 7a). Similarly, reconstitution of mcGASK173N into cGas−/− MEFs led to higher levels of Ifnb, Ip10 and Cxcl1 than did wild-type mcGAS after HSV-1 infection (Supplementary Fig. 6e). In addition, reconstitution of cGASK187R into cGas−/− MEFs promoted HSV-1-induced phosphorylation of IRF3, TBK1 and p65 more profoundly than did reconstitution of wild-type cGAS (Fig. 7b). Consistent with these observations, the cGas−/− MEFs reconstituted with cGASK187R produced higher levels of cGAMP after transfection of DNA ligands and exhibited more intensive oligomerization and resulted in lower HSV-1 titers in the supernatants after HSV-1 infection than those reconstituted with wild-type cGAS (Fig. 7c–e), indicating that loss of mono-ISGylation of cGAS at K187 potentiates HSV-1-triggered signaling. The above data suggested that ARIH1 catalyzed mono-ISGylation of cGAS at K187 and mcGAS at K173 to promote antiviral immune responses, whereas cGASK187R and mcGASK173N that lost the mono-ISGylation also promoted cellular antiviral immunity, which prompted us to hypothesize that K187 of hcGAS and K173 of mcGAS might inhibit its optimal activity. To test this hypothesis, we further mutated K187 of cGAS into different amino-acid residues including polar uncharged serine (S) and glycine (G), polar negative-charged aspartic acid (D), or nonpolar phenylalanine (F). Results from luciferase reporter assays showed that all the mutants activated the IFN-β promoter and NF-κB reporter more potently than wild-type cGAS in HEK293 cells that were stably transfected MITA (Supplementary Fig. 7a). In addition, we stably transfected these mutants into cGas−/− MEFs followed by HSV-1 infection and various analyses. Results from qRT-PCR analyses suggested that the expression levels of Ip10, Ccl5 and Tnf in cGas−/− MEFs reconstituted with cGASK187S, cGASK187D, cGASK187G, or cGASK187F were significantly higher than those in cGas−/− MEFs reconstituted with wild-type cGAS (Supplementary Fig. 7b). Consistently, HSV-1-induced oligomerization of cGAS was substantially potentiated when the K187 was mutated into S, D, G, F, or R (Fig. 7c and Supplementary Fig. 7c) and when the K173 of mcGAS was mutated into N (Fig. 7c). These data indicate that K187 of cGAS and K173 of mcGAS inhibit the optimal activation and oligomerization of cGAS after HSV-1 infection or cytoplasmic DNA challenge.
We further analyzed the effects of ARIH1-mediated mono-ISGylation of cGAS on the oligomerization of cGAS in cells and found that ARIH1 but not ARIH1C357S induced oligomerization of cGAS in HEK293 cells that were transfected with cGAS and the ISGylation machinery (Fig. 7f). Next, we examined whether ISGylation of cGAS affected DNA-induced oligomerization of cGAS in vitro. GST-cGAS was incubated with the UBE1L, UBCH8, His-ISG15 and His-ARIH1 or His-ARIH1C357S followed by incubation with ISD45. The cGAS oligomers were determined by monitoring the migration of DNA in agarose gels and the migration of cGAS in SDD-AGE gels. As expected, ISD45 efficiently induced slowly migrating GST-cGAS-ISD45 complexes and cGAS oligomerization in the ARIH1C357S-containing reaction mixture where cGAS was not ISGylated (Fig. 7g). In contrast, the migration of GST-cGAS-ISD45 was substantially slowed, and notably most of the cGAS-DNA complexes were in the loading well and could not migrate into the agarose gel in the ARIH1-containing reaction mixture where cGAS was mono-ISGylated (Fig. 7g), supporting the notion that mono-ISGylation promotes oligomerization of cGAS. Furthermore, we observed that ISD45 induced the oligomerization of cGASK187R more potently than cGAS in vitro and that the cGASK187R-ISG15 complexes migrated much slower than the cGAS-ISG15 complexes in vitro (Fig. 7h). Taken together, these data indicate that K187 of cGAS inhibits DNA-induced oligomerization of cGAS, which is relieved by ARIH1-mediated mono-ISGylation on K187 of cGAS.
The activity and stability of the cytoplasmic DNA sensor cGAS are precisely regulated by various posttranslational modifications to initiate antiviral immunity and avoid harmful autoimmunity. In this study, we have demonstrated that the E3 ubiquitin ligase ARIH1 catalyzes mono-ISGylation of cGAS and promotes oligomerization and activation of cGAS after HSV-1 infection or DNA challenge, therefore promoting the expression of downstream type I IFNs and proinflammatory cytokines (Supplementary Fig. 7d). In support of this notion, we found that (i) ARIH1 interacts with cGAS and catalyzes mono-ISGylation on K187 of hcGAS and K173 of mcGas in cells or in vitro dependently on its ligase activity; (ii) knockdown or knockout of ARIH1 impaired HSV-1- and cytoplasmic DNA- but not cGAMP-induced phosphorylation of IRF3, TBK1 and p65 and production of type I IFNs and proinflammatory cytokines, inhibited HSV-1-induced oligomerization of cGAS, and attenuated cytoplasmic DNA-induced generation of cGAMP; and (iii) ARIH1-deficient mice and cells exhibited increased susceptibility to HSV-1 infection compared to the control counterparts and deletion of ARIH1 in myeloid cells rescued the autoimmune phenotypes in Trex1−/− mice. Collectively, these findings reveal a previously uncharacterized posttranslational modification of cGAS that promotes optimal activation of cGAS and cGAS-mediated antiviral immunity and autoimmunity. ISG15 is promptly upregulated by viral infection and type I IFNs. Previous studies have shown that Isg15−/− mice and Ube1l-/- mice are hypersensitive to HSV-1 infection compared to wild-type mice, while USP18C61A/C61A mice in which ISGylation is accumulated are resistant to Vaccinia virus infection, indicating a protective role of ISG15 and ISG15 conjugation in immune defense against DNA viruses. However, the key ISGylated targets in host remain to be characterized. In addition, ISG15 is one of the immediate-early genes induced by viral infections independently of type I IFNs and its roles in defense against viruses at an early stage are not fully understood. We found that ARIH1 catalyzed the conjugation of ISG15 to cGAS at early time points after HSV-1 infection, which promotes its activation and oligomerization and thereby facilitates innate immune responses against DNA viruses. Consistent with this notion, knockout of ARIH1 abolished HSV-1-induced mono-ISGylation of cGAS and resulted in hypersensitivity to HSV-1 infection. Although it is currently unknown whether there exist additional ISGylated targets of ARIH1 in the context of viral infection, the available data have suggested a positive feedback loop of cGAS ISGylation by ARIH1 to promote antiviral immunity. In contrast to an antiviral role of ISG15 in mice, patients deficient in ISG15 display autoinflammatory interferonopathies as a result of the impaired accumulation of USP18 which is a potent negative regulator of type I IFN signaling, indicating that a major function of human ISG15 is likely to attenuate type I IFN responses rather than to facilitate antiviral responses. However, it should be noted that ISG15-deficient patients are prone to mycobacterial disease. It is well recognized that cGAS is an indispensable sensor of Mycobacterium tuberculosis and mediates protective immune responses against mycobacterial infections. Therefore, the loss of mono-ISGylation of cGAS might be involved in mycobacterial disease of ISG15-deficient patients as a result of impaired activity of cGAS. It is of great interest to examine whether ARIH1-mediated mono-ISGylation of cGAS promotes immune responses against Mycobacterium tuberculosis infections in the future. It has been shown that ARIH1 is a component of CRLs and activated by NEDD8-Cullin-RBX1 complex to catalyze mono-ubiquitination of CRL substrates. Our data showed that ARIH1 catalyzed mono-ISGylation of cGAS independently of CRLs. Firstly, treatment of MLN4924 that inhibits NEDD8 conjugation to Cullin proteins and inactivates CRLs did not affect ARIH1-mediated mono-ISGylation of cGAS in HEK293 cells. Secondly, ARIH1 failed to increase the ubiquitination of cGAS in cells or in vitro. Thirdly, ARIH1 but not the enzymatic inactive mutant ARIH1C357S directly catalyzed mono-ISGylation of cGAS in the presence of UBE1L and UBCH8 as required for ISGylation and in the absence of CRLs and UBCH7 as required for mono-ubiquitination. These data have demonstrated that ARIH1 functions as an E3 ISG15 ligase for optimal activation of cGAS in the context of antiviral immunity and autoimmunity. Structural analyses suggest that the ARIH1 catalytic site (Cys357) is masked by its C-terminal Ariadne domain and that NEDD8-Cullin-RBX1 complex binds to ARIH1 and leads to conformational change and exposure of the active site of ARIH1. How the catalytic site Cys357 of ARIH1 was exposed for ISGylation during HSV-1 infection remained to be elucidated. One of the possibilities might be that the association of cGAS facilitates the conformational change as does the NEDD8-Cullin-RBX1 complex, as it was noted that the C-terminal Ariadne domain of ARIH1 interacted with cGAS in co-immunoprecipitation assays. A second possibility was that the E2 UBCH8 was required and sufficient for such a conformational change of ARIH1, which was supported by the observation that ARIH1 catalyzed ISGylation only in the presence of UBCH8. A third explanation for this was that the ISG15 ligase activity of ARIH1 might be regulated in a different manner. In this context, deletion of the C-terminal Ariadne domain of ARIH1 impairs its ability to catalyze ISGylation of another substrate 4EHP. Further structural studies with the purified ISGylation system together with substrates would help to understand the mechanisms for ARIH1 activation as an E3 ISG15 ligase. We have provided several lines of evidence that ISG15 was targeted on Lys187 of hcGAS and Lys173 of mcGAS. Analyses of MS data suggested that there was a Gly-Gly modification on K187 of cGAS only when cGAS was co-transfected and incubated with ARIH1, ISG15, UBE1L, and UBCH8 in HEK293 cells. Mutation of K187 or K173 completely abolished ARIH1-mediated ISGylation of hcGAS or mcGAS in vitro or in cells after HSV-1 infection, respectively. Structural analysis has suggested a DNA binding site (A site) at aa176-195 of hcGAS and aa147-181 of mcGAS in which K187 and K173 are located, respectively. However, mutation of multiple positive charged amino-acid residues in these regions into Ala has minimal effect on the DNA binding activity of cGAS, indicating that site A plays a minor role in regard of activating cGAS. In contrast, mutation of K187 and L195 into Asn and Arg enhances the DNA binding and oligomerization of cGAS in vitro. In our study, we found that mutation of hcGAS K187 into R, S, D, G, or F and mutation of mcGAS K173 into N substantially enhanced the oligomerization and activity of cGAS in cells after HSV-1 infection and in vitro in the presence of DNA. These data strongly indicate that K187 exerts an inhibitory effect on the activation and oligomerization of cGAS. Consequently, the mono-ISGylation on K187 of hcGAS and K173 of mcGAS blocked their inhibitory effects, thereby promoting the activation and oligomerization of cGAS in cells and in vitro. So far we do not know whether and how such a modification affects the DNA binding to cGAS, as we failed to purify enough amounts of ISGylated cGAS for in vitro DNA binding assays. It should be noted that in all the cGAS structures, cGAS proteins were crystallized as truncated forms that only include NTase and Mab21 domains. It is conceivable that additional regulatory machinery exists to regulate the DNA binding, oligomerization, and activation of full-length cGAS in cells and in vitro. In this context, it has been shown that the N terminus of hcGAS binds to DNA and facilitates the optimal activation of cGAS. A comprehensive understanding of the mechanisms by which ISGylation of cGAS on K187 promotes activation and oligomerization of cGAS depends on more detailed structural and functional analyses of full-length cGAS. Recent studies have revealed a suppressive role of ARIH1 in tumorigenesis. A more recent report has shown that ARIH1 catalyzes ubiquitination and degradation of PD-L1 and thereby promotes anti-tumor immunity and that the expression of ARIH1 is severely suppressed in lung adenocarcinoma biopsies. It has been reported that cytoplasmic cGAS activates innate immune signaling in response to DNA damage or genome instability in tumor cells and thereby promotes the activation of CD8+ T cells and the efficacy of immune checkpoint blockades therapies. It is of great interest to examine whether ARIH1 also exerts anti-tumor activity through promoting ISGylation and activation of cGAS. Collectively, our findings not only characterize a previously uncovered regulatory mechanism of cGAS activation but also provide potential targets for viral infection-caused diseases and autoimmune disorders.
The Arih1fl/+ mice were generated by GemPharmatech Co. Ltd through CRISPR/Cas9-mediated gene editing. In brief, guide RNAs (5′-GGCAGGAGCAGGCGAGCCCT-3′ and 5′-AAGTAAGTGATATAGCCCCC-3′) were obtained through in vitro transcription and purification. The gRNAs were incubated with purified Cas9 protein and injected into the fertilized eggs (at the one-cell stage) together with the targeting vector with two loxp sites flanking the exon 3 of the Arih1 gene. The injected fertilized eggs were cultured to the two-cell stage followed by transplantation into pseudopregnant mice. The targeted genomes of F0 mice were amplified by PCR and sequenced and the chimeras were crossed with wild-type C57BL/6 mice to obtain F1 Arih1fl/+ mice. Southern blot analysis was conducted with the tail DNA from F1 mice to confirm correct recombination and exclude random insertions of the targeting vector. Lyz2-Cre mice (B6/JNju-Lyz2em1Cin(iCre)/Nju, stock number: T003822) were purchased from the Nanjing Biomedical Research Institute of Nanjing University. Trex1+/− mice were described previously. Cre-ER mice (B6.129-Gt(ROSA)26Sortm1(cre/ERT2)Tyj, stock number: 008463) were from the Jackson Laboratory and kindly provided by Dr. Chen Dong (Tsinghua University). Arih1fl/+ mice were crossed with Cre-ER, Lyz2-Cre, or Trex1+/− mice to obtain Cre-ER;Arih1fl/fl, Lyz2-Cre;Arih1fl/fl, and Lyz2-Cre;Arih1fl/flTrex1−/− mice, respectively. All genetic models were on the C57BL/6 background. Mice including both sexes, between the ages of 5–8 weeks were used for all described experiments. 5-week old, gender-matched Trex1−/− and Lyz2-Cre;Arih1fl/flTrex1−/− mice were used for experiments. 6 to 8-week old, gender-matched mice were used for all remaining experiments. Mice genotypes were determined by PCR analysis of tail DNA, and the genotyping primers are as follows (wild-type Arih1 allele is of 280 bp; floxed allele is of 378 bp; positive Cre-ER is of 825 bp; positive Lyz2-Cre is of 1413 bp; positive Trex1 knockout allele is of 200 bp): Arih1 forward: 5′-TGCTAAGATACTTTAGACTGGGCC-3′, reverse: 5′-TGTTATCAGGAAATGGTGTACCAAG-3′; Cre-ER forward: 5′-AAAGTCGCTCTGAGTTGTTAT-3′, reverse: 5′-CCTGATCCTGGCAATTTCG-3′; Lyz2-Cre forward: 5′-AGTGCTGAAGTCCATAGATCGG-3′, reverse: 5′- GTCACTCACTGCTCCCCTGT-3′; Trex1 forward: 5′-AGGCAAATAAGTAGTGGA-3′, reverse: 5′-TCTCACTGGCCCCAGGGCTAC-3′.
To achieve conditional knockout of Arih1, 8–10-week-old Cre-ER and Cre-ER;Arih1fl/fl mice were injected intraperitoneally with tamoxifen (80 mg per kg body weight, dissolved in corn oil) (Sigma, #T5648) for 5 successive days. After 5 days rest, mice were either euthanized to test the knockout efficiency or infected with HSV-1. To delete ARIH1 in cultured cells, Cre-ER and Cre-ER;Arih1fl/fl cells were treated with 4-hydroxytamoxifen (4-OHT, 1 μM) (Sigma, H6278) for 3 days. Cells were then re-seeded into culture dishes or plated in 4-OHT-free medium and rested for 24 h followed by infection with HSV-1, SeV or transfection with dsDNA, poly(I:C) or cGAMP.
Poly(I:C) and dsDNA were described previously. MLN4924 (Pevonedistat, HY-70062) was purchased from MedChemExpress. H129-G4 was previously described and kindly provided by Dr. Min-Hua Luo (Wuhan Institute of Virology, Chinese Academy of Sciences). Recombinant mouse GM-CSF (500-P65) and mouse M-CSF (500-P62G) were purchased from PeproTech.). Information on the antibodies used in this study is included in Supplementary Table 1. Various reporter plasmids and Mammalian expression plasmids for SUMO1/2/3 and UBC9 were kindly provided by Drs. Ming-Ming Hu and Hong-Bing Shu. Mammalian expression plasmids for NEDD8 and NEDD8ΔGG were kindly provided by Dr. Ling-Qiang Zhang (Beijing Institute of Lifeomics). The cDNAs encoding human E3 ligases were amplified and cloned into the pGADT7 vectors. The plasmids for cGAS, MAVS, MITA, TBK1, IRF3, RIG-I, ubiquitin were previously described. Mammalian expression plasmids for ARIH1, ARIH1 mutants or truncations, cGAS mutants or truncations, ISG15, UBE1L, and UBCH8 were constructed by standard molecular biology techniques.
The pGBT9-cGAS vector and the individual pGADT7 vectors encoding E3s were transformed into AH109 competent cells which were grown on the Trp−Leu− medium plates at 30 °C for 2 days. The positive clones were transferred to the Ade−His−Trp−Leu− medium plates and cultured at 30 °C for 3–5 days. The positive clones were recognized as potential cGAS-interacting E3s.
HEK293 cells were transiently transfected with firefly luciferase reporter (100 ng) and TK-Renilla luciferase reporter (20 ng) and indicated plasmids or empty vector (100 ng) using standard calcium phosphate precipitation. After 24 h, luciferase assays were performed with a dual-specific luciferase reporter kit (Promega). The activity of firefly luciferase was normalized by that of Renilla luciferase to obtain relative luciferase activity.
Cells were cultured in plates or dishes for 24 h before being transfected with DNA ligands and poly(I:C) via PEI reagent (Polysciences Inc, 24765-1) according to the manufacturer’s instructions. Briefly, the ligands were diluted in serum-free DMEM (the volume of DMEM is 10% of final volume of cell culture medium) (1 μg ligands in 25 μl DMEM). PEI (1 μg/μl) was diluted in an equal volume of DMEM with a ratio of 3:1 [PEI (μl):ligands (μg)]. The PEI-containing DMEM was mixed with ligands-containing DMEM and incubated for 15 min at room temperature before adding into the cell cultures. For transfection of cGAMP, the cGAMP (1 μg/μl) and 10 × digitonin were diluted in DMEM (the volume of DMEM is 50% of the cell culture medium). The supernatants of cell cultures were removed and the cGAMP-containing DMEM was added to cell cultures. Half an hour later, the cGAMP-containing DMEM was removed and full medium was added to culture the cells for different time points followed by various assays. The oligonucleotide sequences of DNA ligands were included in Supplementary Table 2.
Cells were collected and lysed for 15 min with 800 μL Nonidet P-40 lysis buffer (20 mM Tris-HCl, pH 7.4–7.5, 150 mM NaCl, 1 mM EDTA, 1% Nonidet P-40) containing inhibitors for protease and phosphatases (TopScience). Cell lysates (700 μl) were incubated with a control IgG or specific antibodies and protein G agarose for 2–4 h. The immunoprecipitates were washed three times by 1 ml pre-lysis buffer and subject to immunoblot analysis. The rest of lysates (100 μl) were subject to immunoblot analysis to detect the expression of target proteins. All uncropped and unprocessed scans of the blots are provided in the Source Data file.
Cells were lysed in NP-40 lysis buffer, and the cell lysates were mixed in 1 × sample buffer (0.5 × TBE, 10% glycerol, 2% SDS, and 0.0025% bromophenol blue) and loaded onto a vertical 2% agarose gel (Bio-Rad). After electrophoresis in the running buffer (1 × TBE and 0.1% SDS) for about 2 h with a constant voltage of 100 V at 4 °C, the proteins were subject to immunoblot analysis.
The plasmids encoding GST, GST-ARIH1 and GST-cGAS or encoding His-ISG15, UBE1L, UBCH8, cGAS, cGASK187R, ARIH1, and ARIH1C357S were transformed into BL21(DE3) or Rosetta competent cells which were induced with IPTG (1 mM) at 16 °C at 200 rpm for 16 h. The cells were lysed in lysis buffer (20 mM Tris-HCl, 200 mM NaCl, 5% glycerol, and 0.3% Triton X-100) and the proteins were purified through affinity chromatography using a glutathione-Sepharose matrix (Transgen Biotech) followed by glutathione (10 mM in 50 mM Tris-HCl) elution (for GST-tagged proteins) or using Ni-NTA agarose followed by 300 mM imidazole elution (for His-tagged proteins) and dialysis. To obtain untagged proteins, His-tagged cGAS, ARIH1 or their mutants were incubated with His-TEV enzyme at 4oC overnight followed by purification by a Ni-NTA column. The untagged proteins were in the flow-through fluid and used for subsequent experiments. The recombinant proteins were saved at −80 °C until use. FLAG-cGAS proteins were expressed with TNT Quick Coupled Transcription/Translation Systems kit (Promega, Madison, WI) as the manufacturer’s instructions. For GST Pull-Down assay, the purified GST and GST-ARIH1 proteins were incubated with FLAG-cGAS at 4 °C for overnight followed by ProteinIso GST Resin (Transgen Biotech) pulldown for 2 h in PBS containing protease inhibitors. The GST resin was washed 3 times with PBS and subject to immunoblot analysis and Coomassie brilliant blue staining.
Cells cultured in 6 cm plates were transfected with the indicated plasmids. Twenty-four hours after transfection, cells from each plate were collected and divided into two aliquots. One aliquot was lysed in lysis buffer and analyzed by immunoblotting to examine the expression levels of transfected plasmids. The aliquot was lysed in buffer A (6 M guanidinium-HCl, 0.1 M Na2HPO4/NaH2PO4, 10 mM Tris-Cl pH 8.0, 5 mM imidazole, and 10 mM β-mercaptoethanol), and incubated with Ni2+-NTA beads (QIAGEN) for 4 h at room temperature or overnight at 4 °C. The beads were washed sequentially with buffers A, B (8 M urea, 0.1 M Na2PO4/NaH2PO4, 10 mM Tris-HCl pH 8.0, 10 mM β-mercaptoethanol), and C (same as B except pH 6.3). Beads with bound proteins were incubated in SDS loading buffer and heated at 95oC for 10 min followed by immunoblot analysis.
Cells were lysed in regular lysis buffer (100–200 μl) and the cell lysates were denatured at 95 °C for 5 min in the presence of 1% SDS. A portion of cell lysates (20 μl) were saved for immunoblot analysis to detect the expression of target proteins. The rest of cell lysates (80–180 μl) were diluted with 1–2 ml lysis buffer and immunoprecipitated (Denature-IP) with either anti-FLAG beads or with protein G (20 μl) plus anti-FLAG (0.5 μg) or anti-cGAS (1 μg). The immunoprecipitates were washed by three times and subject to immunoblot analysis.
GST-ARIH1, GST-cGAS, His-ISG15, hcGAS, hcGASK187R, mcGAS, mcGASK173N, ARIH1, and ARIH1C357S proteins were purified from bacteria. UBE1L (11990-H20B) and UBCH8 (BML-UW9135) were purchased from Sino Biological and Enzo Life Sciences, respectively. In vitro ISGylation reactions were performed at 37 oC for 2 h in 20 μL volume containing His-ISG15 (5 μg), UBE1L (0.2 μg), UBCH8 (0.5 μg), ARIH1 or ARIH1C357S (5 μg), cGAS or cGASK187R (5 μg), mcGAS or mcGASK173N (5 μg) in the reaction buffer (50 mM Tris-HCl pH 7.5, 5 mM Mg2+-ATP, and 2.5 mM DTT). The mix was fractionated by SDS-PAGE and analyzed by Coomassie brilliant blue staining.
Purified cGAS or cGAS mutants (3-9 μg) were incubated with 2 μM 45 bp dsDNA in the reaction buffer containing 20 mM HEPES-NaOH (pH 7.8), 1 mM DTT, 75 mM KCl at 4 °C for 30 min. Reactions were separated on a 2% agarose gel in 0.5 × TBE buffer at 4 °C followed by imaging with the G:BOX system. Alternatively, the reactions were loaded to SDD-AGE followed by immunoblot analysis. To examine the effect of cGAS mono-ISGylation on its oligomerization, GST-cGAS were incubated with UBE1L, UBCH8, His-ISG15 and ARIH1 or ARIH1C357S in the presence of 5 mM ATP. Subsequently, the mixtures were incubated with 45 bp dsDNA (ISD45) in reaction buffer at 4 °C for 30 min followed by electrophoresis on a 2% agarose gel in 0.5 × TBE buffer at 4 °C. Alternatively, the mixtures were loaded to SDD-AGE followed by immunoblot with anti-cGAS to determine the oligomerization of cGAS.
Total RNA was extracted from cells using TRIzol (Life Technologies), and the first-strand cDNA was reversed-transcribed with All-in-One cDNA Synthesis SuperMix (Aidlab Biotechnologies). Gene expression was examined with a Bio-Rad CFX Manager 3.1 by a fast two-step amplification program with 2 × SYBR Green Fast qPCR Master Mix (Yeasen Biotechnology). The value obtained for each gene was normalized to that of the gene encoding β-actin. The sequences of primers for qRT-PCR analysis were included in Supplementary Table 3. The IFN-β, IL-6, TNF (Biolegend), and CCL5 (4A Biotech) protein in the sera or cell supernatants were determined by ELISA kits from the indicated manufacturers.
Bone marrow cells were isolated from femurs of Arih1fl/fl and Lyz2-Cre;Arih1fl/fl mice. The cells were cultured in DMEM containing 15% (vol/vol) FBS, 1% streptomycin–penicillin. GM-CSF (20 ng/ml, Peprotech) and M-CSF (10 ng/ml, Peprotech) were added to the bone marrow culture for differentiation of BMDCs and BMDMs, respectively. THP-1 and HEK293 cells were from the American Type Culture Collection, authenticated by STR locus analysis and tested for mycoplasma contamination. Primary MLFs were isolated from ~8–10-week-old Cre-ER and Cre-ER;Arih1fl/fl mice. Lungs were minced and digested in calcium and magnesium free HBSS buffer supplemented with 10 mg/ml type I collagenase (Worthington) and 20 μg/ml DNase I (Sigma-Aldrich) for 3 h at 37 °C with shaking. Cell suspensions were cultured in DMEM containing 15% (vol/vol) FBS, 1% streptomycin–penicillin. Two days later, adherent fibroblasts were rinsed with PBS and treated with 4-hydroxytamoxifen (1 μM) (Sigma, H6278) for 3 days before use in experiments. cGas−/− MEFs, NCTC clone 929 clone of strain L mouse fibroblasts (L929), and human foreskin fibroblasts cells (HFFs) were kindly provided by Drs. Ming-Ming Hu and Hong-Bing Shu (Wuhan University).
HEK293 cells were transfected with phage-6tag-ARIH1, phage-6tag-ARIH1C357S, phage-6tag-cGAS, phage-6tag-cGASK187R, phage-6tag-mcGASK173N, or the empty vector along with the packaging vectors psPAX2 and pMD2G. The medium was changed with fresh full medium (15% FBS, 1% streptomycin–penicillin) at 8 h after transfection. The supernatants were harvested 40 h later to infect 4OHT-treated Cre-ER;Arih1fl/fl MLFs or cGas−/− MEFs for subsequent experiments.
For qRT-PCR analysis, cells were seeded into 24-well plates (13 × 106 cells per well) and infected with HSV-1 or Sev for the indicated time points. For viral replication assays, cells (1–3 × 106) were infected with H129-G4 or HSV-1. One hour later, the supernatants were removed and cells were washed twice with 1 ml pre-warmed PBS followed by culture in full medium for 12 h. Viral replication was analyzed by flow cytometry, fluorescent microscopy, or qPCR analysis. For the intraperitoneal infection of mice, age- and sex- matched control and ARIH1 knockout mice were injected with HSV-1 (1 × 107 PFU per mouse) and the survival of animals was monitored every day. The spleens were collected for plaque assays and qRT-PCR analysis or plaque assays at 3 days after infection. For the intracranial infection of mice, age- and sex-matched control and ARIH1 knockout mice were anesthetized by intraperitoneal injection of 1% sodium pentobarbital (w/v = 1:6), followed by intracranial injection with HSV-1 (1 × 106 PFU per mouse) using a 25-μl positive displacement syringe. The needle was placed in the approximate region of the hippocampus, equidistant between the lambda and bregma, through the right parietal bone lateral to the sagittal suture. The brains were collected for HE-staining analysis at 3 days after infection.
The supernatants of BMDCs or MLFs cultures and the homogenates (or the serial dilutions) of spleens from infected mice were used to infect monolayers of Vero cells. One hour later, the supernatants or homogenates were removed and the infected Vero cells were washed with pre-warmed PBS twice followed by incubation with DMEM containing 2% methylcellulose for 48 h. The cells were fixed with 4% paraformaldehyde for 15 min and stained with 1% crystal violet for 30 min before counting the plaques.
Cells (1–3 × 107) transfected with dsDNA were harvested and homogenized in 1 mL sterile water by a 1 mL syringe pipetting up and down for 20 times. The homogenates were heated at 95 °C for 10 min followed by centrifuge at 40,000 × g (Hitachi CP100NX, P90NT-1022) for 2 h. The supernatants (900 μL) were mixed with 10 × digitonin (100 μL) and incubated with the single-layered HFF cells or L929 cells (2 × 105). Half an hour later, the supernatants were removed and full medium was added to treat HFFs for 4 h followed by qPCR assays.
The shRNAs targeting ARIH1 were constructed by plasmid pLentiLox 3.7 and transfected using Ultra Fection2.0 (4 A Biotech) or delivered to cells using lentivirus followed by qRT-PCR or immunoblot analysis. The shRNA sequences used in this study are as follows: shARIH1#1: 5′-GAACTACCCTAACTCGTATTT-3′; shARIH1#2: 5′-GCTACCTTGAACGAGATATTT-3′
Tissues from mice were fixed in 4% paraformaldehyde and embedded in paraffin blocks. The paraffin blocks were sectioned (5 μm) for HE staining (Beyotime Biotech) followed by cover-slipped. Images were acquired using an Aperio VERSA 8 (Leica) multifunctional scanner.
Single-cell suspension was resuspended in FACS buffer (PBS, 1% BSA) and blocked with anti-mouse CD16/32 antibodies for 10 min prior to staining with antibodies against surface markers (Biolgend). Flow cytometry data were acquired on a FACS Celesta or Fortesa flow cytometer, BD FACSDiVa Software v8.0.1.1, and analyzed with FlowJo software (TreeStar).
HEK293 cells were co-transfected with plasmids encoding ISG15, UBE1L, UBCH8 and FLAG-ARIH1 or empty vector for 24 h. Cells were then collected and lysed for immunoprecipitation (Denature-IP) with anti-FLAG beads followed by elution with 3 × FLAG peptide (0.3 mg/ml) in 1% SDC+ buffer (10 mM TCEP, 40 mM CAA, 1%SDC, 100 mM Tris-HCl). (Sigma, F4799). The eluted proteins were diluted with an equal volume of water to reduce the SDC concentration to 0.5% before being subjected to trypsin digestion and Liquid chromatography-mass spectrometry (LC-MS) analysis as previously described. In brief, trypsin (1 μg) was added to the diluted elutions followed by overnight incubation at 37 °C while shaking. The reactions were quenched by TFA (final concentration, 1%) followed by centrifuge for 5 min at 12,000 × g. The supernantants containing peptides were transferred to a fresh tube and desalted by SDB-RPS stage tips. The desalted peptides were dissolved in MS loading buffer (0.1% formic acid), loaded onto a C18 trap column (100 μm × 20 mm, 3 μm particle size, 120 Å pore size) through an auto-sampler and then eluted into a C18 analytical column (75 μm × 250 mm, 2 μm particle size, 100 Å pore size). Mobile phase A (0.1% formic acid) and mobile phase B (90% ACN, 0.1% formic acid) were used to establish a 60 min separation gradient. A constant flow rate was set at 300 nL per min. Data was acquired using a spray voltage of 2 kV, Ion funnel RF of 40, and ion transfer tube temperature of 320 °C. For DDA mode analysis, each scan cycle consisted of one full-scan mass spectrum (Res. 60 K, scan range 350–1500 m/z, AGC 300%, IT 20 ms) followed by MS/MS events (Res. 15 K, AGC 100%, IT auto). Cycle time was set to 2 s. Isolation window was set at 1.6 Da. Dynamic exclusion time was set to 35 s. Normalized collision energy was set at 30%. For Parallel reaction monitoring, each sample was analyzed under PRM with an isolation window of 1.6 Da. In all experiments, a full mass spectrum (Res. 60 K, AGC target 300%, scan range 350–1500 m/z, IT 30 ms) was followed by up to 24 PRM scans (Res. 30 K, AGC target 300%, IT 100 ms), as triggered by a unscheduled inclusion list. PRM data were manually curated within Skyline (version 21.1.0.278).
All mice were housed in the specific pathogen-free facility (SPF), and virus infection experiments were carried out in animal biosafety level 2 (ABSL-2) facility at the Medical Research Institute of Wuhan University. Carbon dioxide was used for euthanasia. The experimental protocol adhered to the International Guiding Principles for Biomedical Involving Animals. The protocol for animal experiments was approved by the Institutional Animal Care and Use Committee of the Medical Research Institute of Wuhan University (approval number S10221020A).
Differences between experimental and control groups were determined using two-tailed Student’s t test (where two groups of data were compared) or one-way ANOVA (where more than two groups of data were compared). P values <0.05 were considered statistically significant. For animal survival analysis, the Kaplan–Meier method was used to generate the graphs, and the survival curves were analyzed using log-rank tests.
Further information on research design is available in the Nature Research Reporting Summary linked to this article.
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PMC9551236 | Yean Sheng Lee,Xinyue Chen,Tria Widiasih Widiyanto,Kanami Orihara,Hiroyuki Shibata,Susumu Kajiwara | Curcumin affects function of Hsp90 and drug efflux pump of Candida albicans | 27-09-2022 | antifugal activity,Hsp90,CDR1,post-transcripional control,pathogenic fungus | Candida albicans is a pathogenic yeast that causes candidiasis in immunocompromised patients. The overuse of antifungal drugs has led to the development of resistance to such drugs by this fungus, which is a major challenge in antifungal chemotherapy. One approach to this problem involves the utilization of new natural products as an alternative source of antifungals. Curcumin, one such natural product, has been widely studied as a drug candidate and is reported to exhibit antifungal activity against C. albicans. Although studies of the mechanism of curcumin against human cancer cells have shown that it inhibits heat shock protein 90 (Hsp90), little is known about its function against C. albicans. In this paper, using a doxycycline-mediated HSP90 strain and an HSP90-overexpressing strain of C. albicans, we demonstrated that the curcumin triggered a decrease in Hsp90 by affecting it at the post-transcriptional level. This also led to the downregulation of HOG1 and CDR1, resulting in a reduction of the stress response and efflux pump activity of C. albicans. However, the inhibition of HSP90 by curcumin was not due to the inhibition of transcription factors HSF1 or AHR1. We also found that curcumin can not only decrease the transcriptional expression of CDR1, but also inhibit the efflux pump activity of Cdr1. Hence, we conclude that disruption of HSP90 by curcumin could impair cell growth, stress responses and efflux pump activity of C. albicans. | Curcumin affects function of Hsp90 and drug efflux pump of Candida albicans
Candida albicans is a pathogenic yeast that causes candidiasis in immunocompromised patients. The overuse of antifungal drugs has led to the development of resistance to such drugs by this fungus, which is a major challenge in antifungal chemotherapy. One approach to this problem involves the utilization of new natural products as an alternative source of antifungals. Curcumin, one such natural product, has been widely studied as a drug candidate and is reported to exhibit antifungal activity against C. albicans. Although studies of the mechanism of curcumin against human cancer cells have shown that it inhibits heat shock protein 90 (Hsp90), little is known about its function against C. albicans. In this paper, using a doxycycline-mediated HSP90 strain and an HSP90-overexpressing strain of C. albicans, we demonstrated that the curcumin triggered a decrease in Hsp90 by affecting it at the post-transcriptional level. This also led to the downregulation of HOG1 and CDR1, resulting in a reduction of the stress response and efflux pump activity of C. albicans. However, the inhibition of HSP90 by curcumin was not due to the inhibition of transcription factors HSF1 or AHR1. We also found that curcumin can not only decrease the transcriptional expression of CDR1, but also inhibit the efflux pump activity of Cdr1. Hence, we conclude that disruption of HSP90 by curcumin could impair cell growth, stress responses and efflux pump activity of C. albicans.
Candida albicans is an opportunistic pathogenic fungus, one of many microorganisms including bacteria and other fungi that normally coexist without causing harm within the human body. An infection caused by this fungus is called candidiasis, and healthy people are protected from candidiasis by both innate and acquired immunities. However, this microorganism can cause both superficial and systemic infections in humans, mainly in immunocompromised individuals such as AIDS patients, neonates, people with debilitating disease, or those who have undergone extensive surgery and are hospitalized for an extended period (Eggimann et al., 2003; Hajjeh et al., 2004; Patterson, 2005; Pfaller and Diekema, 2007; Cisterna et al., 2010; Brown et al., 2012). C. albicans has become the most common pathogenic fungi in humans, with the incidence of fungal infections having increased greatly in recent decades. This is due to the growing proportion of the worldwide human population that is immunocompromised and aged. Significant progress has been made in antifungal chemotherapy (Cowen et al., 2002; Carrillo-Munoz et al., 2006; Ortega et al., 2011), but the appearance of antifungal resistant strains and the limits of effective and selective antifungals are major problems in the treatment of clinical fungal infections (Almirante et al., 2005). It is therefore urgent to develop novel antifungal agents that are both safe and effective. One strategy is to combine the search for new potential targets with the screening of promising new antifungal agents (Carrillo-Munoz et al., 2006). To develop novel antifungals, there have been numerous efforts to identify natural compounds that exhibit effective antifungal activity, and one such compound, curcumin, has been of great interest to the scientific community due to its chemotherapeutic properties (Hatcher et al., 2008). Curcumin is a yellow-pigmented polyphenolic compound that is derived from the roots of the Curcuma longa, a plant native to India and other parts of southeast Asia (Limtrakul et al., 2004; Jurenka, 2009; Rowe et al., 2009). In India and China, this compound has been widely used as a cosmetic and sometimes as medicine for the treatment of wounds and inflammation (Govindarajan and Stahl, 1980; Ammon and Wahl, 1991; Strimpakos and Sharma, 2008). Previous studies have found that curcumin has anti-carcinogenic, antioxidant, anti-inflammatory, and antimicrobial properties, as well as exhibiting hypoglycemic effects in humans (Jurenka, 2009). In addition, the safety of curcumin has been studied in animal models and human clinical trials, which have shown that its toxicity is low even when administered at high doses (Bhavani Shankar et al., 1980; Qureshi et al., 1992). Previous studies using both biochemical, genetic or both approaches have shown that the curcumin exhibits antifungal activity against C. albicans via oxidative stress, inhibiting hyphal development, disrupting cell wall integrity and plasma membrane, modulates proteolytic enzyme activity, altering the membrane-associated properties of ATPase activity, modulating efflux pumps, synergizing with antifungal azoles, and inhibiting biofilm formation (Sharma et al., 2009; Sharma et al., 2010a; Sharma et al., 2010b; Neelofar et al., 2011; Garcia-Gomes et al., 2012; Kumar et al., 2014; Lee and Lee, 2014; Shahzad et al., 2014; Thakre et al., 2016; Alalwan et al., 2017; Chen et al., 2018; Andrade et al., 2019; Hamzah et al., 2020; Cheraghipour et al., 2021; Dong et al., 2021; Lasrado et al., 2022). However, little is known about the molecular mechanisms of curcumin’s effect on yeast cells. In human cancer therapeutic, a series of recent studies show that curcumin inhibits heat-shock protein 90 (Hsp90) in human cancer cells (Zhang et al., 2007; Giommarelli et al., 2010; Anand et al., 2012; Khan et al., 2012; Li et al., 2012; Bhullar et al., 2015; Lv et al., 2015; Zheng et al., 2016; Ye et al., 2017; Fan et al., 2018; Forouzanfar et al., 2019; Liu et al., 2020; Surma et al., 2022). Due to the high conservation of Hsp90 across species and the high degree of homology between C. albicans and human Hsp90, curcumin is expected to have disruptive effects on Hsp90 in fungal cells as well (Whitesell et al., 2019). But to our knowledge, no study has examined the relationship between fungal HSP90 and curcumin. To illuminate this uncharted area, we examined the effects of curcumin on the HSP90 of C. albicans by utilizing a defective conditional HSP90 mutant and an HSP90-overexpressing strain. Since the HSP90 gene is essential for C. albicans, a doxycycline (Dox)-regulated expression system was adopted in C. albicans by replacing the promoter of HSP90 with the tetO system. This allowed us to control the gene expression of HSP90 by supplementing Dox, which binds to tetR to prevent the transcription of HSP90. To better understand the mechanism of curcumin, we also overexpressed HSP90 by replacing its promoter with the constitutive ADH1 promoter. In addition, the low bioavailability and poor stability of curcumin have been highlighted as major problems for therapeutic application (Blasius et al., 2004; Anand et al., 2007; Fang et al., 2013). Therefore, many studies have been carried out attempting to improve the bioavailability and stability of curcumin by modification of the molecular structure. GO-Y030, a curcumin derivative designed by Shibata et al. (Shibata et al., 2009), has been reported to possess greater anti-cancer properties than curcumin itself and is significantly less toxic (Gritsko et al., 2006; Cen et al., 2009; Hutzen et al., 2009; Kudo et al., 2011; Mohan Yallapu et al., 2012). However, the antifungal activity of curcumin GO-Y030 has not yet been studied. This study aimed to study the effect of curcumin and its derivative GO-Y030 on Hsp90 of C. albicans.
Curcumin (Wako, Japan) stock solutions were prepared in sterile dimethyl sulfoxide (DMSO). The curcumin analogue GO-Y030 was provided by Akita University, Japan. Its stock solution was prepared in sterile DMSO and stored at 4°C. Nile red (Wako, Japan) stock solution was prepared in ethanol and stored at 4°C. Doxycycline (Wako, Japan) was prepared in distilled water and stored at 4°C. Curcumin compounds and all dye solutions were kept in the dark to prevent light exposure.
C. albicans strains used in this study are listed in the Table 1 . All strains were routinely grown in Yeast Extract Peptone Dextrose (YPD; 1% yeast extract, 2% peptone, 2% glucose) or synthetic defined medium (SD; 0.67% yeast nitrogen base without amino acids, 0.079% complete supplement mixture without uracil, 2% glucose) on plates with 2% agar at 37°C. All strains were maintained and stored at 4°C. All strains were stored as frozen stocks with 15% glycerol at −80°C. Construction of the Dox-mediated HSP90 gene mutant and HSP90 overexpression mutant were performed as previously described (Reuß and Morschhäuser, 2006; Lai et al., 2016). The plasmids and primers used in this study are listed in the Tables 2 , 3 . The HSP90/hsp90Δ strain was constructed as follows: one of the chromosomal HSP90 alleles in the C. albicans strain THE1 was deleted using the SAT-flipper method, as described previously (Reuß et al., 2004). SAT1 was amplified with primers SAT1.FOR and SAT1.REV. SAT2 was amplified with primers SAT2.FOR and SAT2.REV. From plasmid pSFS2, pSFS2-SAT1/2 was generated by cloning PCR fragments SAT1 and SAT2 into the respective sites. pSFS2-SAT1/2 was digested with KpnI and SacI to release the disruption cassette and transformed into the TR transactivator gene-containing strain THE1 by electroporation (Thompson et al., 1998). Nourseothricin-resistant transformants were selected on YPD agar plates containing 200 µg/mL of nourseothricin. After the induction of FLP recombinase by growing in YPD medium, nourseothricin-sensitive colonies were selected on the YPD plates containing 25 µg/mL of nourseothricin according to their colony size. The tet-HSP90/hsp90Δ strain was constructed as follows: two regions spanning positions −711 to −138 (HSP1) and positions −7 to +528 (HSP2) relative to the ATG start codon of the HSP90 open reading frame were PCR amplified using primer pairs HSP1.FOR with HSP1.REV and HSP2.FOR with HSP2.REV. These amplification products were then cloned into the respective sites of plasmid p97CAU1 (Nakayama et al., 2000) to form p97CAU1-HSP1/2. This plasmid was then digested with ApaI and SacII to liberate the entire 3 kb promoter-replacing construct and transformed into the HSP90/hsp90Δ strain using electroporation (Thompson et al., 1998). Ura+ transformants were selected on SD agar plates without uracil. The HSP90-overexpressing mutant (PADH1 -HSP90) was constructed as follows: the TR promoter of plasmid p97CAU1-HSP1/2 was replaced by the ADH1 promoter to form plasmid p97CAU1A-HSP1/2. Briefly, the ADH1 promoter was amplified by ADH1.FOR and ADH1.REV using C. albicans SC5314. Then, the ADH1 promoter fragment replaced the TR promoter of plasmid p97CAU1-HSP1/2 at restriction sites SpeI and SmaI to form plasmid p97CAU1A-HSP1/2. Similar to the construction of the tet-HSP90/hsp90Δ strain, this plasmid was then digested with ApaI and SacII to liberate the entire 2.505 kb promoter-replacing construct and transformed into C. albicans THE1 using electroporation (Thompson et al., 1998). Ura+ transformants were selected on SD agar plates without uracil.
Minimum inhibitory concentration (MIC) assays were carried out in flat-bottom, 96-well microtiter plates (Iwaki, Japan) using serial broth microdilution with minor modifications (Rodríguez-Tudela et al., 2003). The MIC80 was defined as the concentration of the antifungal compound that inhibits 80% of the growth of cells as compared with the control. MIC tests were set up in a final volume of 200 µL per well with 2-fold serial dilutions of curcumin compounds in YPD. Gradients of curcumin compounds were diluted from 250 µg/mL down to 0 µg/mL. C. albicans strains SC5314 or PADH1-HSP90 were grown in YPD overnight at 37°C. Then the cells were collected and washed by phosphate-buffered saline (PBS) three times. The number of cells was adjusted to 1 × 103 cells/mL in YPD. 100 µL of each strain was inoculated into each well. The plates were then incubated at 37°C for 24 h. The endpoint of the MIC assay was determined by Varioskan Lux (Thermo Scientific, Japan) at an absorbance of 530 nm and corrected for background from the corresponding medium. Each strain was tested in triplicate for each curcumin compound. The optical densities were averaged for triplicate measurements.
To elucidate the potential mechanism by which curcumin inhibits the growth of C. albicans, HSP90, HSF1, AHR1, HOG1, CDR1, CDR2, and MDR1 gene expression analysis was performed using qRT-PCR. Briefly, the wildtype, tet-HSP90/hsp90Δ, or PADH1-HSP90 strains were cultured at 37°C in YPD until they reached the exponential phase. The cells were then collected, washed, and resuspended in YPD containing curcumin compounds or Dox. A drug-free control was included for each experiment. The samples were then pelleted and washed with Diethyl pyrocarbonate (DEPC)-treated water. The pellet was used to extract the RNA using hot acidic phenol and purified using ethanol (Collart and Oliviero, 1993). The purity and concentration of the extracted RNA were verified using GeneQuant 100 (Biochrom, Japan). RNA was then converted to cDNA using ReverTra Ace™ qRT RT Master Mix with gDNA Remover (Toyobo, Japan) following the manufacturer’s recommended protocol. Gene expression was analyzed by qRT-PCR using the StepOne™ Real-Time PCR System (Thermo Fisher, Japan). The ACT1 housekeeping gene was used as a reference, and the relative gene expression (fold change) was determined by the 2-ΔΔCT method (Livak and Schmittgen, 2001). The primers used for qRT-PCR are listed in Table 4 .
The drug combinations were studied by means of a two-dimensional broth microdilution checkerboard procedure using two-antifungal agents as described in the Clinical Microbiology Procedures Handbook (Isenberg, 1992). The checkerboard assays were carried out in flat-bottom, 96-well microtiter plates (Iwaki, Japan) using a serial broth microdilution protocol with minor modifications (Chaturvedi et al., 2008). Tests were set up in a final volume of 200 µL per well with 2-fold serial dilutions of curcumin in YPD medium. Gradients of curcumin and Dox were diluted from 250 µg/mL down to 0.24 µg/mL and from 0.1 µg/mL to 0.00156 µg/mL, respectively. C. albicans SC5314 and tet-HSP90/hsp90Δ strains were grown in YPD overnight at 37°C. Then the cells were collected and washed by PBS three times, and the number of cells was adjusted to 1 × 103 cells/mL in YPD. 100 µL of each strain was inoculated into each well, and the plates were incubated at 37°C for 24 h. The endpoint of the MIC was determined by Varioskan Lux (Thermo Scientific, Japan) at an absorbance of 530 nm and corrected for background from the corresponding medium. The data were quantitatively displayed with color using the program Java TreeView 1.2.0.
The heat shock and osmotic stress experiments were performed according to the protocol described previously (Enjalbert et al., 2003). Briefly, cells from an overnight culture were transferred to fresh YPD medium containing curcumin compounds and allowed to grow at 37°C for 2 h. A drug-free control was included for each experiment. For heat shock experiments, the cells were then transferred to 42°C. 100 µL aliquots of the control and stress samples were removed at 0 and 20 min. The cells were then diluted and spread on YPD agar plates. For osmotic stress response, the cells were diluted and spread on YPD plates with or without 1 M NaCl. The plates were then incubated at 37°C for 24 h to observe cell growth. Each experiment was repeated three times.
The Nile red efflux assay was performed according to a previous protocol (Ivnitski-Steele et al., 2009; Keniya et al., 2015; Eldesouky et al., 2018). To determine the relationship between efflux pump activity and curcumin without depleting the HSP90 gene, curcumin and Nile red were supplemented simultaneously. Briefly, exponential phase wildtype strain was harvested, washed twice with PBS, and resuspended in PBS containing 2% glucose. The cells were then incubated with 125 µg/mL of curcumin and 7 µM of Nile red for 10 min. To determine the relationship between efflux pump activity and depletion of the HSP90 gene by curcumin, exponential phase wildtype or PADH1-HSP90 strain were incubated with 125 µg/mL of curcumin for 2 h. Then the cells were washed with PBS, resuspended in PBS containing 2% glucose, and incubated with 7 µM Nile red for 10 min at 37°C. For the tet-HSP90/hsp90Δ mutant, cells were incubated with 0.1 µg/mL of Dox for 2 h before treatment with Nile red. For flow cytometry analysis, the accumulation of Nile red was measured using an EC800 (Sony, Japan) flow cytometer with an excitation wavelength of 488 nm and emission filter of 585/42 nm. At least 10,000 events were analyzed in each experiment.
To determine the in vitro susceptibility of C. albicans SC5314 to curcumin and GO-Y030, broth microdilution assays were performed in YPD medium. Cell growth was determined by absorbance at 530 nm after a 24-h drug treatment. As the concentration of curcumin compounds increased, the cell growth decreased ( Figure 1 ). We found that both curcumin compounds inhibited the growth of C. albicans dose-dependently. The data also revealed that C. albicans was more susceptible to curcumin than to GO-Y030. At a concentration of 250 µg/mL, curcumin inhibited about 80% of cell growth compared to the control (MIC80 = 250 µg/mL). In contrast, GO-Y030 inhibited only about 60% of cell growth.
To investigate the effect of curcumin compounds on the gene expression of HSP90, we determined the transcript levels of HSP90 after mid-log phase C. albicans was treated with these compounds for 2 h in YPD at a sub-MIC80 concentration (125 µg/mL). Figure 2 shows the relative transcript levels of HSP90 in C. albicans SC5314 after treatment with the two curcumin compounds. HSP90 levels in cells with either compound was significantly lower than those in untreated cells. This suggests that both curcumin compounds downregulated HSP90 expression. Our results also showed that curcumin strongly reduced the transcript levels of HSP90 compared to GO-Y030. This might explain why curcumin exhibited greater antifungal activity than GO-Y030. These results suggest that the effect of curcumin might be attributable to the inhibition of HSP90 expression.
To determine whether the HSP90 gene is involved in the function of curcumin, we constructed a conditional HSP90 mutant and an HSP90-overexpressing strain of C. albicans. To construct a Dox-repressible allele of HSP90, by using the HSP90/hsp90Δ strain derived from SC5314, we replaced the C. albicans HSP90 promoter on the other allele with a tetO element to obtain the tetO-HSP90/hsp90Δ strain. This strain reduces HSP90 expression in a Dox-dependent manner ( Figure 3A ). In addition, an HSP90-overexpressing strain, PADH1-HSP90, was produced by replacing the promoter of HSP90 with the ADH1 promoter as shown in Figure 3B . The levels of curcumin sensitivity of the wildtype, tetO-HSP90/hsp90Δ, and PADH1 -HSP90 strains were compared. For the wildtype, 250 µg/mL of curcumin (MIC80) inhibited cell growth completely ( Figure 3C ). This data also revealed that Dox did not affect the curcumin sensitivity of the wild type. For the tetO-HSP90/hsp90Δ strain, the MIC80 of curcumin was decreased under a high concentration of Dox. At 0.025 µg/mL and 0.05 µg/mL of Dox, the MIC80 of curcumin were 15.6 µg/mL and 7.8 µg/mL, respectively. This result showed that the depletion of HSP90 enhanced sensitivity to curcumin. Hence, the HSP90 gene might play an important role in resistance to curcumin in C. albicans. Moreover, microbroth dilution assays using the HSP90 overexpression strain (PADH1-HSP90) were performed. Figure 3D shows the growth of SC5314 and PADH1-HSP90 after treatment with curcumin. Although growth of the wildtype strain was decreased at a high concentration of curcumin, this compound had no effect on the growth of PADH1-HSP90 cells. This result indicated that overexpression of the HSP90 gene suppressed sensitivity to curcumin. Overall, these results suggest that HSP90 is the key factor in the growth inhibition of C. albicans by curcumin.
We then investigated the effect of curcumin on HOG1 expression as well as that of HSP90. Figure 4A shows that curcumin reduced the transcript levels of both HOG1 and HSP90. This reduction was restored by the overexpression of HSP90 in the presence of curcumin ( Figure 4B ). To confirm the relationship between the HSP90 and HOG1, the mRNA levels of tetO-HSP90/Δhsp90 strain were also analyzed. When HSP90 expression was suppressed by Dox, the gene expression of HOG1 was decreased ( Figure 4C ), confirming that the reduction of HSP90 transcripts led to the reduction of HOG1 gene expression in C. albicans. To further validate the stress responses of the wild type, PADH1-HSP90, and tetO-HSP90/hsp90Δ, the growth of these strains under thermal and osmotic stresses were analyzed. Stress response tests were performed with heat shock at 42°C for 30 min and with 1 M NaCl. Curcumin reduced the thermotolerance of the wildtype strain after it was exposed to 42°C for 30 min compared to the control (37°C) ( Figure 4D ). In contrast to the wild type, HSP90 overexpression in C. albicans resulted in the growth of cells at 42°C ( Figure 4E ). In addition, the repression of HSP90 led to a reduction in the tolerance of cells at high temperature ( Figure 4F ). Similarly, curcumin also reduced the osmotic tolerance of C. albicans to exposure to 1 M NaCl ( Figure 4D ). Contrastingly, the overexpression of HSP90 in C. albicans retained the tolerance when cells were treated with curcumin ( Figure 4E ). Repression of HSP90 decreased the osmotic tolerance to a high concentration of NaCl ( Figure 4F ). These results implied that the downregulation of HSP90 by curcumin impaired the thermal and osmotic stress responses of C. albicans.
The mRNA levels of transcription factors HSF1 and AHR1 were analyzed in the presence of curcumin. Unexpectedly, curcumin initiated the transcriptional induction of HSF1, while it did not affect the mRNA of AHR1 ( Figure 5A ). This suggests that the reduction of the HSP90 mRNA level by curcumin was not due to the inhibition of HSF1 transcriptional expression. We confirmed this using the tetO-HSP90/Δhsp90 mutant. In the presence of the Dox, which suppressed the gene expression of HSP90, the HSF1 transcript level was increased ( Figure 5B ). Therefore, HSP90 reduction by curcumin was not a result of, but rather led to, the increase of HSF1 mRNA in C. albicans. We initially thought that Dox-controlled HSP90 in the tetO-HSP90/Δhsp90 strain would not be affected by curcumin. However, our results showed that curcumin downregulated HSP90 in tetO-HSP90/Δhsp90 as well as in the wild type. We speculated that this might be due to the post-transcriptional regulation of HSP90 by curcumin. To test this, the mRNA level of HSP90 was measured after cells were treated with actinomycin D (ActD), an RNA polymerase inhibitor, as shown in Figure 5C . The cells were then treated with curcumin for 0, 30, 60, or 90 min. After treatment with ActD, HSP90 mRNA of the cells degraded gradually, and in addition, it degraded faster in the presence of curcumin than in the control ( Figure 5D ). In contrast, the degradation of ACT1 mRNA was not affected by the addition of curcumin ( Figure 5D ). This showed that curcumin accelerated the degradation of HSP90 mRNA specifically and suggests that curcumin induces the post-transcriptional degradation of HSP90.
Since curcumin downregulated the transcriptional level of HSP90, we expected that curcumin might influence the gene expression of CDR1. Therefore, we investigated CDR1 and CDR2 (another ABC transporter gene) expression in the presence of curcumin or geldanamycin, which is a known Hsp90 inhibitor. Figure 6A shows that CDR1 gene expression was reduced significantly by curcumin and geldanamycin, but that of CDR2 was not. A reduction of the CDRs by curcumin and geldanamycin did not occur in the PADH1 -HSP90 strain ( Figure 6B ). To further confirm that the CDR1 reduction was due to a reduction of HSP90 by curcumin and geldanamycin, the effect of depleting HSP90 on CDR1 was determined using the tetO-HSP90/Δhsp90 strain ( Figure 6C ). In the presence of Dox, CDR1 transcripts decreased while those of CDR2 remained unchanged. These results suggest that curcumin only downregulated CDR1 expression via a reduction of HSP90 in C. albicans.
As the gene expression of CDR1 in C. albicans was reduced by curcumin, we assumed that the efflux pump activity of the cells might be affected by curcumin. To test this, the Nile red accumulation assay was performed ( Figure 7A ). For the wildtype strain, the addition of curcumin led to a high accumulation of Nile red compared to the control ( Figures 7B, C ). This accumulation was thought to be due to the repression of the CDR1 gene by the reduction of HSP90 ( Figure 8 ). The relationship between the expression of HSP90 and the export of Nile red was confirmed by using the tetO-HSP90/hsp90Δ strain ( Figures 7D, E ). The overexpression of HSP90 reversed the accumulation of Nile red by curcumin ( Figures 7F, G ), suggesting that overexpression of the HSP90 gene maintained CDR1 expression and restored Nile red extrusion. These results implied that curcumin repressed HSP90 mRNA resulted in repression of CDR1 which caused the disruption of efflux pump activity.
To test the effect of curcumin as an efflux pump inhibitor, cells were exposed to curcumin and Nile red simultaneously for 10 min ( Figure 9A ). Based on the flow cytometry results, the addition of curcumin led to the accumulation of Nile red compared to the control ( Figures 9B, C ). However, Nile red did not accumulate in the tetO-HSP90/hsp90Δ strain with Dox ( Figures 9D, E ). Since the 10-min pretreatment with curcumin would not alter the gene expression of HSP90 and CDR1, Cdr1 was not decreased ( Figure 10 ). These results suggest that, without affecting gene expression of ABC-transporters, curcumin also acts on Cdr1 directly to inhibit its function but Dox does not.
Curcumin, a curcuminoid produced from the rhizomes of Curcuma longa (a tiny perennial herb native to India), has been reported to possess anti-inflammatory, anticarcinogenic, and anti-infectious activities (Ravindran et al., 2009; Neelofar et al., 2011). Several shortcomings of curcumin, such as its low bioavailability and poor stability, have been highlighted as major problems in its therapeutic application (Blasius et al., 2004; Anand et al., 2007; Fang et al., 2013). Therefore, many studies have tried to improve the bioavailability and stability of curcumin by structural modification. GO-Y030 reportedly has greater anti-carcinogenic activity and lower toxicity than curcumin (Gritsko et al., 2006; Cen et al., 2009; Hutzen et al., 2009; Kudo et al., 2011; Mohan Yallapu et al., 2012). As the antifungal activity of GO-Y030 has remained unclear, we assessed its inhibitory effect on C. albicans growth. In this study, broth microdilution assays demonstrated that curcumin and GO-Y030 had antifungal inhibitory activity against the growth of C. albicans SC5314 ( Figure 1 ). This result is consistent with previous studies (Andrade et al., 2019; Narayanan et al., 2020) wherein curcumin inhibited the growth of Candida strains in a range between 100 µg/mL and 250 µg/mL. Although GO-Y030 had lower antifungal activity than curcumin in this study, to our knowledge, this is the first report showing that GO-Y030 inhibits the growth of C. albicans. Despite the numerous cytotoxic effects of curcumin on C. albicans that have been already reported (Sharma et al., 2009; Sharma et al., 2010a; Sharma et al., 2010b; Neelofar et al., 2011; Shahzad et al., 2014; Alalwan et al., 2017; Andrade et al., 2019; Hamzah et al., 2020), the mechanism of this function of curcumin remains unknown. In cancer therapeutics for humans, curcumin has also been reported to be an antitumor compound. This compound influences the HSP90 gene and its gene product in human tumor cells (Zhang et al., 2007; Giommarelli et al., 2010; Anand et al., 2012; Khan et al., 2012; Li et al., 2012; Liu et al., 2014; Bhullar et al., 2015; Lv et al., 2015; Zheng et al., 2016; Ye et al., 2017; Fan et al., 2018; Forouzanfar et al., 2019). Recent studies have shown that curcumin inhibits ATPase activity in Hsp90 of human cancer cells. The expression of HSP90 is higher in tumors compared with normal tissues and is important in the maintenance of the stability, integrity, and function of oncogenic proteins. Curcumin and several curcumin derivatives such as C1206, C0818, and CUR3d, have been shown to inhibit Hsp90 function. This results in the dissociation of complexes with client proteins that are important in cell proliferation, cytotoxic damage survivability, and apoptosis, among other functions (Jung et al., 2007; Giommarelli et al., 2010; Lee and Chung, 2010; Bhullar et al., 2015; Fan et al., 2017; Fan et al., 2018). In addition, curcumin has also been found to downregulate HSP90 gene expression in human cells such as chronic myeloid leukemia cells and human embryonic lung fibroblast cells (Zhang et al., 2007; Lv et al., 2015; Zheng et al., 2016; Ye et al., 2017; Sang et al., 2018). C. albicans Hsp90 has also been studied as a heat shock protein that is essential for maintaining homeostasis by promoting the proper folding of abundant client proteins. According to numerous studies, Hsp90 is involved in thermal stability, morphogenesis, cell cycle control, apoptosis, and drug resistance in C. albicans (Leach et al., 2012b; O’Meara and Cowen, 2014). Hence, interfering with the physiological activity of Hsp90 could be a promising strategy for treating candidiasis. However, there have been no reports about the effects of curcumin on Hsp90 in this pathogenic fungus. Hsp90 is common among many species and has a conserved amino acid sequence between C. albicans and humans (Swoboda et al., 1995), so we expected curcumin to affect Hsp90 in C. albicans as well. This study showed that the exposure of C. albicans to curcumin or GO-Y030 triggered the transcriptional reduction of HSP90 ( Figure 2 ). This is an important finding in understanding the function of curcumin in C. albicans. Unexpectedly, curcumin exhibited greater antifungal activity than GO-Y030 on C. albicans, which is the opposite of findings in human tumor cells. To alter HSP90 expression in C. albicans, we utilized a Dox-mediated HSP90 strain and an HSP90-overexpressing strain to investigate the effects of curcumin on C. albicans. Our data revealed that the depletion of HSP90 in the tetO-HSP90/hsp90Δ strain increased susceptibility to curcumin dose-dependently with Dox ( Figure 3C ), and a synergic effect of curcumin and Dox appeared. In contrast, the effect of curcumin disappeared by the overexpression of HSP90 in the PADH1-HSP90 strain ( Figure 3D ). These findings indicated that curcumin inhibits the growth of C. albicans by repressing HSP90 function. Previous reports (Diezmann et al., 2012; Leach et al., 2012a; Leach et al., 2012b; O’Meara and Cowen, 2014) have shown that HSP90 plays an important role in the survivability of yeast species at high temperatures and high osmotic pressures. The depletion of HSP90 reduced the thermotolerance of C. albicans and led to the decrease of a mitogen-activated protein kinase, Hog1, which plays an important role in the osmotic stress response. This study showed that the depletion of HSP90 by curcumin resulted in a reduction of HOG1 ( Figure 4 ), suggesting that curcumin also decreased HOG1 expression and impaired the stress response of C. albicans. In C. albicans, protein kinase CK2 and transcription factor Ahr1 operate upstream of Hsp90 to promote cell growth in many environments. In addition, HSP90 expression is also controlled by the transcription factor Hsf1, whose activation is repressed by Hsp90. The depletion of Hsp90 induces Hsf1 phosphorylation and upregulates Hsf1 targets, and depletion of HSP90 activates HSF1 (Zou et al., 1998; Diezmann et al., 2012; Leach et al., 2012a; Leach et al., 2016; Kijima et al., 2018; Veri et al., 2018). Our results showed that curcumin induced the transcription of HSF1 in the wildtype strain, the same as in the Dox-mediated tetO-HSP90/hsp90Δ strain ( Figures 5A,B ). These experiments suggested that curcumin reduces HSP90 expression directly, and not dependently on Ahr1 and Hsf1. Interestingly, we thought that HSP90 expression in the tetO-HSP90/hsp90Δ strain would not be influenced by curcumin, because the HSP90 promoter was replaced by the tetO element. However, curcumin reduced HSP90 mRNA in the tetO-HSP90/Δhsp90 strain ( Figure 4C ). Hence, we assumed that the induction of HSP90 mRNA degradation occurred in the presence of curcumin. After actinomycin D inhibited transcription in the cells, the HSP90 mRNA amount was measured in the presence or absence of curcumin ( Figure 5C ). Although HSP90 mRNA was degraded gradually after inhibition of mRNA synthesis, curcumin accelerated its degradation ( Figure 5D ). In contrast, faster degradation of ACT1 mRNA was not observed when adding curcumin ( Figure 5D ). Curcumin has been reported to change DNA methylation in human cancer cells as an epigenetic modification (Link et al., 2013). This indicates that curcumin might have inhibited HSP90 expression at the post-transcriptional level by DNA methylation changes. ABC transporters, including Cdr1 and Cdr2, are drug efflux pumps that play an important role in the development of multidrug resistance in C. albicans. Previous studies have shown that curcumin inhibits ABC transporters, including C. albicans Cdr1, Cdr2, and Saccharomyces cerevisiae Pdr5p, competitively (Sharma et al., 2009; Sharma and Prasad, 2011). In addition, recent studies (Diezmann et al., 2012; Leach et al., 2012a) have shown that a reduction of HSP90 reduces the protein level of Cdr1 in C. albicans. In this study, curcumin downregulated CDR1 gene expression, suggesting that the reduction of HSP90 expression by curcumin led to a decrease in CDR1 expression. Previous study showed that curcumin was able to modulate multidrug resistance (MDR) phenotype of C. albicans (Garcia-Gomes et al., 2012). In this study, the Nile red accumulation assay was used to analyze the efflux pump activity in C. albicans. Nile red is a known substrate of ABC-transporters Cdr1, Cdr2 and Mdr1 in C. albicans (Ivnitski-Steele et al., 2009), the cells can efflux Nile red immediately. Our data showed that curcumin drastically decreased the efflux pump activity of the wildtype strain after a 2-h incubation with curcumin ( Figures 7B, C ). This was due to the reduction of CDR1 expression by curcumin. The depletion of HSP90 in the tetO-HSP90/Δhsp90 strain also led to a decrease in efflux pump activity, while HSP90 overexpression maintained the efflux pump activity of the PADH1-HSP90 strain in the presence of curcumin ( Figures 7D-G ). Curcumin is also known to be an inhibitor of Cdr1 activity (Pearson et al., 1999; Falagas et al., 2006; Piddock, 2006; Sharom, 2008; Wu et al., 2011). In this study, without affecting gene expression of ABC-transporters, curcumin also blocked efflux pump activity for Nile red in the wild type ( Figures 9 , 10 ). This finding showed that curcumin inhibited the activity of efflux pumps such as Cdr1, while low efflux pump activity remained because Cdr2 and Mdr1 were not inhibited by curcumin. Taken together, this study sheds new light on the functions of curcumin ( Figure 11 ). Curcumin affects not only drug efflux pumps such as Cdr1 but also HSP90 expression, mainly at the post-transcriptional level. Hence, the natural product curcumin and its derivatives may be used as antifungals to inhibit drug efflux pumps and cell growth of C. albicans. However, the complex mechanism by which curcumin affects C. albicans needs to be further explored.
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.
YL and SK conceived the study. YL performed the experiments; YL, TW, and XC collected and analyzed the data. KO and HS gave support YL, XC and SK wrote the manuscript. All authors contributed to the article and approved the submitted version.
We received internal research funds from Tokyo Institute of Technology.
We thank the Open Research Facilities for Life Science and Technology in the Tokyo Institute of Technology for technical support and equipment.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9551381 | Xintong Liu,Peihong Fang,Zicheng Wang,Xiaoqian Cao,Zhiyi Yu,Xi Chen,Zhao Zhang | Comparative RNA-seq analysis reveals a critical role for ethylene in rose (Rosa hybrida) susceptible response to Podosphera pannosa | 27-09-2022 | powdery mildew,transcriptome,transcription factors,rose leaf,1-MCP | Rose is one of the most important ornamental flowers, accounting for approximately one-third of the world’s cut flower market. Powdery mildew caused by Podosphera pannosa is a devastating fungal disease in rose, mainly infecting the young leaves and causing serious economic losses. Therefore, a study on the mechanism of the fungus infecting the rose leaves and the possibility to improve resistance hereby is interesting and meaningful. Accordingly, we conducted transcriptome sequencing of rose leaves infected by P. pannosa at different time points to reveal the molecular mechanism of resistance to powdery mildew. The high-quality reads were aligned to the reference genome of Rosa chinensis, yielding 51,230 transcripts. A total of 1,181 differentially expressed genes (DEGs) were identified in leaves during P. pannosa infection at 12, 24, and 48 hpi. The transcription factors of ERF, MYB, bHLH, WRKY, etc., family were identified among DEGs, and most of them were downregulated during P. pannosa infection. The Kyoto Encyclopedia of Genes and Genomes analysis showed that the hormone signal transduction pathway, especially ethylene signal-related genes, was consistently showing a downregulated expression during powdery mildew infection. More importantly, exogenous 1-MCP (inhibitor of ethylene) treatment could improve the rose leaves’ resistance to P. pannosa. In summary, our transcriptome of rose leaf infected by powdery mildew gives universal insights into the complex gene regulatory networks mediating the rose leaf response to P. pannosa, further demonstrating the positive role of 1-MCP in resistance to biotrophic pathogens. | Comparative RNA-seq analysis reveals a critical role for ethylene in rose (Rosa hybrida) susceptible response to Podosphera pannosa
Rose is one of the most important ornamental flowers, accounting for approximately one-third of the world’s cut flower market. Powdery mildew caused by Podosphera pannosa is a devastating fungal disease in rose, mainly infecting the young leaves and causing serious economic losses. Therefore, a study on the mechanism of the fungus infecting the rose leaves and the possibility to improve resistance hereby is interesting and meaningful. Accordingly, we conducted transcriptome sequencing of rose leaves infected by P. pannosa at different time points to reveal the molecular mechanism of resistance to powdery mildew. The high-quality reads were aligned to the reference genome of Rosa chinensis, yielding 51,230 transcripts. A total of 1,181 differentially expressed genes (DEGs) were identified in leaves during P. pannosa infection at 12, 24, and 48 hpi. The transcription factors of ERF, MYB, bHLH, WRKY, etc., family were identified among DEGs, and most of them were downregulated during P. pannosa infection. The Kyoto Encyclopedia of Genes and Genomes analysis showed that the hormone signal transduction pathway, especially ethylene signal-related genes, was consistently showing a downregulated expression during powdery mildew infection. More importantly, exogenous 1-MCP (inhibitor of ethylene) treatment could improve the rose leaves’ resistance to P. pannosa. In summary, our transcriptome of rose leaf infected by powdery mildew gives universal insights into the complex gene regulatory networks mediating the rose leaf response to P. pannosa, further demonstrating the positive role of 1-MCP in resistance to biotrophic pathogens.
Rosa hybrida (modern rose) is independently domesticated in both Europe and China several thousands of years ago (Rusanov et al., 2009). Rose is one of the most important cut flowers and ornamental plants worldwide. Its planting area and market size rank as the first in global flower production, which means a remarkable commercial value. However, the rose is vulnerable to fungal diseases during cultivation and post-harvest transport, which cause huge economic losses. Among them, powdery mildew (PM) is one of the most common but devastating fungal diseases in the world (Debener and Byrne, 2014). In addition to the diseases of rose, it also affects other Roseceae plants, like apple, strawberry, pear, etc., and it is more serious in the greenhouse than in the open field. There are more than 650 species of Erysiphales in Ascomycota, including 15 sexual and four asexual species. This fungus has a wide range of hosts. More than 650 species of monocotyledonous plants and over 9,000 species of dicotyledonous plants have been reported (Schulzelefert and Vogel, 2000). Rose powdery mildew was caused by Podospheara pannosa (Pp.). The fungus is a biotrophic ascomycete. In a warm, dry, or humid environment, PM infects the green vegetative organs such as young leaves and shoots of rose (Debener and Byrne, 2014). The rapid spread of PM causes the withered leaves of the plants to shrivel, shrink, or even fall off, and the surface is covered with white powder. PM is greatly damaging the ornamental and economic value of rose worldwide. An effective way to control the disease is to improve the resistance of plants (Vielba-Fernández et al., 2020). Comparative transcriptional analysis, using RNA-based sequencing (RNA-seq), is a common strategy of understanding the molecular mechanism of plant–pathogen interactions. This method has been widely applied in research about plant–pathogen interactions in horticultural crops, including rose (Rosa hybrida) (Liu et al., 2018), grape (Vitis vinifera) (Toffolatti et al., 2018), and apple (Malus × domestica) (Tian et al., 2019). However, to date, the lack of transcriptomic data on rose–PM interactions, coupled with the limitations of transgenesis and gene editing on rose, led to breeding in rose against PM with little progress achieved. Normally, the onset of plant resistance to pathogens begins from the recognition of pathogens by plants, followed by the cascade of transmission of disease resistance signals depending on PAMP-triggered immunity and effector-triggered immunity. Signaling molecules and transcription factors (TFs) are the key components in both basal and race-specific immunity (Yuan et al., 2021). Plant hormones SA, JA, and ethylene (ET) are considered to be the main regulatory signals related to plant disease resistance. It is generally believed that SA is mainly the downstream signal of defense responding to the biotrophic fungi. JA and ET are involved in the downstream signal pathway of the defense response of necrotrophic fungi (Glazebrook, 2005). Studies have shown that, after a biotrophic infection, the plant cells in the infected area would accumulate SA in a short time (Duan et al., 2015). The function of plant defense-related TFs has also been reported in recent years. Overexpression of VvZIP60 enhanced grape resistance to PM via the SA signaling pathway (Yu et al., 2019). Meanwhile, overexoression of CmbHLH87 in pumpkin (Guo et al., 2020), HvNAC6 in barley (Chen et al., 2013), and FvWRKY42 (Wei et al., 2018) in strawberry enhanced the resistance to PM as a whole. However, a systematic study of the genes involved in rose early resistance to PM is still lacking. Here we investigated the transcriptome dynamics of rose seedlings following Pp. primary, secondary, and tertiary infection, expecting to dig out more genes related to the resistance of rose to PM. Our aim is to provide a relevant rose gene pool with resistance to powdery mildew in order to improve the quality and the technology foundation, thereby achieving rose varieties resistant to powdery mildew and improving the commodity value of rose. Meanwhile, it is of great theoretical and practical significance to improve the plant disease resistance of powdery mildew by genetic engineering.
Rosa hybrida ‘Samantha’ was propagated by tissue culture (Fang et al., 2021). Rose shoots with at least two leaves were cultured on half-strength Murashige and Skoog (MS) medium supplemented with 0.1 mg L-1 α-naphthaleneacetic (NAA) for 30 days at 22°C under a 16-h/8-h light/dark photoperiod for rooting. The rooted plants were transferred to pots containing peat moss/vermiculite (1:1) and grown at 25/16°C, 16-h/8-h light/dark photoperiod, and 60% humidity. The powdery mildew Podosphaera pannosa, Pp, strain was cultivated with ‘Samantha’ seedlings at 25/16°C and 16-h/8-h light/dark photoperiod. Spore inoculums were prepared by harvesting spores from rose leaves in deionized water. The impurities were removed by centrifugation at 5,000 rmp for 10 min, and the culture was resuspended in distilled water to achieve experimental concentration.
For the RNA-seq samples, the healthy rose seedlings with young leaves (after having been transferred to pots for 4 weeks) are evenly inoculated with powdery mildew spore suspension with a concentration of 5 × 105/ml by spraying method to ensure that each leaf can be inoculated with powdery mildew. All the seedlings were covered with white film to ensure nearly 100% humidity. The seedlings without roots were harvested at 12, 24, and 48 hours post-inoculation (hpi), immediately frozen in liquid nitrogen, and stored at -80°C for further use. For the leaf discs, young stems with three to five pairs of dark red pinnate compound leaves were cut from ‘Samantha’ grown in glasshouses in Nankou, Changping District, Beijing, China, and their stems were immediately placed in water. Rose leaves, after the hormone treatments, were punched into 12.5-mm disks and placed in 0.4% water agar with back-up, at 16 disks per petri dish. Then, each leaf disc was sprayed with 1 × 107/ml powdery mildew spore suspension. The leaf discs were dried at room temperature before the petri dishes were closed. After 48 h of dark treatment, these were switched to a light culture grown at 25/16°C and 16-h/8-h light/dark photoperiod. The lesion sizes were measured at 6, 9, 12, and 15 dpi and analyzed statistically by Student’s t-test.
Total RNA was extracted using the hot borate method as previously described (Wu et al., 2017), and the cultures were treated with RNase-free DNase I (Promega) to remove any contaminating genomic DNA. Two biological repeats were performed for each time point after the infection. Strand-specific RNA libraries were constructed using a protocol described previously (Jiang et al., 2011) and sequenced on the HiSeq2500 system according to the manufacturer’s instructions. The raw reads were deposited in the NCBI SRA database under accession no. PRJNA661227.
Firstly, the raw data was cleaned by removing the adaptor-containing sequences, the poly-N adaptor-containing sequences, and the low-quality reads (-L = 20, -q = 0.5). The clean reads were evaluated by FastQC (Brown et al., 2017). The reference genome of Rosa chinensis ‘Old blash’ (RchiOBHm-V2, GCF_002994745.1) was downloaded from the website (https://lipm-browsers.toulouse.inra.fr/pub/RchiOBHm-V2/) (Raymond et al., 2018). The reference genome index was constructed with Bowtie v2.2.3, and the reads were aligned to the reference genome with TopHat v2.0.12. All genes were annotated by non-redundant protein (NR), NCBI non-redundant transcript (NT), and Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) libraries with e-value ≤10-5. The fragments per kilobase per million reads (FPKM) method was used for the gene expression calculation (Trapnell et al., 2010). Principal component analysis (PCA) was performed using the ggord package in R software. The differentially expressed genes (DEGs) were analyzed by DESeq (Anders et al., 2013) and defined as genes with |log2 fold change (FC)| ≥1, an adjusted P-value <0.05, a false discovery rate of <0.001. The GO and KEGG enrichment analyses of the DEGs were conducted to identify the enriched biological functions using the GOseq R software package (Young et al., 2010) and KOBAS software (Xie et al., 2011).
Leaf stems were cut into 30 cm with three pairs of pinnate compound leaves and individually placed into 100 ml of 50 μM 1-aminocyclopropanecarboxylic acid (ACC) or deionized water as a control. After 24 h of treatment, the leaves were punched into discs.
Leaf stems placed in 100 ml deionized water were exposed to ethylene (10 μl/L), 1-methylcyclopropene (1-MCP, 2 μl/L), or regular air as a control for 24 h. 1M NaOH solution was added to the chambers to prevent CO2 accumulation. The leaves were then punched into discs for inoculation.
The rose leaves were harvested after inoculation for 0, 12, and 24 h and decolorized in the decolorizing solution (ethanol/glacial acetic acid = 1: 3) for 24–48 h until the leaves were bleached. The bleached leaves were stained with 0.05% trypan blue for 3 mins. The stained sections were visualized under an Olympus microscope. At least 4 leaves per time point were observed.
In our previous study, after P. pannosa was infected for 12 h on rose leaves, the spores began to germinate and produce germinating tubes. Therefore, 12 hpi is the initiation of infection. At this time, the germination of spores produced a bud tube that extends into the epidermal cells of the rose leaves, and haustorium formed to obtain nutrients from plants, which is a key time point of initial infection. At 24 hpi, the conidia cluster formed, which means that the fungus was in the stage of asexual propagation. At this point, the second-generation spore was about to mature, and the second infection will occur soon. Accordingly, the third-generation spore will be produced and mature in the next 24 hours ( Supplementary Figure S1 ). Therefore, we chose the points of 0, 12, 24, and 48 hpi samples for transcriptome sequencing. The expression profiles were obtained from rose seedlings infected with P. pannosa. About 195 million clean reads from eight libraries were generated by 150-bp paired-end RNA sequencing. The quality of clean data was evaluated by FastQC. The results showed that the effective rate of each sample was more than 99%, with ~99% Q20, ~95% Q30, and ~46% GC content. The mapping rate of all samples was between 83.78 and 85.23% ( Supplementary Table S1 ). The high quality of the clean data meets the transcriptome analysis requirements. As a result, 51,230 transcripts were identified in each sample. The gene expression level was evaluated by FPKM. The transcripts were classified by FPKM values, as shown in Figure 1A . There were about 19.8% of genes expressed at low levels (0 < FPKM ≤1), ~37.6% at moderate levels (1 < FPKM ≤60), and ~3.4 at high levels (FPKM >60). The FPKM of eight samples representing different infection time points was subjected to PCA. Although the two samples collected in 24 hpi were shown to be more discrete than the others, every two samples collected in one time point were able to cluster together, and the clear separation between different infection time points was detected ( Figure 1B ). The DEGs were determined by DEGseq in comparison with 0 hpi. A total of 1,181 significant DEGs were obtained (the value of FPKM fold change was more than two times, P-value <0.05; Figure 2 ), of which 518, 537, and 615 DEGs were identified at 12, 24, and 48 hpi, respectively. Among the DEGs, 371 genes were upregulated once at least, and 846 genes were downregulated once at least in three points. In total, 94 DEGs showed a differential expression at all three time points, of which 13 were upregulated and 59 were downregulated. The results indicated that, during P. pannosa infection, the rose seedlings downregulated more genes than upregulated them, and the DEGs greatly varied in primary infection, re-infection, and tertiary infection. The qRT-PCR was used to validate the DEGs ( Figure 3 )
TFs are important components in plant defense, involving multiple cell physiological and molecular progress. Among 1,181 DEGs, we have identified 52 TFs involved in rose defense response once at least in three time points, including bHLH, bZIP, C2H2, ERF, HHO, GATA, MYB, NAC, NFY, OFP, PCL, WOX, WAKY, and Znf family members. The ERF family has the most of DEGs, followed by MYB, bHLH, and WRKY family, with 13, 11, 10, and seven DEGs, respectively ( Figure 4A ). There were 22, 15, and 40 TFs in 12, 24, and 48 hpi, respectively. Meanwhile, 80.2% of the TFs had a downregulated expression ( Figure 4B ). The downregulated TFs were sensitive to P. pannosa, and 10 of them were enriched in the KEGG analysis, which was related to the hormone signal transduction pathway and the MAPK signal pathway ( Supplementary Table S3 ).
To investigate the important biological progresses and pathways in rose seedlings resistant to P. pannosa, we annotated all the DEGs based on GO and KEGG databases. A total of 518, 516, and 461 DEGs were enriched with GO terms in biological progress, cellular component, and molecular function, respectively ( Supplementary Figure S2 ). Interestingly, in the KEGG analysis, we have identified plant hormone signal transduction, MAPK signal pathway, starch and sucrose metabolism, etc., to be involved in rose response to P. pannosa ( Figure 5A ). The DEGs were significantly enriched in abscisic acid (ABA), brassinosteroid (BR), ET, gibberellins (GA), auxin (IAA), JA, and SA in the plant hormone signal transduction pathway. More importantly, the expression of DEGs in ET, JA, and GA was opposite to that in SA; they showed a consistently downregulated expression ( Figure 5B ). However, although the ABA-, BR-, and IAA-related DEGs were also enriched, their expression patterns at different time points were not consistent. With the deepening of research on plant hormones, it is generally believed that SA is mainly the downstream signal of defense responding to the biotrophic pathogens, and JA often play opposite roles to SA in plant defense responses (Caarls et al., 2015). In our results, the JA- and SA-related DEGs also play an opposite expression pattern, and the results further suggested that ET may play a particular role in the rose–P. pannosa interaction.
ACC is an ethylene precursor, which is chemically stable and is often used as a substitute for gaseous ET to evaluate plant susceptibility to ethylene. To investigate the role of ET in rose defense response to P. pannosa, a 50-μM-ACC vase treatment of fresh rose leaf stem was carried out for 24 h. The variations of susceptibility to P. pannosa under ACC-pretreated leaves and mock (H2O-treated) leaves were observed at 6, 9, 12, and 15 dpi. The results showed that the ACC-treated rose leaves were more sensitive to P. pannosa than the mock leaves ( Figures 6A, B ). However, the gaseous-ET-pre-treated rose leaves showed no significant susceptibility to P. pannosa. On the contrary, the 1-MCP (the ET inhibitor)-pre-treated leaves showed a strong resistance to P. pannosa ( Figures 6C, D ). The results imply that 1-MCP can be used in the prevention of rose powdery mildew.
PM, caused by P. pannosa, is one of the most common and important fungal diseases of ornamental and horticultural plants around the world. P. pannosa is a biotrophic fungi which can be difficult to cultivate even though it is further studied compared with necrotrophic fungi. In agronomy cultivation, powdery mildew can infect the young leaves of roses, apples, strawberries, and other Rosaceae plants, which can lead to huge economic losses (Debener and Byrne, 2014; Vielba-Fernández et al., 2020). It is hence quite important and meaningful to study and explore the procedure and the mechanism behind Pp. infection on Rosaceae plants’ leaves. Here the rose cultivar ‘Samantha’ and P. pannosa (Pp) strains were used as materials to conduct transcriptome sequencing, and this highlighted massive genes and several hormone signal transduction pathways relevant to the resistance to rose powdery mildew. In recent years, RNA-seq has been applied on several studies of plant–PM interaction, revealing the core DEGs and the biological progress in plant defense response. In this study, we have identified 1,181 DEGs once at least following three Pp. infection time points. Among the 1,181 DEGs, there were 846 downregulated genes and 371 upregulated genes. Consistently, in apple, jointly belonging to Rosaceae, 1,177 DEGs were identified between apple leaves subjected to fungal infection and those grown without pathogens at 12, 24, and 48 hpi (Tian et al., 2019). In pumpkin leaves, they obtained more than 3,000 DEGs after PM was inoculated for 24 and 48 h (Guo et al., 2018). Transcriptional regulation is a central step in plant defense responses. Therefore, for understanding the molecular basis of plant–pathogen interactions, it is critical to elucidate the complex regulatory mechanisms that control defense gene expression among plant species. Here we have found 52 TFs with significantly differential expression, including four major family members (ERF, MYB, bHLH, and WRKY) and other 10 family members ( Figure 4 ). Previous studies have shown that WRKY family members are involved in the regulation of plant disease resistance as well as in the regulation of transcriptional reprograming associated with plant immune responses (Eulgem and Somssich, 2007; Buscaill and Rivas, 2014). However, we identified ERF members as the most common in the TF family, similar to our previous study of rose petal defense response to Botrytis cinerea (Liu et al., 2018). The results indicated that ERF family members played an important role in rose defense response to both biotrophic and necrotrophic fungus. In recent years, there are more and more studies that show that ERF family members acted as a positive regulator in plant resistance to PM (Xing et al., 2017; Li et al., 2021; Zhang et al., 2021) and to grey mold (Pré et al., 2008; Catinot et al., 2015; Li et al., 2020). The KEGG analysis demonstrated that most of the DEGs were enriched in plant hormone signal transduction pathway, including ABA-, AUX-, BR-, ET-, GA-, JA-, and SA-related genes. Although only one DEG was identified in the SA signal pathway, the expression pattern of this gene (RchiOBHm_Chr6g0247671) was opposite to that of the DEGs (RchiOBHm_Chr7g0187141, RchiOBHm_Chr1g0360811, RchiOBHm_Chr2g0146371, and RchiOBHm_Chr4g0429271) related to the JA pathway ( Figure 5 ). Various research have pointed out that SA and JA form the basic bone of plant immunity system (De Vleesschauwer et al., 2013). It is generally believed that SA is thought to mediate defense signaling in response to biotrophic and hemibiotrophic pathogens, while JA and ET are associated with defense responses to necrotrophs, and these two pathways work in an antagonistic manner (Caarls et al., 2015). In addition, SA can inhibit a series of JA response genes (such as PDH1.2) and JA biosynthesis-related genes (LOX2/AOS/AOC2/OPR3) (Leon-Reyes et al., 2010). In this study, four DEGs were found in the ET signaling pathway. Interestingly, all of the four DEGs were downregulated during Pp. infection ( Figure 5 ). These results indicated that ET may play a negative role in rose defense response to Pp. Ethylene is a gaseous plant hormone, which is involved in regulating the physiological and biochemical processes of many plants, including seed germination, plant growth, fruit ripening, organ abscission, and aging (Schulzelefert and Vogel, 2000). In addition, when plants are attacked by pathogens and herbivores, ethylene also plays an important role in plant defense system (Broekaert et al., 2006; Broekgaarden et al., 2015). ACC is the premise of ethylene synthesis to replace ethylene and added hormones to water agar to ensure the continuous supply of ethylene. The results showed that the treatment group had a later onset than the control group, had a significant difference at the time of inoculation for 6 days, then exceeded the control group (H2O), and reached a significant difference at the time of inoculation for 15 days ( Figures 6A, B ). While we first found that 1-MCP, a gas ethylene inhibitor, can significantly improve the disease resistance of rose leaves after 9 dpi, gas ET treatment showed increased resistance at 9 dpi and gradually approached the control group at 15 dpi ( Figures 6C, D ). We speculated that the different phenotype between ACC and gas ET treatment may be due to the fact that the gas ethylene treatment in a short day cannot play a role in the detached leaves continuously. The continuous energy supply of ACC keeps producing gas ethylene, which makes the ethylene concentration in the inoculated environment higher and higher. Therefore, based on the above-mentioned results, we clarified that 1-MCP could be a candidate for exogenous chemical agents for the economic and sustainable improvement of rose resistance to PM.
In conclusion, this study focused on rose early defense response to powdery mildew and identified 1,181 DEGs during infection. In total, 52 differentially expressed TFs, especially ERF, MYB, bHLH, and WRKY family members, consisted of the core regulatory factor network. Simultaneously, besides SA and JA, the KEGG enrichment highlighted the ET signaling pathway in the regulation of rose leaves’ resistance. The application test of 1-MCP, an ethylene inhibitor, showed that 1-MCP played a positive role in rose resistance to PM.
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/, PRJNA661227.
XL and PF performed the experiments. XL, PF, XiaC, and ZW analyzed the data. XL, XQC, and ZZ complemented the writing of the manuscript. XiC and ZZ planned the project, designed and supervised the experiments, and coordinated the collaboration of the authors. All authors contributed to the article and approved the submitted version.
This work was supported by the National Natural Science Foundation of China (grant number 31501791), and the Construction of Beijing Science and Technology Innovation and Service Capacity in Top Subjects (CEFF-PXM2019_ 014207_000032) to ZZ. This study was further sponsored by the Natural Science Foundation of Jiangsu Province (BK20191224) and supported by the project of Jiangsu Vocational College of Agriculture and Forest (2019kj005) to XC, also the China Postdoctoral Science Foundation (2022M713391) to XL.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9551410 | 36177898 | Wujun Wei,Cheng Lin,Rentong Hu,Jingjing Huang,Xiaohao Chen,Lv Zhou,Jiazhu Wei,Yi-Bin Deng,Chun-Fang Wang | LOC102553417 silencing facilitates the apoptosis of hepatic stellate cells via the miR-30e/MTDH axis | 29-09-2022 | long non-coding RNA LOC102553417,microRNA-30e,metadherin,hepatic stellate cell,hepatic fibrosis | Hepatic fibrosis is an inevitable pathological process in the progression of multiple chronic liver diseases and remains a major challenge in the treatment of liver diseases. The purpose of the present study was to demonstrate whether silencing of the long non-coding RNA LOC102553417 promoted hepatic stellate cell (HSC) apoptosis via the microRNA (miR)-30e/metadherin (MTDH) axis. A LOC102553417 silencing lentivirus was constructed and transduced into HSC-T6 cells. After confirming the silencing efficiency by reverse transcription-quantitative PCR, cell proliferation was assessed using the Cell Counting Kit-8 assay and apoptosis was assessed using flow cytometry. The interaction between LOC102553417 and miR-30e, and that between miR-30e and MTDH, was demonstrated using the dual-luciferase reporter assay and RNA binding protein immunoprecipitation. The apoptosis of HSC-T6 cells was detected after transfection of miR-30e mimics and inhibitors with or without silencing LOC102553417. Silencing of LOC102553417 curbed HSC-T6 cell proliferation and expedited their apoptosis. LOC102553417 was demonstrated to target miR-30e, whereas miR-30e targeted MTDH. In addition, LOC102553417 silencing significantly upregulated miR-30e expression levels, and significantly downregulated MTDH mRNA and protein expression levels, which resulted in a significantly reduced p-Akt/Akt ratio and significantly elevated p53 protein expression levels. Transfection with miR-30e mimic alone significantly enhanced HSC-T6 cell apoptosis and inhibits LOC102553417 and MTDH expressions, In addition, miR-30e mimic expedites the apoptosis of HSCs stimulated by LOC102553417 silencing; consistent results were obtained by reverse validation of miR-30e inhibitor. In conclusion, the present study demonstrated that LOC102553417 silencing stimulated the apoptosis of HSCs via the miR-30e/MTDH axis. | LOC102553417 silencing facilitates the apoptosis of hepatic stellate cells via the miR-30e/MTDH axis
Hepatic fibrosis is an inevitable pathological process in the progression of multiple chronic liver diseases and remains a major challenge in the treatment of liver diseases. The purpose of the present study was to demonstrate whether silencing of the long non-coding RNA LOC102553417 promoted hepatic stellate cell (HSC) apoptosis via the microRNA (miR)-30e/metadherin (MTDH) axis. A LOC102553417 silencing lentivirus was constructed and transduced into HSC-T6 cells. After confirming the silencing efficiency by reverse transcription-quantitative PCR, cell proliferation was assessed using the Cell Counting Kit-8 assay and apoptosis was assessed using flow cytometry. The interaction between LOC102553417 and miR-30e, and that between miR-30e and MTDH, was demonstrated using the dual-luciferase reporter assay and RNA binding protein immunoprecipitation. The apoptosis of HSC-T6 cells was detected after transfection of miR-30e mimics and inhibitors with or without silencing LOC102553417. Silencing of LOC102553417 curbed HSC-T6 cell proliferation and expedited their apoptosis. LOC102553417 was demonstrated to target miR-30e, whereas miR-30e targeted MTDH. In addition, LOC102553417 silencing significantly upregulated miR-30e expression levels, and significantly downregulated MTDH mRNA and protein expression levels, which resulted in a significantly reduced p-Akt/Akt ratio and significantly elevated p53 protein expression levels. Transfection with miR-30e mimic alone significantly enhanced HSC-T6 cell apoptosis and inhibits LOC102553417 and MTDH expressions, In addition, miR-30e mimic expedites the apoptosis of HSCs stimulated by LOC102553417 silencing; consistent results were obtained by reverse validation of miR-30e inhibitor. In conclusion, the present study demonstrated that LOC102553417 silencing stimulated the apoptosis of HSCs via the miR-30e/MTDH axis.
Hepatic fibrosis (HF) is an important health condition linked to chronic liver injury and HF is a disease associated with high morbidity (1). HF is a pathological process involving structural or functional abnormalities of the liver mainly attributed to the excessive accumulation of extracellular matrix components in hepatic tissues, which can lead to liver cirrhosis and liver cancer (2). The morbidity and mortality of HF-induced liver cirrhosis and liver cancer rank sixth globally and are increasing year-on-year in China (3). Previous studies reported that drugs for liver fibrosis treatment mainly inhibit hepatocyte apoptosis (emricasan) (4) and hepatic stellate cell (HSC) activation (PRI-724) (5), reduce fibrotic scar evolution and contraction (simtuzumab) (6), and regulate the immune response (cenicriviroc) (7). However, there is currently a lack of effective strategies and drugs to directly treat this disease (8,9). Numerous studies have demonstrated that the initiation and development of HF are primarily elicited by factors including viral infections, alcohol toxins and metabolites (Such as cholesterol). Furthermore, the activation and proliferation of HSCs also serve as key drivers of HF (10,11). HSC activation is a complicated process controlled by multiple molecules and signaling pathways (12), yet its underlying mechanisms remain largely undetermined. Exploring the molecular mechanisms related to the function of HSCs in order to identify new diagnostic and therapeutic molecular targets could be instrumental in developing new possibilities for the treatment of HF. Long non-coding (lnc)RNAs are a set of non-protein-coding transcripts with a length of over 200 nt (13). A better understanding of HF could support the use of novel concepts and avenues in the targeted therapy of HF (14). A recent study by Zhang et al (15) reported that lnc-Lfar1 was closely associated with HF and modulated the macrophage activation evoked via lipopolysaccharide and IFN-γ to influence the occurrence and development of fibrosis via the NF-κB signaling pathway. Furthermore, Liao et al (16) recently reported that the lncRNA Gpr137b-ps could bind to and impair microRNA (miRNA/miR)-200a-3p causing inhibition of chemokine (C-X-C motif) ligand 14, which may promote the pathological process of HF via alteration of the activation and proliferation of HSCs. A whole-transcriptome sequencing analysis by Gong et al (17) revealed that lncRNA LOC102553417 (Genbank ID: XR_595047) was expressed at a high level in a rat carbon tetrachloride-induced HF model. LOC102553417 is a lncRNA of rats, which can be queried through the UCSC database (genome-asia.ucsc.edu). However, the role of LOC102553417 in the occurrence and development of HF remains undetermined. In the present study, LOC102553417 silencing was used to investigate its role in HSC activation via the miR-30e/metadherin (MTDH) axis. An in-depth understanding of the functions and mechanisms of LOC102553417 in HF could provide a theoretical basis for the clinical use of LOC102553417 as a diagnostic biomarker and treatment for HF.
The rat HSC-T6 cell line was purchased from The Cell Bank of Type Culture Collection of The Chinese Academy of Sciences. Cells were cultured at 37°C with 5% CO2 in DMEM (cat. no. PM150210; Procell Life Science & Technology Co., Ltd.), which was supplemented with 10% fetal bovine serum (cat. no. 164210-500; Procell Life Science & Technology Co., Ltd.) and 1% penicillin-streptomycin (cat. no. PB180120; Procell Life Science & Technology Co., Ltd.). The cells were passaged at a 1:3 ratio and the medium was renewed three times per week. For TGF-β1 induction, HSC-T6 cells were stimulated with 10 ng/ml TGF-β1 (cat. no. HY-P7118; MedChemExpress) for 24 h at 37°C or treated with an equal amount of double-distilled H2O as the control.
The LOC102553417 silencing lentiviral vector (vector no. GV492) was constructed by Guangzhou Anernor Biotechnology Co., Ltd. Briefly, GV492 plasmid vector (100 nM) and packaging plasmid (psPaX2; third generation lentiviral packaging system (vector: packaging vector: envelope ratio, 10:3:1; Promega Corporation) were mixed with lipo3000 (L3000-015; Invitrogen; Thermo Fisher Scientific, Inc.) were co-transfected into 1×106 293T cells (Cell Bank of the Chinese Academy of Sciences). When 293T cells were cultured for 4 days, the cell supernatant was collected, and then the collected cell supernatant was centrifuged at 251.55 × g for 5 min at 4°C, and the supernatant was filtered with a 0.22 µm membrane. The targeting sequences used for the knockdowns (KDs) and negative control (NC, non-targeting.) were as follows: KD1, 5′-GACCCTGCATCAGAGTCTTCCAGA-3′; KD2, 5′-GGACTCTTCCTGGACTACCATAAAT-3′; KD3, 5′-CATACATGCTAGGGCAGCCATTGCA-3′; and NC, 5′-TTCTCCGAACGTGTCACGT-3′. HSC-T6 cells were transduced at 37°C (multiplicity of infection, 30) for 96 h and green fluorescence was observed via fluorescence microscopy to demonstrate transduction (data not shown). LOC102553417 expression was determined via reverse transcription-quantitative (RT-q)PCR. The vector with the highest silencing efficiency was used for subsequent experimentation at 24 h post-transduction. The miR-30e mimic (sense, 5′-UGUAAACAUCCUUGACUGGAAG-3′, double chain; antisense 5′-CUUCCAGUCAAGGAUGUUUACA-3′), miR-30e inhibitor (5′-CUUCCAGUCAAGGAUGUUUACA-3′), mimic NC (5′-UUUGUACUACACAAAAGUACUG-3′) and inhibitor NC (5′-CAGUACUUUUGUGUAGUACAAA-3′) vectors were synthesized by Huzhou Hippo Biotechnology Co., Ltd. Lipofectamine® 3000 kit (cat. no. L3000015; Invitrogen; Thermo Fisher Scientific, Inc.) was employed for transfection(final concentration of nucleic acid: 20nM, cell density, 50%, 37°C) for 48 h, subsequent experiments were performed 48 h after transfection.
TRIzol® reagent (cat. no. 15596-026; Invitrogen; Thermo Fisher Scientific, Inc.) was used to extract total cellular RNA. RT-PCR was performed using an RT-PCR kit (cat. no. RT-02011; Chengdu Foregene Biotechnology Co., Ltd.), which consisted of 10 µl SYBR-Green Mix, 2 µl forward (F) primer, 2 µl reverse (R) primer, 1 µl cDNA and 5 µl RNase-free deionized water. After the purity and concentration tests, RNA was reverse transcribed into cDNA (70°C, 5 min; 42°C, 60 min; 70°C, 10 min). Primer Premier 5.0 software (Premier, Inc.) was employed for primer design; each primer was composed of 20–22 bases and the product size was 70–200 bp. The reaction conditions were set as follows: Pre-denaturation for 15 sec at 95°C; 40 cycles of denaturation for 5 sec at 95°C, annealing and extension at 60°C for 30 sec; and for the melting curve, amplification at 55–95°C for 10 sec (81 cycles in total). Three parallel wells were used for each group with a blank control and a NC group at the same time. After determining the cycle threshold, the relative expression of the target gene normalized to the internal control(GAPDH was used for lncRNA and mRNA, U6 was used for miRNA) was calculated using 2−ΔΔCq analysis (18). The primer sequences were synthesized by Sangon Biotech Co., Ltd. as follows: LOC102553417 (F), AGTCCTGCCCACACTGCTTTT; LOC102553417 (R), AACAGAGGCCTGAAATAGAC; MTDH (F), AGCGGGAGGAGGTGACCCCGCC; MTDH (R), ATTTGGTTTGGGCTTTTCA; miR-30e-RT, GTCGTATCCAGTGCAGGGTCCG AGGTATTCGCACTGGATACGACCTTCCAGT; miR-30e (F), GCCGAGTGTAAACATCCT; miR-30e (R), GTCGTATCCAGTGCGAATAC; GAPDH (F), TGTGAACGGATTTGGCCGTA; GAPDH (R), GATGGTGATGGGTTTCCCGT; U6 (F), CTCGCTTCGGCAGCACA; and U6 (R), AACGCTTCACGAATTTGCGT.
Cells were lysed using RIPA lysis buffer (cat. no. P0013B; Beyotime Institute of Biotechnology). Following homogenization, lysis and centrifugation at 200 × g for 5 min at 4°C, total protein was extracted and the concentration was assessed using the BCA method. Following separation via SDS-PAGE (5% stacking gel, 12% running gel, 20 µg total protein per lane). Electrophoresed proteins were transferred to a PVDF membrane (constant current of 200 mA for 1 h and a constant current of 250 mA for 2 h). The membrane was then blocked with TBS-Tween (Tween 0.1% in TBS) solution containing 5% skimmed milk powder for 1 h and was incubated with primary antibodies against the following proteins: Akt (1:500; cat. no. ab18785; Abcam), phosphorylated (p)-Akt (1:500; cat. no. ab8933; Abcam), p53 (1:333; cat. no. ab26; Abcam), MTDH (1:10,000; cat. no. ab124789; Abcam), β-actin (1:20,000; cat. no. 66009-1-Ig; ProteinTech Group, Inc.), Cleaved Caspase-3 (1:500; cat. no. ab32042; Abcam) and caspase-3 (1:1,000; cat. no. 19677-1-AP; ProteinTech Group, Inc.). After 1 h of agitation at room temperature, overnight incubation was performed with the primary antibodies at 4°C. After washing, the membrane was incubated with a secondary antibody (HRP; anti-rabbit 1:5000, cat. no. 074-1506; anti-mouse 1:5000, cat. no. 074-1807; KPL, Inc.) for 1 h at 37°C. The bands were visualized using ECL kit (P0018S; Beyotime Institute of Biotechnology), followed by pressing, exposure and fixation. Grayscale analysis of the images was performed using ImageJ software 1.8.0 (National Institutes of Health).
HSC-T6 cell suspension was prepared and seeded onto a 96-well plate (100 µl/well) at 1×103 cells/well with three parallel wells for each group. On each of 5 consecutive days, 10 µl CCK-8 reagent (cat. no. FC101-03; TransGen Biotech Co., Ltd.) was added to each well. Following incubation in 37°C and 5% CO2 incubator for 2 h, absorbance was quantified at 450 nm using an ELx800 Absorbance Microplate Reader (BioTek Instruments Inc.).
HSC-T6 cells were transferred directly into a 10-ml centrifuge tube at 106/ml cells per sample, total 1ml. Following centrifugation at 200 × g for 5 min, the supernatant was discarded. Subsequently, cells (100 µl) were suspended in a 5 ml flow tube and incubated with 5 µl Annexin V-PE and 5 µl PI (cat. no. 640914; Biolegend, Inc.) at ambient temperature for 15 min. The samples were then loaded onto a CytoFLEX Flow Cytometer (Beckman Coulter, Inc.) for apoptosis analysis with FlowJo Software V10 (FlowJo, LLC).
It has been reported that miR-30e is a miRNA associated with HF using the RegRNA2 database (regrna2.mbc.nctu.edu.tw/) (19), predicted that wild-type (WT) LOC102553417 contained a binding site with miR-30e. The binding site was mutated into the original complementary sequence and designed as LOC102553417 mutant (MUT). The TargetScan database, version 8.0 (http://www.targetscan.org/vert_80/) was used to identify potential target genes selecting the total context++ score <-0.8, aggregate PCT ≥90 and selecting for genes that have been reported to be related to liver disease. miR-30e was predicted to have a binding site with MTDH and based on the binding site, the binding site was mutated into the original complementary sequence and designed as MTDH MUT.
Log-phase HSC-T6 cells were seeded into a 24-well plate and cultured for 24 h. Cell transfection by lipo3000 (L3000-015; Invitrogen; Thermo Fisher Scientific, Inc.) was performed using MTDH 3′UTR or LOC102553417 (wild or mutant type) psicheck2 luciferase reporter gene plasmid (Shanghai Genechem Technology Co., Ltd), Renilla control plasmid, aforementioned miR-30e mimic or mimic-NC. Three parallel wells were used in each group. After culture at 37°C and 5% CO2 for 24 h, the medium was discarded and the residual medium was removed via two washes in ice-cold PBS. Immediately following transduction, activity measurement was performed. According to the manufacturers' protocol, 100 µl 1X Passive Lysis Buffer from the Dual-Luciferase Reporter Assay System kit (cat. no. E1910; Promega Corporation) was added to each well. Following gentle shaking, the cells were maintained at ambient temperature for 15 min. The lysate (20 µl) was placed into a 96-well plate and the luminescence was quantified using a Lux-T020 Ultra-sensitive Tube Luminometer (Guangzhou Biolight Biotechnology Co., Ltd.) for statistical analysis of relative luciferase activity normalized to Renilla luciferase activity.
According to the manufacturer's instructions of RIP kit (cat. no. Bes5101; Guangzhou Boxin Biotechnology Co., Ltd.), RIP buffer and Argonaute RNA-induced silencing complex catalytic component 2 (Ago2) antibodies 3ug (cat. no. ab233727; Abcam) were equilibrated at ambient temperature for 10 min. The harvested HSC-T6 cells were lysed with RIP lysis buffer at 4°C for 10 min, washed with 2 ml PBS and centrifuged at 200 × g for 5 min at room temperature to collect cell lysate. The cell lysate (100 µl) was incubated with RIP buffer (900 µl) containing antibody-labeled A + G magnetic beads (20 µl) at 4°C for 16 h (overnight). IgG (cat. no. ab172730; Abcam) served as a NC and the supernatant was harvested as ‘Input’ as a control. The immunoprecipitated complex was isolated and detached with 150 µl proteinase K buffer to isolate the RNA at 55°C for 1 h. RT-qPCR was employed to analyze the relative expression of miR-30e and LOC102553417 as aforementioned.
All experimental data were analyzed using Prism 8.0 software (GraphPad Software Inc.). Statistics was obtained from three repeat experiments. Data are presented as the mean ± standard deviation. Comparisons between two groups were performed using unpaired Student's t-test, whereas one-way ANOVA followed by Tukey's post-hoc test was used for comparisons among three or more groups. P<0.05 was considered to indicate a statistically significant difference.
To ascertain the importance of LOC102553417 in the activation of HSCs, the mRNA expression levels of LOC102553417 after TGF-β1-triggered activation of HSC-T6 cells were determined using RT-qPCR. LOC102553417 mRNA expression levels in the TGF-β1-induced group were significantly higher compared with those in the control group (P<0.001; Fig. 1A). Post-transduction of HSC-T6 cells with LOC102553417 silencing vectors and NC vector, LOC102553417 mRNA expression levels were assessed via RT-qPCR. The mRNA expression levels of LOC102553417 in the KD1 group (0.20±0.02), KD2 group (0.12±0.01) and KD3 group (0.16±0.01) were all significantly downregulated compared with those in the NC vector group (1.00±0.03; P<0.001). The silencing efficiency of LOC102553417 KD2 was the greatest (Fig. 1B); therefore, KD2 was selected for use in the subsequent experiments. CCK-8 assay demonstrated significantly reduced proliferation of HSCs in LOC102553417-silenced cells compared with in the NC group (P<0.001; Fig. 1C). Furthermore, flow cytometry data demonstrated increased cell apoptosis in LOC102553417-silenced cells compared with in the NC group (P<0.001; Fig. 1D and E).
Using the RegRNA2 database predicted that wild-type (WT) LOC102553417 contained a binding site with miR-30e. MUT LOC102553417 was designed (Fig. 2A. Using the TargetScan predicted that WT MTDH 3′UTR contained a binding site with miR-30e. MUT MTDH 3′UTR was designed (Fig. 2B). The binding of LOC102553417 to miR-30e was demonstrated by the dual-luciferase reporter assay. Luciferase activity was significantly reduced in the LOC102553417-WT + miR-30e mimic compared with that in the LOC102553417-WT + miR-NC group (P<0.01; Fig. 2C). However, the LOC102553417-MUT + miR-30e mimic demonstrated no significant difference in luciferase activity compared with the LOC102553417-MUT + miR-NC group (P>0.05), which demonstrated the binding of LOC102553417 to miR-30e at the aforementioned binding site. The binding of MTDH to miR-30e was also demonstrated using the luciferase assay. Compared with the MTDH-WT + miR-NC group, the MTDH-WT + miR-30e mimic group demonstrated significantly reduced luciferase activity (P<0.01); however the MTDH-MUT + miR-30e mimic group demonstrated no significant difference in luciferase activity compared with the MTDH-MUT + miR-NC group (P>0.05; Fig. 2D), which demonstrated the binding of miR-30e to MTDH at the binding site predicted using TargetScan database. Antibodies to Ago2, a miRNA precursor cleavage protein, were used to conduct RIP experiments to verify the binding of miR-30e to LOC102553417. Compared with in the IgG antibody group (NC antibody), significantly higher expression levels of miR-30e and LOC102553417 were detected in the Ago2 antibody group (P<0.001; Fig. 2E). Subsequently, LOC102553417 was silenced in HSC-T6 cells, the miR-30e and MTDH expression levels were determined via RT-qPCR, and the MTDH protein expression levels were assessed via western blotting. miR-30e relative expression levels in the KD group were significantly elevated compared with those in the NC group (P<0.001; Fig. 2F). MTDH mRNA expression levels (P<0.001; Fig. 2G) and protein expression levels (P<0.001; Fig. 2H and I) were significantly reduced in the LOC102553417 KD group compared with those in the NC group. Western blot analysis of the protein expression levels of p-Akt, Akt, caspase-3, cleaved caspase-3 and p53 was used to assess the downstream mechanism of the LOC102553417/miR-30e/MTDH axis. Western blotting demonstrated significant reductions in the p-Akt/Akt ratio (P<0.001), and significant elevations in p53, caspase-3 and cleaved caspase-3 protein expression levels (P<0.001) in the LOC102553417 KD group compared with those in the NC group.
The present study subsequently focused on whether LOC102553417 could function via the miR-30e/MTDH axis. miR-30e mimic, miR-30e inhibitor, NC-mimic and NC-inhibitor were constructed and transfected into HSC-T6 cells, and the mRNA expression levels of miR-30e, LOC102553417 and MTDH were quantified via RT-qPCR. miR-30e expression levels in the miR-30e inhibitor group were significantly reduced compared with those in the NC-inhibitor group (P<0.001; Fig. 3A); however, LOC102553417 (Fig. 3B) and MTDH (Fig. 3C) expression levels were significantly increased in the miR-30e inhibitor group compared with in the NC-inhibitor group (P<0.001). miR-30e mRNA expression levels were significantly raised in the miR-30e mimic group compared with in the NC-mimic group (P<0.001). Furthermore, the miR-30e mimic resulted in significant reductions in LOC102553417 and MTDH mRNA expression levels compared with in the NC-mimic group (P<0.001). Western blotting demonstrated that MTDH protein expression levels were significantly elevated in the miR-30e inhibitor group compared with in the NC-inhibitor group (P<0. 001; Fig.3D and E); however, they were significantly reduced in the miR-30e mimic group compared with in the NC-mimic group (P<0.001) (Fig. 3D and E). Apoptosis analysis demonstrated that the apoptotic rate was significantly suppressed following miR-30e inhibitor transfection compared with that in the NC-inhibitor group (P<0.001; Fig. 3F and G). Furthermore, a significant increase in apoptotic rate was demonstrated after miR-30e mimic transfection compared with the NC-mimic (P<0.001). Compared with LOC102553417 silencing (NC-inhibitor + KD-LOC102553417), simultaneous miR-30e inhibitor and LOC102553417 silencing (miR-30e inhibitor + KD-LOC102553417) demonstrated a significantly reduced apoptotic rate (P<0.001), whereas simultaneous miR-30e mimic and LOC102553417 silencing (miR-30e mimic + KD-LOC102553417) demonstrated a significant enhancement in the apoptotic rate compared with NC-mimic + KD-LOC102553417 (P<0.001) (Fig. 3H and I). These findings indicate miR-30e inhibits LOC102553417 and MTDH expression levels and expedites the apoptosis of HSCs in which LOC102553417 is knocked down.
HF is a dynamic process that manifests through extracellular matrix accumulation triggered by chronic liver injury of any etiology, including viral infection, alcoholic liver disease and nonalcoholic steatohepatitis (12). Activation of HSCs is a crucial event in HF, and their proliferation and apoptosis are highly relevant to the initiation and development of HF (20). Previous studies have reported that the proliferation of HSCs can drive the initiation of HF and stimulating HSC apoptosis could ameliorate HF (21,22). The present study demonstrated that silencing LOC102553417 contributed to the significant suppression of HSC-T6 cell proliferation and the significant enhancement of their apoptotic rate. Therefore, it could be hypothesized that LOC102553417 may be a driver of HF, which agrees with a previous finding that LOC102553417 was highly expressed in a rat model of HF (17), and that targeting LOC102553417 could be a potential strategy to treat HF. The gene encoding MTDH is located on the long arm of human chromosome 8 (8q22) in region 22, with a molecular weight of ~64 kDa and has previously been reported as an miR-30e-5p target gene (23). MTDH can facilitate hepatocarcinogenesis and cancer progression (24); in addition, abnormal expression of miR-30a-5p can impede the proliferative function of liver cancer cells and enhance their apoptosis via targeting of the MTDH/PTEN/AKT pathway (25). MTDH knockout has been shown to impair the proliferation and accelerate the apoptosis of hepatocellular carcinoma cells via the PTEN/AKT pathway (26); however, the significance of MTDH in HF is rarely reported. Previous studies have reported that miR-30e is abnormally expressed in liver injury and hepatocellular carcinoma (27,28). Furthermore, hepatitis B virus X protein may promote the development of liver fibrosis and hepatoma through the downregulation of miR-30e, which targets prolyl 4-hydroxylase subunit α2 (29). Moreover, human antigen R has been reported to be involved in sphingosine 1-phosphate (S1P)-induced bone marrow mesenchymal stem cell migration and can increase the stabilization of S1P receptor 3 mRNA by competing with miR-30e to regulate liver fibrosis (30). The present study demonstrated that LOC102553417 loss-of-function expedited HSC apoptosis by inhibiting MTDH expression through competitively binding to miR-30e, which could be a key mechanism responsible for the action of LOC102553417 on HSCs, which drive HF. The combination of the miR-30e inhibitor and KD-LOC102553417 significantly inhibited apoptosis. The results of the present study demonstrated that the miR-30e inhibitor significantly decreased the apoptotic rate and that silencing of LOC102553417 significantly promoted apoptosis. Furthermore, miR-30e could competitively bind to LOC102553417 and when the miR-30e inhibitor inhibited the expression of miR-30e, thus reducing the binding of miR-30e to LOC102553417, the expression of LOC102553417 was significantly increased and the cell apoptotic rate was significantly reduced. Moreover, miR-30e inhibits LOC102553417 and MTDH expression levels, and expedites the apoptosis of HSCs in which LOC102553417 is knocked down. These results further indicate that the three factors have a mutual regulatory relationship in the apoptosis of hepatic stellate cells. Akt is a serine/threonine protein kinase. Activation of the Akt signaling pathway mainly depends on the activity of PI3K, which can be stimulated by JAK1 and CD19. Akt phosphorylation is essential for Akt activation and subsequent PI3K/Akt signaling pathway activation (31–33). Akt phosphorylates downstream targets to block cell apoptosis (34). A recent study reported that activation of the PI3K/AKT/MDM2 signaling pathway could degrade p53, inhibiting apoptosis (35). p53 is a key tumor suppressor that suppresses cell proliferation and induces apoptosis. It predominantly maintains body homeostasis via diverse regulatory mechanisms, including mediating DNA repair, impeding cell proliferation, stimulating apoptosis and boosting metabolism (36,37). The results of the present study demonstrated that LOC102553417 silencing significantly increased apoptotic rate, significantly reduced Akt protein phosphorylation and significantly upregulated p53 protein expression levels. Furthermore, the present study demonstrated that LOC102553417 silencing could enhance Akt protein phosphorylation via the miR-30e/MTDH signaling pathway. This may be the downstream pathway of the LOC102553417-mediated miR-30e/MTDH axis affecting the apoptosis of HSCs. Notably, the present study has certain limitations. Firstly, the significantly upregulated LOC102553417 expression in clinical HF samples and its clinical significance were not verified. Furthermore, the present study was only performed on rat HSCs and needs to be further explored and verified in human cells and clinical samples. Secondly, an HF cell model was not established to validate the in vivo function and mechanism of LOC102553417. Thirdly, pathway inhibitors were not utilized to verify the downstream pathways of the LOC102553417/miR-30e/MTDH axis; therefore, an in-depth exploration of their interaction is warranted in the future. In conclusion, the present study demonstrated that silencing LOC102553417 reinforced HSC apoptosis via the miR-30e/MTDH axis, which could be a crucial regulatory mechanism in HF and may provide a theoretical basis for HF-targeted therapy. | true | true | true |
PMC9551565 | Jingping Fang,Xiuming Xu,Qinchang Chen,Aiting Lin,Shaoqing Lin,Wen Lei,Cairong Zhong,Yongji Huang,Yongjin He | The complete mitochondrial genome of Isochrysis galbana harbors a unique repeat structure and a specific trans-spliced cox1 gene | 27-09-2022 | haptophytes,Isochrysis galbana,mitochondrial genome,comparative analysis,trans-splicing,RNA editing | The haptophyte Isochrysis galbana is considered as a promising source for food supplements due to its rich fucoxanthin and polyunsaturated fatty acids content. Here, the I. galbana mitochondrial genome (mitogenome) was sequenced using a combination of Illumina and PacBio sequencing platforms. This 39,258 bp circular mitogenome has a total of 46 genes, including 20 protein-coding genes, 24 tRNA genes and two rRNA genes. A large block of repeats (~12.7 kb) was segregated in one region of the mitogenome, accounting for almost one third of the total size. A trans-spliced gene cox1 was first identified in I. galbana mitogenome and was verified by RNA-seq and DNA-seq data. The massive expansion of tandem repeat size and cis- to trans-splicing shift could be explained by the high mitogenome rearrangement rates in haptophytes. Strict SNP calling based on deep transcriptome sequencing data suggested the lack of RNA editing in both organelles in this species, consistent with previous studies in other algal lineages. To gain insight into haptophyte mitogenome evolution, a comparative analysis of mitogenomes within haptophytes and among eight main algal lineages was performed. A core gene set of 15 energy and metabolism genes is present in haptophyte mitogenomes, consisting of 1 cob, 3 cox, 7 nad, 2 atp and 2 ribosomal genes. Gene content and order was poorly conserved in this lineage. Haptophyte mitogenomes have lost many functional genes found in many other eukaryotes including rps/rpl, sdh, tat, secY genes, which make it contain the smallest gene set among all algal taxa. All these implied the rapid-evolving and more recently evolved mitogenomes of haptophytes compared to other algal lineages. The phylogenetic tree constructed by cox1 genes of 204 algal mitogenomes yielded well-resolved internal relationships, providing new evidence for red-lineages that contained plastids of red algal secondary endosymbiotic origin. This newly assembled mitogenome will add to our knowledge of general trends in algal mitogenome evolution within haptophytes and among different algal taxa. | The complete mitochondrial genome of Isochrysis galbana harbors a unique repeat structure and a specific trans-spliced cox1 gene
The haptophyte Isochrysis galbana is considered as a promising source for food supplements due to its rich fucoxanthin and polyunsaturated fatty acids content. Here, the I. galbana mitochondrial genome (mitogenome) was sequenced using a combination of Illumina and PacBio sequencing platforms. This 39,258 bp circular mitogenome has a total of 46 genes, including 20 protein-coding genes, 24 tRNA genes and two rRNA genes. A large block of repeats (~12.7 kb) was segregated in one region of the mitogenome, accounting for almost one third of the total size. A trans-spliced gene cox1 was first identified in I. galbana mitogenome and was verified by RNA-seq and DNA-seq data. The massive expansion of tandem repeat size and cis- to trans-splicing shift could be explained by the high mitogenome rearrangement rates in haptophytes. Strict SNP calling based on deep transcriptome sequencing data suggested the lack of RNA editing in both organelles in this species, consistent with previous studies in other algal lineages. To gain insight into haptophyte mitogenome evolution, a comparative analysis of mitogenomes within haptophytes and among eight main algal lineages was performed. A core gene set of 15 energy and metabolism genes is present in haptophyte mitogenomes, consisting of 1 cob, 3 cox, 7 nad, 2 atp and 2 ribosomal genes. Gene content and order was poorly conserved in this lineage. Haptophyte mitogenomes have lost many functional genes found in many other eukaryotes including rps/rpl, sdh, tat, secY genes, which make it contain the smallest gene set among all algal taxa. All these implied the rapid-evolving and more recently evolved mitogenomes of haptophytes compared to other algal lineages. The phylogenetic tree constructed by cox1 genes of 204 algal mitogenomes yielded well-resolved internal relationships, providing new evidence for red-lineages that contained plastids of red algal secondary endosymbiotic origin. This newly assembled mitogenome will add to our knowledge of general trends in algal mitogenome evolution within haptophytes and among different algal taxa.
The haptophyte microalgae are typically single-celled phytoplankton with tiny cell size (2–20 μm) that live ubiquitously in the photic zone of the oceans and freshwater bodies. As main primary producers, the haptophytes alone may represent 30%–50% of marine photosynthetic biomass, playing a pivotal role in global CO2 fixation in a variety of aquatic ecosystems (Liu et al., 2009). Haptophytes and other three distinct and distantly related lineages including cryptophytes, alveolates, stramenopiles (heterokonts) contained red algal secondary-derived plastids. These four groups were once collectively known as the chromalveolates or CASH based on a uniting biological feature of plastids, but their evolutionary history had long been a bone of contention (Cavalier-Smith, 1999; Petersen et al., 2014; Ponce-Toledo et al., 2019). Recently the monophyly of CASH was overturned by addition of other previously unrelated groups: alveolates and stramenopiles branches with rhizarians forming SAR supergroup (Keeling and Burki, 2019), even T-SAR clade with the subsequent addition of telonemids (Strassert et al., 2019); haptophytes have merged with centrohelids to form Haptista supergroup while cryptophytes saw a coalescence of a few lineages (Palplitomonas and katablepharids) around them to form Cryptista (Keeling and Burki, 2019), even the newly proposed clade Pancrytista plus Microheliella maris (Yazaki et al., 2022). With the maturation of genomic methods and uncovering of new species, clarifying and confirming the phylogenetic positions of these major eukaryotic lineages will continue, which will facilitate the better understanding of distant and murky past of early evolution. Mitochondria are known as the “powerhouse” of the eukaryotic cell as they are the site of aerobic respiration, generating energy-rich adenosine 5′-triphosphates (ATPs) that can be used to fuel the metabolic activities of organisms. About 1.4 billion years ago, mitochondria evolved through endosymbiosis, where free-living single-celled α-proteobacteria ancestors were engulfed by primitive cells and integrated into the host cell (Youle, 2019). Over the course of evolution, the endosymbiont “domestication” in the host cell involved a drastic reduction of genome size and coding capacity resulting from gene loss or massive early non-linear endosymbiont-to-nucleus gene migration events. This process of gene transfer to the nucleus occurred in waves of exponential reduction, in parallel and independently with lineage-specific rates, thus leading to multiple origins of mitochondria and varying degrees of gene retention (Janouškovec et al., 2017). The drastic elimination of redundant genes led to only 0.5%–1.2% of the initial gene repertories retained in present-day mitochondrial genomes (hereafter, mitogenomes; Burger et al., 2013). Mitogenomes in eukaryotes are in every shape and size, with large variations in size, genome architecture, gene order and content, the mobile genetic elements and repeat structure (Smith and Keeling, 2015; Nishimura et al., 2019). Compared with the small compact circular animal mitogenomes (36–37 genes), land-plant and algal mitogenomes possess a puzzling array of genome architectures: large in size and complex in non-coding regions with varying gene number. The most eubacteria-like and gene-rich eukaryotic mitogenomes reported to date are that of jakobids members, which harbor up to 100 genes (including 61–69 protein-coding genes; Burger et al., 2013). Conversely, apicomplexans and their relatives possess the smallest mitogenomes (~6 kb in size) with merely 3–5 genes (Flegontov et al., 2015). In spite of the ecological and phylogenetic importance of haptophytes microalgae, advances in haptophytes genomics have lagged behind other major algal lineages due to the difficulty in excluding the contaminations of its symbiotic bacteria. As of 2016, around 312 haptophytes species had been morphologically characterized (Edvardsen et al., 2016), but the mitogenomes of only 13 haptophyte species have been sequenced, including Emiliania huxleyi (Puerta et al., 2004; Smith and Keeling, 2012) and four Gephyrocapsa species (Kao et al., 2022) from Isochrysidales, Phaeocystis antarctica (Smith et al., 2014), Chrysochromulina tobin (Hovde et al., 2014), Chrysochromulina parva (Hovde et al., 2019), Chrysochromulina sp. (Nishimura et al., 2014) and Phaeocystis globosa (Song et al., 2021) from Prymnesiales, Pavlova lutheri (Hulatt et al., 2020) and Diacronema viridis (Kim et al., 2021) from Pavlovales, and a novel alga Pavlomulina ranunculiformis NIES-3900 from a newly erected haptophyte class, Rappephyceae (Kawachi et al., 2021). The small mitogenome has been considered as an ideal model for genetic diversity, phylogenetic and comparative genomic analysis in algal species with improved resolution compared with traditional molecular markers (Kim et al., 2018; Sibbald et al., 2021; Starko et al., 2021; Zhang et al., 2021; Van Beveren et al., 2022). Unveiling more haptophyte mitogenomes would provide insight into the evolutionary history of haptophytes and the relationships among CASH lineages. Extensive posttranscriptional modifications such as RNA editing and intron splicing are required for plant mitochondrial transcripts during converting RNA from nascent into mature state (Ichinose and Sugita, 2016; Guo et al., 2020). RNA editing is a process during transcription whereby specific nucleotides within mRNA and tRNA sequences were modified by insertions, deletions or base substitutions, thereby affecting the subsequent translation process (Steinhauser et al., 1999). RNA editing is an adaptive process to correct deleterious mutations in non-recombinant organellar genomes, and commonly observed in very diverse groups of eukaryotes, especially in higher plant mitochondria. Trans-splicing, whereby the two exons to be joined to form mature mRNA are from distinct transcripts, has mainly been found in plant organelles and prokaryotes (Bonen, 2008; Laroche-Johnston et al., 2018; Guo et al., 2020). Compared to the typical RNA cis-splicing event, which describes the joining of exons from the same primary transcript, trans-splicing is much less common. Outside of the green-algal lineage (Goldschmidt-Clermont et al., 1991; Cahoon et al., 2017; Kück and Schmitt, 2021), dinoflagellates (Jackson and Waller, 2013) and diplonemids (Valach et al., 2016), little is known about the RNA editing and trans-splicing events in haptophytes. The generation of haptophyte mitogenomes will also give us a good opportunity to undergo a thorough and comprehensive in silico survey of organelle transcriptomes of haptophytes to identify the RNA editing and trans-splicing events. The unicellular golden-brown haptophyte Isochrysis galbana is a member of the Isochrysidaceae family of Isochrysidales order. It is considered as an ideal natural source for human and animal food supplements because it contains rich valuable bioactive compounds such as fucoxanthin (Zarekarizi et al., 2019) and polyunsaturated fatty acids (PUFA; Di Lena et al., 2020). Besides, the high saturated acid of I. galbana can contribute to the improved biodiesel quality applied in renewable energy systems (Sánchez et al., 2013; Silitonga et al., 2017). The small genome with low-level heterozygosity (~93 M), appropriate cell size (5–7 μm), cell wall-less feature, high growth rate and short generation time together make it an exceptionally promising microalgae model for genetic and genomic studies to address many biological questions. A high-quality nuclear genome and a complete chloroplast genome (cpDNA) of I. galbana have been reported (Fang et al., 2020; Chen et al., 2022). However, until recently little was known about the mitochondrial genomic characterization of I. galbana. Mitogenomes are evolving much faster than their plastid genomes in three distinct lineages with secondary red plastids including haptophyte species (Smith and Keeling, 2012), thus often resulting in large complex repeat structures in algal mitogenomes. Nearly all published haptophyte mitogenomes contain complex and highly repetitive non-coding regions. For example, the mitogenome of haptophyte C. tobin has a 9 kb long repeat region, which features three ~1.5 kb large tandem repeats that are flanked by two regions containing small tandem repeats (Hovde et al., 2014). The first full-length mitogenome of haptophyte P. globosa strain CNS00066 contains two large repeat regions with combined length of 20.7 kb, representing the longest repeat region among sequenced haptophytes mitogenomes (Song et al., 2021). The accumulation of tandem repeats in large intergenic regions (LIRs) of mitogenomes are also ubiquitous in unicellular green algae (Turmel et al., 1999, 2007), red algae (Van Beveren et al., 2022), cryptophytes (Hauth et al., 2005; Kim et al., 2008) and diatoms (Oudot-Le Secq and Green, 2011). Porphyridium harbors the largest red algal mitogenomes reported thus far, which could be ascribed to the invasion of group II introns in genic regions and the repeat-rich LIRs (Kim et al., 2022). Undoubtedly, the complexity of repeat structures within mitogenomes in haptophytes and other related algae would present a challenge for assembling the complete circular mitogenomes. It can be inferred that incompletely assembled (linear) mitogenomes of several haptophyte species (P. antarctica [GenBank: JN131834, JN131835], P. globosa [GenBank: KC967226], Pavlova lutheri [GenBank: HQ908424], Gephyrocapsa species [GenBank: OL703630- OL703635], P. ranunculiformis [GenBank: LC564891 plus LC564892]) could be attributed to the presence of one or more large complex repeat structures by which the short-read strategy is limited. Revolutionary breakthroughs in sequencing technologies and bioinformatics methods that are tailored to solve assembly difficulties have largely overcome the short-read dilemma. The Pacific BioSciences (PacBio) long reads combined with the correction of Illumina short-read data was proved to be a highly accurate method to assemble finished-quality (circularized) organellar genomes with no gaps (Fang et al., 2020; Song et al., 2021). Here, the first complete I. galbana mitogenome was constructed based on a combination of PacBio RSII and Illumina Hiseq data from the ongoing I. galbana genome sequencing project. This complete circular mitogenome allows us to perform comparative mitogenome analysis of haptophytes and give a more holistic view of the gene content, architecture, arrangement and complex repeat structure among haptophyte species. We also used Illumina resequencing and transcriptome sequencing data to in silico screen the trans-splicing and RNA editing events in haptophytes for the first time. Our results of algal mitogenomes comparison and phylogenetic analysis provide us with a specific perspective of the evolutionary pattern of haptophytes and related algal lineages.
Isochrysis galbana OA3011 was deposited in the Southern Institute of Oceanography, Fujian Normal University, China. The I. galbana cultures were maintained in 250 ml Erlenmeyer flasks containing 100 ml f/2 medium10 and incubated at 23 ± 1°C under 100 μmol photons m−2 s−1 light on a 12 h:12 h light:dark cycle using fluorescent light bulbs. These flasks were shaken manually 4–6 times a day. Purified total genomic DNA was isolated using a modified cetyltrimethylammonium bromide (CTAB) method (Allen et al., 2006). The concentration and purity of DNA was evaluated by a NanoDrop 2000c spectrophotometer (Life Technologies, DE, United States). The Isochrysis galbana genome was sequenced using a combination of Illumina and PacBio sequencing technologies. Library construction and sequencing of I. galbana genome was carried out by the Novogene Company (Beijing, China). Resequencing was performed on Illumina HiSeq X Ten platform (Illumina Inc., CA, United States) in paired-end (PE) 150 nt mode. Prior to downstream analysis, raw Illumina data were initially subjected to quality checks to obtain clean reads. The empty reads, reads with low-quality bases [Phred quality score (Q) < 20] and Illumina adapters were filtered out by Trimmomatic v0.36 (Bolger et al., 2014). After filtering, over 8.92 Gbp clean PE data including 59.45 million high-quality reads were generated, which represented around 89× genome equivalents. For PacBio library construction and sequencing, at least 5 μl sheared and concentrated DNA was applied to size-selection with BluePippin (Sage Science, MA, United States). A total of ~15.5 Gb data composed of 2,033,745 million reads were obtained from the PacBio RSII platform, i.e., 166 × coverage of the estimated genome size.
The Illumina-generated reads were assembled by NOVOPlasty (Dierckxsens et al., 2016) with the mitogenome of closely related species Emiliania huxleyi (GenBank: AY342361.1) as reference genome, which produced a single linear contig of 27,129 bp as a candidate mitogenome. Based on homologous BLAST searches against the NOVOPlasty result and mitogenomes of related species E. huxleyi and Chrysochromulina sp. CCMP291 (GenBank: KJ201908.1), 310,630 potential mitochondrial reads consisting of 46,594,500 bp data were extracted from the Illumina reads pool. Those extracted Illumina homoreads were used to perform mitogenome de novo assembly using the Abyss (Simpson et al., 2009), SPAdes (Bankevich et al., 2012) and SOAPdenovo2 (Luo et al., 2015). The Abyss draft assembly that could cover the total length of NOVOPlasty result was chosen for further analysis. PacBio long-reads were aligned against the NOVOPlasty and Abyss assembled contigs using BLASR program (Chaisson and Tesler, 2012). Aligned PacBio reads were extracted from the reads pool and considered as potential chloroplast reads. A total of 6.52 Gb data composed of 869,453 million PacBio long reads was extracted after aligning, which were used to perform self-correction and mitogenome de novo assembly of cp genome using CANU v2.1 with default parameters (Koren et al., 2017), followed by error correction using the Quiver (Chin et al., 2013) and Pilon program (Walker et al., 2014). We check the circularity of the final assembly of mitogenome by the “check_circularity.pl” script provided by the sprai package. The resulting mitogenome assembly was arbitrarily reordered and oriented according to the mitogenome sequence of E. huxleyi which starts with genes rrnL and rrnS on the forward strand.
When the I. galbana cells reached the logarithmic phase (106 cells/ml), the culture was evenly divided into eight groups. Each two groups were cultured under white, green, blue and red light of 100 μmol photons m−2 s−1, respectively. The white light was used as control. These groups were harvested at 3 and 7 days. Three biological replicates were carried out for each treatment. Total RNA was extracted using Omega E.Z.N.A.® Plant RNA Kit (Omega Bio-tek Inc., GA, United States) and purified using RNeasy MiniElute Cleanup Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. After quantity and quality determination, RNA samples were further used to Illumina sequencing library construction. A total of 24 cDNA libraries (D3 and D7 samples under four different light qualities) were constructed and sequenced on the Illumina HiSeq X Ten platform (Illumina Inc., CA, United States) in paired-end (PE) 150 nt mode by the Novogene Company (Beijing, China). Prior to downstream analysis, raw Illumina data were initially subjected to quality checks to obtain clean reads. The empty reads, reads with low-quality bases [Phred quality score (Q) < 20] and Illumina adapters were filtered out by Trimmomatic v0.36 (Bolger et al., 2014). Quality reports for the raw and clean RNA-seq data are available in Supplementary Table S1. Over 1.97 billion clean PE reads, totaling 295.59 Gb transcriptome data were generated. PE 150-bp reads were aligned with the I. galbana OA3011 mitochondrial, chloroplast and genomic sequences, respectively using HISAT2 v2.1.0 (Kim et al., 2015) with parameters: --new-summary -p -x -1 -2 -S. The reads for each biological replicate were mapped independently, during which Sequence Alignments/Map (SAM) format files were produced. Unmapped reads were removed in raw SAM files. Then two concatenated SAM files, one for mitochondria and the other for chloroplast, were converted to Binary Alignment/Map (BAM) format and sorted according to chromosomal coordinates using the SAMtools suite (Li et al., 2009). The DNA resequencing short and long reads generated from Illumina and PacBio platforms were aligned against the complete I. galbana mitogenome using BWA (Li and Durbin, 2009) and Minimap2 (Li, 2018), respectively. Multiple-mapped reads and PCR duplicates were removed to prevent the false positives. The Integrative Genomics Viewer (IGV) software (Thorvaldsdóttir et al., 2013) was used to manually visualize and check the accuracy of assembly, gene annotation and gene expression level using the BAM alignment output as a guide.
Preliminary annotation of protein-coding genes was based on ab initio gene predicitons by GeneMarkS (Besemer et al., 2001) and homologous predictions by BLAST searches (Altschul et al., 1990) against extracted gene sequences from published mitogenomes of five haptophyte species Emiliania huxleyi CCMP1516 (linear; GenBank: JN022704.1), Emiliania huxleyi (GenBank: AY342361.1), Chrysochromulina parva (GenBank: NC_036938.1), Chrysochromulina sp. NIES-1333 (GenBank: AB930144.1) and Chrysochromulina tobin CCMP291 (GenBank: KJ201908.1). The start/stop codons and intron/exon boundaries of each protein-coding gene were manually corrected in SnapGene Viewer by referencing the transcriptome alignment file and mitochondrial genes of related species. GroupII introns were predicted by the RNAweasel program (Lang et al., 2007). The noncoding RNA genes (ncRNAs) include transfer RNA genes (tRNAs) and ribosomal RNA genes (rRNAs). We predicted rRNAs by homologous gene evidence and transcript evidence, and tRNAs by tRNAscan-SE version 2.0.4 (Schattner et al., 2005) with default parameters. Manual inspection was also performed to remove overlapped ncRNAs and remain the longest ones with high-confidence. Tandem Repeats Finder (v4.10; Benson, 1999) was applied to identify tandem repeats. The circle graph of I. galbana mitogenome was drawn by Circos v0.69–9 (Krzywinski et al., 2009). Functional annotation of the protein-coding genes was carried out by BLASTP based on sequence-similarity searches against five publicly available protein databases: NCBI non-redundant protein database (Nr), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Groups (COGs) and Swiss-Prot, with a typical E-value cut-off of 1e−5.
Codon usage and relative synonymous codon usage (RSCU) were analyzed by CUSP program in EMBOSS. For the analysis of RNA editing, the “mpileup” utility of SAMtools software suite (Li et al., 2009) was performed to call SNP variants with parameters -I -C50 -u -q 20 -Q 20 based on the transcript alignment output (the BAM file) aforementioned, followed by of SAMtools “bcftools” command. A minimum variant frequency threshold of 0.1 was set to minimize the possibility of overlooking edits due to a low editing frequency. The output variant call format (VCF) file contained all polymorphism information between mRNA transcripts and the DNA sequence. The raw variant calls were filtered with the SAMtools vcfutils.pl. varFilter script and a python script vcf_filter.py for read depth ≥ 5 and polymorphism site quality ≥50. The final SNPs and InDels in the filtered VCF file represent the putative RNA editing sites. The editing efficiency of each site was estimated by calculating the proportion of RNA resequencing reads that contained the SNPs.
The complete sequences and genbank files of 10 haptophyte mitochondrial genomes were downloaded from NCBI Genbank, including Emiliania huxleyi CCMP1516 (linear; GenBank: JN022704.1), Emiliania huxleyi CCMP373 (GenBank: AY342361.1), Diacronema viridis voucher KMMCC0113 (GenBank: MW044630.1), Diacronema viridis culture CCMP620 (GenBank: MW044629.1), Pavlova sp. NIVA-4/92 (GenBank: MN564259.1), Phaeocystis globosa CNS00066 (GenBank: MW435860.1), Phaeocystis antarctica CCMP1374 (GenBank: JN131834.1), Chrysochromulina parva (GenBank: NC_036938.1), Chrysochromulina sp. NIES-1333 (GenBank: AB930144.1) and Chrysochromulina tobin CCMP291 (GenBank: KJ201908.1). Multiple sequence alignment of mitochondrial genomes of I. galbana with other 10 haptophyte algae was conducted on AliTV software (Ankenbrand et al., 2017). The OrthoMCL program (Li et al., 2003) was used to identify common single-copy orthologous genes in 11 mitogenomes with an E-value cutoff of 1e-5. The maximum-likelihood (ML) phylogenetic tree was inferred by PhyML v3.0 (Guindon et al., 2010) employing 1,000 bootstrap replicates and the LG + I + G + F model for amino acid sequences. Mauve genome aligner (Darling et al., 2004) was used to assess the extent of mitochondrial genome rearrangements of haptophyte mitogenomes. Comparisons among all known mitogenomes from a wide range of algal lineages have been made. We collected a total of 2,942 mitogenomes that have been published to date (08/08/2021) of nine main lineages in NCBI, including 333, 282 and 12 mitogenomes from three primary algal lineages (green algae, red algae, glaucophytes), 22, 1,732, 529, 38 mitogenomes from four chlorophyll-c containing algal lineages (cryptophytes, alveolates, stramenopiles, haptophytes), one mitogenome (Lotharella oceanica) from green alga-derived lineage (chlorarachniophytes) and 20 mitogenomes from the jakobids group. Euglenophytes and cyanophytes were not included in this analysis due to no available data of mitogenomes in Genbank. The core set of genes from each lineage were inferred based on gff3 annotation files of all mitogenomes published to date. An in-house python script was used to dig out the conserved core gene set in each group based on the concatenated gff3 file.
To identify positive and negative selection in Isochrysidales species, nonsynonymous (Ka) and synonymous (Ks) substitution rates of 19 functional protein-coding genes shared by three species (I. galbana OA3011, E. huxleyi CCMP373 and E. huxleyi CCMP1516) were calculated. Novel genes (ORFs) were excluded from this analysis. Sequences of these 19 shared exons were extracted from three mitogenomes using an in-house Python script. Each exon of E. huxleyi was aligned separately with the same exon of I. galbana as reference using ClustalW2 (Larkin et al., 2007). To evaluate the divergence of paralogous genes, the KaKs_Calculator tool (Zhang et al., 2006) with parameters “-c 11 -m MS” was performed to calculate the Ka, Ks and evolutionary constraint (Ka/Ks rate) between paralogous pairs of genes based on the output alignment file from ClustalW2. Ka/Ks value of >1 signifies the gene is subjected to positive selection; Ka/Ks value of 1 indicates neutral selection; Ka/Ks value of <1 represents negative purifying selection.
The cox1 gene as a single copy gene is conserved and present in the great mass of algal mitogenomes, and thus was used to investigate the evolutionary pattern of mitochondrial genes among seven algal lineages. The mitogenomes of 200 species (204 mitogenomes in total) in green-algal lineage Chlorophyta (25 species) and Cercozoa (1 species), Glaucophyta (6 species), and five red-algal lineages consisting of Cryptophyta (10 species), Alveolata (13 species), Stramenopiles (79 species) and Haptophyta (15 species) and Rhodophyta (51 species) were retrieved from NCBI GenBank. The mitogenomes from Cryptophyta, Haptophyta, Cercozoa and Glaucophyta nearly covered all available species in GenBank and most mitogenomes in other phyla we selected were recently published before the June, 2022. All selected mitogenomes were checked to ensure that the cox1 gene was a single-copy gene. The coding sequences of cox1 genes were extracted by an in-house perl script “getSeqFromList.pl” and transferred the coding sequences to amino acid sequnences then aligned using MUSCLE v.3.8.1 with default parameters (Edgar, 2004). Multiple sequence alignments were manually trimmed to exclude ambiguously aligned areas adjacent to indels. The ML phylogenetic tree of mitochondrial cox1 genes was inferred using IQ-TREE 2 v2.1.4-beta (Minh et al., 2020). The best-fitting substitution model of ML for cox1 was assessed to be “TN + F + R10” according to the Bayesian information criterion (BIC) by “-m MFP” parameter. Branch supports were calculated using 1,000 ultrafast bootstrap replicates and 1,000 replicates of SH-aLRT test (“-alrt” parameter; Guindon et al., 2010). The concatenated mitochondrial dataset comprised 10 common single-protein (nad1, nad2, nad3, nad4, nad4L, nad5, nad6, cob, cox1, atp6) among 178 species (183 mitogenomes) and 6,266 amino acid positions in total. The mitogenomes of 178 species in green-algal lineage Chlorophyta (24 species) and Cercozoa (1 species), Glaucophyta (6 species), and four red-algal lineages consisting of Cryptophyta (7 species), Stramenopiles (77 species) and Haptophyta (13 species) and Rhodophyta (50 species) were retrieved from NCBI GenBank. Alignments were trimmed by Muscle v.3.8.1 program with default parameters and merged into a single matrix. The ML phylogeny was computed in IQ-TREE 2 v2.1.4-beta. The best-fit model “mtInv + F + I + I + R10” was generated by “-m MFP” and branch supports were calculated using 1,000 ultrafast bootstrap replicates and 1,000 replicates of SH-aLRT test.
The final complete mitogenome of I. galbana was assembled into a single circular double-stranded DNA molecule of 39,258 bp in length with an overall AT content of 72.95% (Figure 1). The mitogenome with gene annotation has been deposited in the NCBI GenBank database with the accession number ON688523. This mitogenome contained a large block of repeat sequences (~12.7 kb) segregated in one region of the genome, which accounted for almost one third of the total genome size (39.26 kb). Aside from the repeat region, this genome presented relatively compact in the coding region. The mitogenome encoded 46 genes, 44 of which were unique, including 20 for protein coding genes, 24 for tRNAs (22 unique) and a split ribosomal operon comprising genes encoding small (16S or rrnS) and large (23S or rrnL) subunits of rRNAs; no 5S rRNA gene was detected (Figure 1). One tRNA gene (trnM-CAU) was tripled and scattered singly in the mitogenome. All annotated genes were found to be encoded on a single strand. The 20 protein coding genes include seven, one, three and three (14 genes) encoding mitochondrial respiratory chain complexes I, III, IV, and V, respectively; one and four encoding large and small subunit ribosomal proteins, respectively. It is noteworthy that no genes were found to be related to complex II (the succinate dehydrogenase, secY) and cytochrome c biogenesis. A single novel gene with unknown function named orf110 was identified. The open reading frame (ORF) of orf110 contained 333 nucleotides, encoding a putative protein of 110 amino acids that had 66% similarity to the orf104 gene of Emiliania huxleyi (GenBank: AAP94716.1) in Nr database. All the protein-coding genes had typical ATG start codon, except for the orf110, which contained the unusual TTA as an initiator codon. Coding regions with combined length of 21,643 bp comprised protein-coding genes (15,594 bp), tRNA genes (1,803 bp) and rRNA genes (4,246 bp), accounting for 55.14% of the genome, whereas the non-coding regions represented 44.86% of the genome. More specifically, the lengths of the I. galbana mitochondrial protein-coding genes ranged from 225 to 2,025 bp with an average length of 780 bp. The lengths of tRNA genes had an average length of 75 bp, ranging from 69 to 90 bp. The two rRNA genes (rrnS and rrnL) were, respectively, 1,544 and 2,702 bp in length. Detailed information on the I. galbana mitochondrial genes is provided in Supplementary Table S2. Global functional analyses of all 20 protein-coding genes revealed that a total of 20, 12, 15, 8, and 15 genes were annotated to Nr, GO, COG, KEGG and Swiss-Prot databases, respectively (Supplementary Figure S1; Supplementary Tables S3–S5). Five genes were annotated in all databases and 12 corresponding genes were assigned with at least one GO term, which could be classified into three main ontologies: molecular function (MF), biological process (BP) and cellular component (CC; Supplementary Figure S1; Supplementary Table S4). Eight genes were mainly involved in metabolic, oxidative phosphorylation and ribosome pathways in our KEGG analysis (Supplementary Figure S2; Supplementary Table S5), which inosculates with the known mitochondrial function. The potential codon bias and codon-anticodon recognition pattern in the I. galbana mitogenome was accessed (Supplementary Table S6). In total, 5,205 codons encoding 20 protein-coding genes were identified in the mitogenome. The 24 tRNAs consisting of 22 unique tRNA contained codons for 20 essential amino acid for algae biosynthesis. The most ubiquitous amino acid was leucine (758, 14.56%), followed by phenylalanine (514, 9.87%) and isoleucine (493, 9.47%), whereas tryptophane (6, 0.12%) was the least common amino acid. Relative synonymous codon usage (RSCU) was calculated by the coding sequences of 20 protein-coding genes in I. galbana. Based on the A/T position in codons, we found that A/T content located at the third position of each codon was the most common pattern (83.13%), followed by the second position of 65.80% and the first position of 64.44%. The RSCU analysis also present the similar trend that A/T were more frequently used (>1) compared with G/C at the third positions of I. galbana mitochondrial codons (Supplementary Table S6). This significant AT-rich bias at the third codon position is common in the extremely AT-rich biased organelle genomes.
Almost all sequenced haptophyte mitogenomes contain highly repetitive non-coding repeat regions, the exception being one of the Prymnesiale species Chrysochromulina parva (Table 1). Like other haptophytes, the complex and highly repetitive non-coding region contribute to the large genome size of I. galbana mitochondrion. The I. galbana mitogenome contained a large repeat localized to a single region measuring 12.7 kb in length (Figure 1), covering 32.24% of its genome. The Tandem Repeat Finder program (Benson, 1999) identified nine tandem repeat blocks which could be condensed to five blocks due to the presence of overlapping (Supplementary Table S7). These five blocks were comprised of repeat units ranging in size from 17 to 1,141 bp and were present in 2 to 115 copies. After manually checking, the whole repeat region could be arbitrarily divided into two large tandem repeats and one small tandem repeat (Figure 1), ~7.5 kb in length of the first large repeat (repeat I: 20,165–27,632) which was combined by several tandem repeat blocks and ~5.0 kb in length of the second large repeat (repeat II: 27,743–32,669) which was previously identified by Tandem Repeat Finder. The first large tandem repeat region (repeat I) was composed of three subunit classes, arbitrarily classified A, B and C, based on the sequence similarity within each subunit with high cutoff criteria of 95% identity (Figure 1). An additional small tandem repeat measuring ~0.3 kb whose unit had some homology to A and C subunits was located upstream of repeat I. Repeat unit A, unit B and unit C was comprised of 81, 56, and 159 bp in length with 50, 44, and 6 copies, respectively (Supplementary Table S8). Repeat I was primarily formed with two consistent patterns of A–B and A–C. The A–B pattern was the main pattern with a total length of 6,514 bp which accounted for 87.23% of repeat I, while A–C pattern represented 12.77% of repeat I with a total length of 954 bp. The GC content of repeat I was 38.43%, which was much higher than that of the whole genome (27.05%), while only 6.9% was detected in the repeat II area. The increase size of tandem repeats in I. galbana and P. globose result in mitogenomes that are only 55% coding regions, in contrast to Jakobids species whose mitogenomes contained very high proportion of coding regions (80%–93%; Burger et al., 2013). The red algae Chondrus crispus owns the most compact mitogenome so far known, with coding sequences amounting to nearly 96%. The most loosely compact mitogenome and massive expansion in tandem repeats have also been reported in green alga Chlorokybus atmophyticus (Turmel et al., 2007) and the red alga Porphyridium purpureum (~132 kbp; Kim et al., 2022). As found in cryptophytes and most other algae (Kim et al., 2018), the tandem repeats within haptophyte mitogenomes represent species-specific pattern. The repeat sequences within the mitogenome of I. galbana showed no sequence and structural similarity to any tandem repeat block identified in other haptophyte mitogenomes. The origins of these repeat sequences still remain enigmatic. This is in contrast to mitogenomes in higher plants and animals whose tandem repeats play an important role in uncovering their evolutionary origins among species (Casane et al., 1997). It is increasingly thought that these variable repeats occurred as a result of strand slippage during recombination (Sibbald et al., 2021). The change in various repeat regions may be mainly induced by differential repeat unit amplification, which represents an indispensable driving force for algal mitogenome evolution (Song et al., 2021).
We compared nine complete and circular mitogenomes of haptophycean algae sequenced to date which belong to four orders: Isochrysidales, Pavlovales, Phaeocystales and Prymnesiales (Table 1). The haptophyte mitogenomes ranged in length from 24,009 bp (Chrysochromulina parva) to 43,585 bp (Phaeocystis globosa). The size increase of the P. globosa mitogenome relative to the other haptophytes was largely attributed to an increase in repetitive elements, which reached up to nearly 19.62 kb. The mitogenome of Chrysochromulina sp. NIES-1333 in Prymnesiales owned the fewest number of protein-coding genes (17 genes), whereas Pavlova sp. in Pavlovales had the most (22 genes). Other species had 19–21 mt protein-coding genes. Comparison of the gene content among 37 available haptophyte mitogenomes revealed that a total of 24 protein-coding genes with known functions in addition to 8 novel genes were found (Supplementary Table S9). All haptophyte genomes contained an identical complement of 15 energy and metabolism genes consisting of one Cytochrome b gene (cob), 3 Cytochrome c oxidase genes (cox1, cox2, cox3), 7 NADH dehydrogenase genes (nad1, nad2, nad3, nad4, nad4L, nad5, nad6), 2 ATPase genes (atp6, atp9), and 2 ribosomal genes (rpl16, rps12; Table 1). Three genes atp8, rpl14 and rps19 were missing from all Isochrysidales mitogenomes, of which rpl14 and rps19 were found to be present exclusively in all Pavlovales species. The nad9 gene was only present in P. ranunculiformis in the new class Rappephyceae. Dam gene which is responsible for DNA adenine methylation was only found in E. huxleyi and G. oceanica in all haptophyte mitogenomes (Supplementary Table S9). With regard to rRNAs, most haptophytean mitogenomes contained only two rRNA genes (16S and 23S) except for Pavlovales which also had a 5S rRNA gene. The number of tRNAs ranged from 24 to 28 with some small variations in tRNA gene content (Table 2). For instance, trnT-UCA was only present in the order Isochrysidales and Prymnesiales. trnU-UCA was only found in Prymnesiales and Pavlovales, whereas trnW-UCA was exclusively present in the other two orders Isochrysidales and Phaeocystales. The Pavlovales had a unique isotype trnW-CCA while the trnC-GCA and trnV-UAC were absent in this order. trnI-CAU was missing in all listed species with the exception of Emiliania huxleyi CCMP1516. Likewise, trnS-ACU was only present in Chrysochromulina sp. NIES-1333. At least three copies of trnM-CAU were present in all examined species, suggesting a major role of this tRNA in haptophyte mitogenomes. It should be noted that trnN-GUU contained the codon for asparagine was absent in I. galbana although it could be found in any other known haptophyte mitogenomes. In terms of gene strand directions, the haptophyte mitogenomes present variation of strand polarity within orders (Table 1), which are structurally similar to that of cryptophytes (Kim et al., 2018). All species in Isochrysidales and Prymnesiales showed absolute strand polarity but not in Pavlovales and Phaeocystales. To be more specific, all genes were located on the same strand in the Isochrysis galbana, Emiliania huxleyi and three Chrysochromulina sp. mitogenomes, while some genes were located on the opposite strand in Diacronema viridis (16 genes), Pavlova sp. (17 genes) and Phaeocystis globose (5 genes). With respect to co-linearity in gene placement among 11 haptophyte mitogenomes, many structural rearrangements have taken placed (Figure 2). In this section, the linear mitogenomes of Emiliania huxleyi CCMP 1516 and Phaeocystis antarctica CCMP1374 were also included in spite that they were partially assembled. These haptophyte species herein could be divided into four orders based on their mitogenome sequences, consisting of Isochrysidales, Prymnesiales, Phaeocystales and Pavlovales (Table 1; Figure 2A; Supplementary Figure S3), which is in accordance with traditional taxonomy. The most significant feature of the haptophyte mitogenomes was that their gene content and gene order were highly variable (Supplementary Table S9; Figure 2A; Supplementary Figure S3). The gene map comparison result showed that barely no syntenic gene blocks were arranged together among all haptophyte mitogenomes. Gene content was broadly conserved but gene order shuffled within the order of Isochrysidales which contained I. galbana and E. huxleyi (Table 1; Figures 2B–D), reflecting their close phylogenetic relationship. Mauve alignment between two E. huxleyi mitogenomes reflected they shared near perfect synteny with identical gene arrangements along the entire length other than the unique novel gene orf104. In contrast, I. galbana shared 11 locally syntenic blocks with the other two E. huxleyi mitogenomes (Figure 2B), which could arbitrarily be assigned into three large conserved syntenic clusters of protein-coding genes (Figures 2C,D). Each cluster contained identical gene order among three species as follows: ① rrnL-rrnS-rps8-cob-rps3-nad4, ② rpl16-nad4L-nad2-cox2-atp4-atp6, ③ nad5-atp9-nad1-rps14-nad6 (Figure 2D). Four tandem gene clusters consisting of 2–4 genes were found to be common to three Isochrysidales species: (a) rrnS-rps8, (b) rps3-nad4, (c) rpl116-nad4L-nad2, (d) atp9-nad1-rps14-nad6. The relative arrangements of these collinear gene blocks revealed that at least one inversion and four translocations have occurred between I. galbana and E. huxleyi. One distinct difference between the two species was the insertion of a large complex tandem repeat region in I. galbana. Additional complete mitogenomes of new taxa in Isochrysidales order need to be sequenced and assembled for comparative genomic studies to confirm these conserved gene clusters and patterns in the arrangement of repeat regions. In contrast to the highly conserved or identical gene arrangement within orders in stramenopiles (Ševčíková et al., 2016; Liu et al., 2020; Sibbald et al., 2021), the haptophyte mitochondrial gene synteny analysis in the current study showed that multiple gene order rearrangements were detected within this lineage and even a given order, which is similar to cryptophytes (Kim et al., 2018).
The cox1 gene encoding cytochrome c oxidase subunit 1 was the only one interrupted gene identified in this mitogenome. The cox1 gene was split into two exons with 12 genes in between (Figure 2D). The Illumina RNA-seq data alignment result confirmed the presence of the two distantly dispersed exons of cox1 in I. galbana (Figures 1, 3). Four exon borders of cox1 could also be determined precisely by RNA-seq data (Figure 3C). The alignment of DNA-seq data generated from Illumina and PacBio platforms was also visualized and showed that no obvious breakpoint was present at the borders of the exon a and b of cox1 (Figure 3A; Supplementary Figure S4), demonstrating the continuity and accuracy of the interrupted cox1 gene and this assembly. Intriguingly, based on the location of cox1 exons, we inferred the intron of cox1 was removed by trans-splicing. The unusual structure of cox1 in I. galbana is the first trans-splicing event ever observed in haptophyte mitochondrion. The mature psaA mRNA in the green alga Chlamydomonas reinhardtii chloroplast genome was also assembled by a process involving trans-splicing of three separate transcripts encoded at three widely scattered loci with many other protein-coding genes in-between (Goldschmidt-Clermont et al., 1991; Kück and Schmitt, 2021). Group II introns are believed to be critical for the splicing reaction and ubiquitously found in in the prokaryote genomes and the plant organelles which are derived from archaebacteria, but very rare or missing in green algal mitochondrion (Gray et al., 1998). Analysis of the whole mitogenome sequence identified one putative group II intron segment (located at the position 18,031–18,074) adjacent to exon b of cox1, which encoded no apparent open reading frame (designated as Ig_cox1i; Figure 3D). A novel gene orf110 with unknown function was identified in the region between two cox1 exons at the position 12,111–12,443. Group II introns have been identified in the mitochondrial genomes of various red algae, diatoms and haptophyte (Ehara et al., 2000; Nishimura et al., 2014; Guillory et al., 2018; Kim et al., 2018). A groupIIA intron with a classical intronic orf in the cox1 gene was found in diatom species (Oudot-Le Secq and Green, 2011). How the group II intron involved in the process of cox1 trans-splicing and the mechanism behind the association remain to be solved. Further analysis should focus on identifying related genes/RNAs required in this process. Many nucleus-encoded pentatricopeptide repeat (PPR) proteins have been shown previously to be targeted to organelles and play essential roles in the trans-splicing of organelle introns (Lee et al., 2019; Kück and Schmitt, 2021). Shifts from cis- to trans-splicing show good correspondence with genome rearrangement rates (Guo et al., 2020), which is further evidenced by the highly poor gene cluster conservation among haptophyte mitogenomes (Figure 2A). On the contrary, no trans-splicing event has yet been detected in any mitochondria of the closely related taxa cryptophytes, whose gene order tend to be less variable (Kim et al., 2018). It should be noted that the cox1 is the nearest neighboring gene to the repeat region (Figures 1, 3C). A hypothesis put forward here is that the intra-genomic rearrangement of cox1 increased the instability of the mitogenome, enabling recombination at small repeats or nuclear DNA fragments to be readily integrated and accumulated into the double-strand break site. The NHEJ-DSB (Non-homologous end joining of double-strand breaks) repair mechanism was triggered when the DNA lesion such as DSB occurred (Waterman et al., 2020).
Using a reference-based single-nucleotide polymorphisms (SNP) calling strategy, a total of 256,757 reads were aligned to the chloroplast genome and 8,660 reads aligned to the mitochondrial genome. Compared to the mitochondrial genome sequence, the aligned mitochondrial transcriptome differed by 6 SNPs (Supplementary Figure S5; Supplementary Table S10), among which two occurred outside of protein-coding regions and four were in exonic region of atp6, rps3, nad6 and rpl16. Initial SNP calling results revealed these sites to be either real SNPs or caused by spurious deep sequencing. In higher plants, the nucleotide transition is commonly observed to be G/C to A/U (Steinhauser et al., 1999), whereas the range of nucleotides found in I. galbana mitogenome in the current study is extensive with more nucleotide transition types. Further strict screening found that each SNP has very low supportive depth with ref.:alt of 13:10, 9:4, 19:4, 37:4, 7:4, and 5:3, respectively (Supplementary Figure S5; Supplementary Table S10). We deduce that none of these SNPs were likely candidates for RNA editing. Likewise, no SNPs were identified when aligning RNA-seq data to I. galbana chloroplast genome sequence by SAMtools “mpileup” utility with the same parameters, revealing no chloroplast RNA editing event in I. galbana. Overall, the results based on deep transcriptome sequencing reflected that RNA editing does not occur in the organelles of I. galbana, which is in accord with the earlier observation in green algae (Cahoon et al., 2017) and Charales (Steinhauser et al., 1999) revealing the absence of RNA editing. The lack of RNA editing in I. galbana organelles is also consistent with the hypothesis that RNA editing has originated in embryophytes after they split from the ancestral algal lineage (Cahoon et al., 2017).
The non-synonymous (Ka) and synonymous (Ks) substitutions and Ka/Ks ratio would reveal the natural selective strength for protein-coding sequence evolution (Yang and Nielsen, 2000). Ka/Ks value <1 is more prevalent given that synonymous nucleotide substitutions have occurred more frequently in protein-coding genes (Makalowski and Boguski, 1998). To pinpoint whether protein-coding genes within mitogenome underwent adaptive evolution in I. galbana compared with other Isochrysidales species. We compared the Ka/Ks ratio for 19 common protein-coding genes within mitogenomes between I. galbana and the most closely related species E. huxleyi hitherto found (Supplementary Tables S11, S12; Supplementary Figure S6). The I. galbana mitogenome was used as a reference. The Ka/Ks ratios of protein-coding genes between two E. huxleyi mitogenomes were calculated to be zero or close to zero, which was in accord with synteny analysis results between two mitogenomes showing nearly no SNPs in these genes (Figure 2B). This result is common between two varieties of a single biological species. The average Ka value and Ka/Ks ratio of 19 protein genes were fairly low (mean Ka = 0.180 ± 0.12631; mean Ka/Ks = 0.042 ± 0.03888) between mitogenomes of I. galbana and E. huxleyi (Supplementary Table S12). The Ka/Ks ratios of all protein-coding genes between two species were less than one, providing the evidence that these genes were subjected to negative purifying selection among Isochrysidales species. More mitogenomes of Isochrysidales should be analyzed in the future to reach this conclusion. Changes in evolutionary rates are strongly correlated with the gene function. All 19 genes exhibited rather low Ka/Ks values with 18 genes <0.08 (all <0.20). Out of them, seven genes revealed a rather low synonymous substitution rate (Ka/Ks < 0.02) between two species, which were found to mainly function in electron transport and ATP synthesis (Supplementary Table S11). The lowest Ka/Ks ratio was observed for three slow-evolving genes including the cytochrome b gene (cob), one cytochrome c oxidase gene (cox1) and one ATP synthase gene (atp9), suggesting they were conserved in Isochrysidales and play indispensable roles in haptophyte mitogenomes. Five genes exhibited highest Ka/Ks (> 0.06) values consisting of three genes encoding small subunits of ribosomal protein (rps3, rps8, rps14), one gene encoding NADH dehydrogenase subunit 2 (nad2) and one for ATPase subunit 4 (apt4), directly leading to a higher average Ka/Ks value for ribosomal protein genes (Supplementary Table S11). The rps8 gene had the highest Ka/Ks ratio (0.180) in the mitogenome. Intriguingly, four out of these five genes (atp4, rps3, rps8, rps14) with slightly high Ka/Ks ratio were also absent from the core mitochondrial gene set (15 genes) identified in all haptophyte species aforementioned, suggesting rapid divergence has been occurred in these four genes in haptophyte mitogenomes in order to better adapt to environment.
Gene content of all mitogenomes from nine diverse eukaryotic assemblages are shown (Figure 4; Supplementary Table S13), including three primary algal lineages (Chlorophyta, Rhodophyta and Glaucophyta), four red alga-derived algal lineages (Cryptophyta, Alveolata, Stramenopiles and Haptista), one green alga-derived lineage Cercozoa (Chlorarachniophytes), and Jakobida which has exceptionally gene-rich mitogenomes. The mitogenomes of jakobid flagellates are noteworthy in retaining certain genes that were transferred to nucleus or absent in algal mitogenomes, including genes involved in cytochrome c oxidase assembly (cox11, cox15), genes encoding the ATP synthase subunit 3 (atp3), LSU ribosomal proteins (rpl1, rpl18, rpl19, rpl27, rpl34, rpl35), core RNA polymerase (rpoA, B, C, D), the RNA subunit of RNase P (rnpB) and elongation factor (tufA; Figure 4). With the exception of unknown ORFs in each mitogenome, the haptophyte mitogenomes contain the smallest conversed gene set (24 protein-coding genes) in algae, smaller than that observed in alveolates (33 protein-coding genes), glaucophytes (34 protein-coding genes), rhodophytes (38 protein-coding genes), cryptophytes (42 protein-coding genes), stramenopiles (45 protein-coding genes) and chlorophytes (48 protein-coding genes). Chlorarachniophytes mitogenomes were found to contain a small set of 24 protein-coding genes. This could be a consequence of only one mitogenome (Lotharella oceanica) that has been published to date. There were no records for euglenophytes and cyanophytes mitogenomes in NCBI. Despite core sets of genes of some groups have been noted before (Kim et al., 2018), their composition; however, present expanded in this study (glaucophytes [34 vs. 30], rhodophytes [38 vs. 22], chlorophytes [48 vs. 39] and haptophyte [24 vs. 22]) that could be ascribed to the addition of several newly updated mitogenomes in these groups since then. The core gene set of cryptophytes remain fairly constant despite the addition of several new mitogenomes. Excluding jakobids, a core set of 17 genes is present in mitogenomes of eight algal lineages sequenced to date. Overall, a more comprehensive set of 48 genes was retained in green algae than that of red algae (45 genes), especially for genes involved in energy metabolism (NADH dehydrogenase subunits) and translation (ribosomal proteins; Figure 4). In contrast, mitogenomes in the red lineage retained genes encoding the translocase subunit tatA related to twin-arginine translocation system transporters, the succinate dehydrogenase subunit (sdh2), the cytochrome c1 ABC transporter ATP-binding subunit (ccmA) and the ribosomal protein L20 (rpl20). The smallest gene set of haptophytes mitogenomes suggest that they have undergone an extreme mitogenome reduction compared to others. Despite of the minimal set, the majority of the haptophytes mitochondrial genes were implicated in oxidative phosphorylation (“OXPHOS”) and protein synthesis belonging to five mitochondrial respiratory complexes, as described above. Jakobid and cryptophytes mitogenomes have the largest complement of genes encoding NADH dehydrogenase subunits (nad1–nad11), which are combined into the complex I in mitochondrion (Figure 4). By contrast, the nad7–11 genes were missing from all rhodophytes mitogenomes and typically rarely found in many species of other phyla. Three genes, nad7, nad9, nad11, were present in stramenopiles, glaucophytes and chlorophytes. Chlorophytes have an additional nad10 compared with the other two. Instead, alveolates mitogenomes have nad8 superseding nad11 in this regard. Mitochondrial respiratory complex II are composed of four subunits of the succinate dehydrogenase, two of which, encoded by sdh1 and sdh2 genes, are hydrophilic and form a subcomplex to play a catalytic role; the other two (encoded by sdh3 and sdh4) are hydrophobic and membrane-integral subunits, playing specific functions in electron transfer (Huang et al., 2019). Previous studies have found that sdh1 and sdh2 are highly conserved among species and has already transferred to the nuclear genome in almost all eukaryotes (Lang et al., 1999; Huang et al., 2019). According to our result, sdh1 was absent in the mitogenomes of any algal lineage we examined, suggesting that this gene might experience an ancient transfer event. Although sdh2 is nucleus encoded in almost all algal species, it is found to be mtDNA-encoded in Rhodophyta and Jakobida, which is in accordance with previous findings (Gray et al., 1998; Burger et al., 2013; Huang et al., 2019). The other two complex II subunits sdh3 and sdh4, on the contrary, were found in either nuclear encoded or mitochondrion encoded (Gray et al., 1998), and our result also corresponds well with this trend. It should be noted that all haptophytes, stramenopiles and alveolates have lost all sdh genes from their mitogenomes. This is similar to the observation in animals and fungi that present all four sdh genes have moved to the nuclear genome (Huang et al., 2019). Genes encoding the cytochrome bc1 complex subunit (complex III: cob gene) and three cytochrome c oxidase subunits (complex IV: cox1, cox2 and cox3 genes) were present in the mitogenomes of all haptophyte species and other examined algal lineages. These four genes were dispersedly distributed throughout the entire mitogenome in Haptophytes (Figure 2), in contrast to the observation in cryptophyte mitogenomes, which showed that cob and cox genes normally stayed in groups (Kim et al., 2018). Group II introns were particularly common in the mitochondrial cox1 gene of various red algae, stramenopiles, cryptophytes (Guillory et al., 2018; Kim et al., 2018; Sibbald et al., 2021). Like Chroomonas placoidea in cryptophytes, the cox1 gene in I. galbana was split into two exons with many genes in-between (Kim et al., 2018). In I. galbana, a putative group II intron segment with no apparent ORF was also found adjacent to the exon b of cox1, and one single ORF with unknown function lay in the middle region between two cox1 exons (Figure 3D). This has not been consistently observed in other algal species which reported that many mitochondrial group II introns of cox1, cob or rnl genes often harbor protein-coding regions corresponding to intron encoded proteins (IEPs), which contain domains encoding a reverse transcriptase/maturase, DNA binding and DNA endonuclease (Zimmerly et al., 2001; Kim et al., 2018; Sibbald et al., 2021). The biggest complement of ATP synthase genes (complex V genes) was possessed by jakobid mitogenomes (six atp genes). The atp3 gene was absent in all eight algal lineages. In algal groups, all green algae and cryptophytes possessed most of the atp gene set (five atp genes) while the alveolates contained the minimal atp gene set (atp6 and apt9). Excluding alveolates and chlorarachniophytes, three atp genes (atp6, atp8, atp9) were conserved in the mitogenomes of other algal lineages. The twin-arginine protein transport pathway (Tat pathway) are ubiquitously present in prokaryotes and plant organelles, and two tat genes (tatA, tatC) were found to be generally conserved in diverse prokaryotes, plastids and some mitochondria (Berks, 2015; Palmer and Stansfeld, 2020). The current study noted their presence in the mitogenomes of three red-algal lineages (rhodophytes, cryptophytes, stramenopiles) aside from jakobids (Figure 4). In the green-algal lineages, the mitochondrial tatC homologs were present but no tatA was found. It is worth noting that both tat genes were absent from two red-algal lineages (haptophyte, alveolates) and glarucophytes mitogenomes sequenced to date (Figure 4). Based on our previous finding, both tat genes were also absent in three haptophyte chloroplast genomes sequenced to date (Puerta et al., 2005; Fang et al., 2020). The general secretory signaling (Sec) pathway always operate in parallel with the Tat pathway to transport folded proteins across membranes (Palmer and Stansfeld, 2020). The secY gene involved in Sec pathway was limited to chloroplast genomes in haptophytes (Fang et al., 2020) while it still existed in green-algal, red-algal and stramenopiles mitogenomes (Figure 4). Other four genes (tufA and rpoA/B/C) that have been absent from all algal mitogenomes (Figure 4) were found in chloroplast genomes of haptophyte species (Fang et al., 2020). Clearly more mitogenome data are required from mitogenome sequences lacking lineages such as haptophytes and chlorarachniophytes to confirm the trend.
The mitochondrial maximum-likelihood (ML) phylogenetic tree was constructed using a total of 204 non-redundant COX1 amino acid sequences recovered from GenBank and the I. galbana mitogenome (Figure 5; Supplementary Table S14). The multiple-gene ML tree was also inferred with concatenated amino acid sequences of 10 common single-copy protein-coding genes from 183 mitogenomes (Supplementary Figures S7, S8). Our extensive taxon sampling suggested that all lineages present well-resolved internal relationships. The topology within the haptophyte clade was very similar to the phylogenetic reconstructions inferred from individual genes or entire plastome/mitogenome sequences (Figures 2A, 5; Supplementary Figure S7; Bendif et al., 2013; Fang et al., 2020; Kawachi et al., 2021; Song et al., 2021; Kao et al., 2022). Within the monophyletic clade of Haptophyta, two main clades consisting of three classes (Prymnesiophyceae, Pavlovophyceae and Rappenphyceae) were statistically strongly supported (MLBS ≥ 97%; Figure 5). Isochrysis galbana, E. huxleyi and four Gephyrocapsa speices (G. oceanica, G. muellerae, G. parvula, G. ericsonii) were nested within the Isochrysidales monophyletic clade, while I. galbana was the only species found in the family of Isochrysidaceae (Figure 5C). This is consistent with previous phylogenetic analyses on Isochrysidales inferred from a concatenated sequence of three genes (SSU/LSU rDNA and cox1) and the entire plastome coding sequences (Bendif et al., 2013; Fang et al., 2020). The interlaced relationship of Emiliania-Gephyrocapsa mitogenomes (Figure 5C) was largely congruent with the topology inferred by concatenated orthologous coding genes of entire mitogenomes (Kao et al., 2022), which also revealed that the most divergent lineage (γ) harbored the mitogenomes of G. oceanica RCC3711 and RCC1296, and G. muellerae RCC3370 and E. huxleyi RCC175 were nested within the β lineage, while the α lineage (subdivided into α1 and α2) contained the rest species. The inclusion of the novel species P. ranunculiformis NIES-3900 of the new class Rappenphyceae within Haptophyta was strongly supported (MLBS = 97%), which was the first to diverge from Prymnesiophyceae and formed a sister group to the class of Pavlovophyceae. This is slightly inconsistent with the ML tree inferred from the mitochondrial dataset that was composed of 49 taxa, which revealed the sister relationship between NIES-3900 and Prymnesiophyceae (Kawachi et al., 2021). The much larger dataset we used in our phylogenetic analysis could explain the discrepancy. The COX1 identity of alveolates was found to the exclusion of all other four red-derived algal lineages (cryptophytes, stramenopiles, haptophytes and rhodophytes; Figure 5A). Alveolates COX1 formed two distinct branches before the split of rhodophytes and other lineages with secondary red-derived plastids. The positions of alveolates and stramenopiles contradicted the formation of SAR supergroup (Keeling and Burki, 2019) or the finding that stramenopiles diverged from alveolates and their extant plastids are direct descendants of a common red algal plastid (Janouškovec et al., 2010), suggesting a different evolutionary trajectory of cox1 genes. This could be explained by mitochondrial-plastid or single/multiple genes phylogenomic incongruence. A monophyletic stramenopiles clade was formed by three distinct phyla (Bigyra, Ochrophyta, and Oomycota), which with nearly full support branches as sister to Haptophyta (Figure 5; Supplementary Figures S7, S8). This relationship is in accord with the schematic tree based on a consensus of phylogenomic studies together with morphological characteristics (Keeling and Burki, 2019). The Cercozoa (chlorarachniophytes) was unexpectedly grouped into the clade of Haptophyta (Figure 5) or the clade of stramenopiles (Supplementary Figures S7, S8; both were the red-derived lineages), in contrast to the perception of its green algae-derived origin. The similar trend was also found in recent algal phylogenetic analysis based on conserved BUSCO sequences (Shi et al., 2021). The cryptophyte lineage was located separately from the SH lineages (Figure 5; Supplementary Figures S7, S8), which is strongly in line with earlier phylogenetic analysis based on a dataset of 16 conserved mtDNA proteins (Kim et al., 2018). In particular, at odds with the evolutionary hypothesis supported by morphological, molecular and organelle phylogenetic studies that the single event of primitive primary endosymbiosis led to the divergence of archaeplastids taxa (green algae, red algae and glaucophytes), the red-derived lineage cryptophytes with secondary plastids formed a monophyletic clade with lineages with primary plastids (Figure 5; Supplementary Figures S7, S8). This finding is also in line with many previous findings that the archaeplastids group are mostly interrupted by cryptists (Keeling and Burki, 2019). To this day the monophyly of archaeplastids group still remain controversial due to lack of comprehensive and solid support from most molecular trees. Compared with the COX1 tree, the main phylogenetic topology of nine algae phyla of the multiple-gene tree was more consistent with the schematic eukaryotic tree summarized by many phylogenomic studies (Keeling and Burki, 2019). From mitochondrial perspective, the relative relationship among algal lineages implied their considerably deeper divergence rather than a simple origin, which fit with the “multiple eukaryote-eukaryote endosymbiosis (EEE) hypothesis” or “rhodoplex hypothesis” hypothesis (Archibald, 2009).
In this study, we reported the first full-length mitogenome of I. galbana, which is an ~39,258 bp circular molecule with an AT-rich pattern (72.9%), encoding 20 protein-coding genes, 24 unique tRNA genes and two rRNA genes. This mitogenome consists of an elaborate combination of direct repeats (about 12.7 kb) uninterrupted by genes, making it much larger than most other haptophytes mitogenomes. Comparative analysis of haptophyte mitogenomes revealed that they shared an identical complement of 15 energy and metabolism genes, exhibited opposite or same strand polarities within different orders and had poorly conserved gene content and order. Genes were broadly conserved with the same strand orientation but gene order was highly variable in the Isochrysidales order. The Ka/Ks ratios of all common genes in Isochrysidales mitogenomes were less than one, suggesting that they are under purifying selection. The visualization of RNA-seq and DNA-seq alignment reads verified the present of the trans-spliced gene cox1 that contained two distantly dispersed exons in I. galbana. This is the first trans-splicing event ever identified in mitochondrion of haptophytes. The high mitogenome rearrangement rates in haptophytes could account for the shifts from cis- to trans-splicing. Also, the intragenomic rearrangement of cox1 could increase the genome instability, thus accelerate the multimerization and accumulation of pre-existing small-repeats at the site of DNA damage. No organelle RNA editing was found in I. galbana based on deep transcriptome sequencing data, further confirming the perception that RNA editing evolved after embryophytes separated from the algal ancestry of all land plants. Mitogenome comparison among algal lineages revealed haptophytes contained the most contracted protein-coding gene set. Haptophytes mitogenomes have lost many functional genes (e.g., sdh, tat, and secY genes) in comparison with other red-lineages. The distinct phylogenetic relationship reflected by chloroplast and mitogenome genes underscore their dramatic different evolutionary tempo and pattern even they coexist in the same cell.
The final complete mitogenome sequence with gene annotation has been deposited in the NCBI GenBank under accession number of ON688523. The Illumina DNA resequencing raw reads in FASTQ format of I. galbana genome have been deposited in the Genome Sequence Archive database (GSA; https://ngdc.cncb.ac.cn/gsa/) under accession number of CRA007102. The Illumina RNA-sequencing raw data of I. galbana transcriptome under different conditions are available in GSA under accession number of CRA007103.
JF conceived this mitogenome project and coordinated the research activities. JF and XX designed the experiments and wrote the manuscript. JF and AL assembled and annotated the mitogenome. QC and JF carried out the experiments and processed genome and transcriptome resequencing data. JF, XX, AL, QC, and SL performed the bioinformatic analyses. All authors contributed to the article and approved the submitted version.
This work was supported by the Natural Science Foundation of China (grant number 41906096), the Middle-aged Teachers from Fujian Provincial Department of Education (grant number JT180082), the Natural Science Foundation of Fujian Province, China (grant number 2019J05066) and Key Projects of Science and Technology Bureau of Fuzhou, Fujian, China (grant number 2021-N-119).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9552351 | Jinjin Yuan,Ziheng Feng,Qiaowen Wang,Lifen Han,Shenchan Guan,Lijuan Liu,Hanhui Ye,Lili Xu,Xiao Han | 3’UTR of SARS-CoV-2 spike gene hijack host miR-296 or miR-520h to disturb cell proliferation and cytokine signaling | 27-09-2022 | SARS-CoV-2,cell proliferation,3’UTR,cytokine signaling,spike gene | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has becoming globally public health threat. Recently studies were focus on SARS-CoV-2 RNA to design vaccine and drugs. It was demonstrated that virus RNA could play as sponge to host noncoding RNAs to regulate cellular processes. Bioinformatic research predicted a series of motif on SARS-CoV-2 genome where are targets of human miRNAs. In this study, we used dual-luciferase reporter assays to validate the interaction between 3’UTR of SARS-CoV-2 S (S-3’UTR) gene and bioinformatic predicted targeting miRNAs. The growth of 293T cells and HUVECs with overexpressed S-3’UTR was determined, while miRNAs and IL6, TNF-α levels were checked in this condition. Then, miR-296 and miR-602 mimic were introduced into 293T cells and HUVECs with overexpressed S-3’UTR, respectively, to reveal the underlying regulation mechanism. In results, we screened 19 miRNAs targeting the S-3’UTR, including miR-296 and miR-602. In 293T cell, S-3’UTR could inhibit 293T cell growth through down-regulation of miR-296. By reducing miR-602, S-3’UTR could induce HUVECs cell proliferation, alter the cell cycle, reduce apoptosis, and enhanced IL6 and TNF-αlevel. In conclusion, SARS-CoV-2 RNA could play as sponge of host miRNA to disturb cell growth and cytokine signaling. It suggests an important clue for designing COVID-19 drug and vaccine. | 3’UTR of SARS-CoV-2 spike gene hijack host miR-296 or miR-520h to disturb cell proliferation and cytokine signaling
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has becoming globally public health threat. Recently studies were focus on SARS-CoV-2 RNA to design vaccine and drugs. It was demonstrated that virus RNA could play as sponge to host noncoding RNAs to regulate cellular processes. Bioinformatic research predicted a series of motif on SARS-CoV-2 genome where are targets of human miRNAs. In this study, we used dual-luciferase reporter assays to validate the interaction between 3’UTR of SARS-CoV-2 S (S-3’UTR) gene and bioinformatic predicted targeting miRNAs. The growth of 293T cells and HUVECs with overexpressed S-3’UTR was determined, while miRNAs and IL6, TNF-α levels were checked in this condition. Then, miR-296 and miR-602 mimic were introduced into 293T cells and HUVECs with overexpressed S-3’UTR, respectively, to reveal the underlying regulation mechanism. In results, we screened 19 miRNAs targeting the S-3’UTR, including miR-296 and miR-602. In 293T cell, S-3’UTR could inhibit 293T cell growth through down-regulation of miR-296. By reducing miR-602, S-3’UTR could induce HUVECs cell proliferation, alter the cell cycle, reduce apoptosis, and enhanced IL6 and TNF-αlevel. In conclusion, SARS-CoV-2 RNA could play as sponge of host miRNA to disturb cell growth and cytokine signaling. It suggests an important clue for designing COVID-19 drug and vaccine.
Since the appearance of coronavirus disease 2019 (COVID-19) in December 2019, the disease has spread globally, becoming the most significant public health threat in the world today. COVID-19 is a novel coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, millions of people have been diagnosed with SARS-CoV-2 worldwide (https://covid19.who.int) and the growing number of individuals with COVID-19 has placed a burden on the healthcare systems of many countries. However, to date, no effective antiviral drugs have been approved to treat COVID-19. The most common initial symptoms of COVID-19 are fever and respiratory symptoms such as cough, shortness of breath, and sore throat. Furthermore, COVID-19 can also affect the heart and blood vessels, promoting the development of cardiovascular diseases such as myocardial damage, arrhythmia, acute coronary syndrome (ACS), and venous thromboembolism. At present, the pathogenic mechanism of the new coronavirus epidemic has not fully been elucidated and most people are still at risk of contracting COVID-19. Further exploration of the pathogenic mechanism of COVID-19 is therefore essential to control and treat this disease. miRNA plays an important regulatory role in many biological processes and is instrumental in the interaction between viruses and hosts. Host miRNA can be used as a “weapon” to interfere with virus replication. Conversely, viruses can regulate host miRNA to suppress the host immune system. Previous studies have identified differentially expressed miRNAs in COVID-19 patients through transcriptome analysis (1–5). In particular, virus RNA can play as sponge of host miRNA to regulate immune processes. It was described hepatitis C virus RNA sequesters host miR-122 to facilitate viral replication (6). Recent study revealed the potential miRNA interacted with SARS genomes in human cell (7). In another study, it was demonstrated endogenous human micro and long non-coding RNAs has potential binding site in the SARS-CoV-2 genome (8). These evidences are clue for RNA-base drugs and understanding pathogen mechanism of COVID-19. However, no experimental evidence proofed that SARS-CoV-2 RNA could play as sponge of host miRNA involved in COVID-19 disease. Here, the current study screens some of the miRNAs that 3’UTR of SARS-CoV-2 S gene can target and further investigates whether 3’UTR of SARS-CoV-2 S gene can affect cell proliferation and expression levels of cytokines through sponging to these miRNAs.
In the SARS-CoV-2 genome, two potential PolyA sites were identified after the S gene by using bioinformatics web tools (http://regrna2.mbc.nctu.edu.tw/) ( Figure 1A ). The polyA site furthest from the stop code of the S gene was used to define the 3′-untranslated region (3′UTR). Subsequently, 19 miRNAs with a predicted interaction site on the 3′UTR of the S gene (S-3′UTR) were identified by screening a bioinformatic database ( Figure 1A ; Supplemental Table 1 ). Potential target genes of the 19 miRNAs were also predicted using the same database. According to Gene Ontology (GO) annotation, these target genes are involved in cardiovascular, metabolic, and chemdependency disease pathways ( Figure 1B ). Furthermore, these genes were suggested to be enriched in biological pathways such as TGF-beta signaling, adherens junction, and metabolism ( Figure 1C ). Interactions between the miRNAs and S-3′UTR were validated via a series of dual-luciferase reporter assays in 293T cells. Eight miRNAs significantly reduced the S-3′UTR reporter signal, including miR-1299, miR-23b, miR-214, miR-296, miR-302c, miR-520h, miR-602, and miR-766. Luciferase activities were decreased by about 20%–50% in the miRNA mimics group compared with the control (NC) group ( Figure 2A ). Mutant S-3′UTRs were generated to disrupt potential interaction sites between miRNAs and S-3′UTR. Dual-luciferase reporter assays were repeated with mutant S-3′UTR controls and revealed that miR-1299, miR-23b, miR-214, miR-296, miR-302c, miR-520h, miR-602, and miR-766 could reduce the S-3′UTR reporter signal but not that of the mutant S-3′UTR ( Figures 2B-H ). Among these miRNAs, miR-296 caused the largest reduction in the reporter signal ( Figure 2C ).
To study the biological cellular function of SARS-CoV-2 S-3′UTR, a vector was constructed to overexpress this region in 293T cells. The expression levels of seven miRNAs that possess the ability to bind S-3′UTR were then determined. Only miR-296-3p was significantly downregulated in 293T cells after overexpression of S-3′UTR, while expression of the other six miRNAs did not change significantly ( Figure 3A ). The proliferation ability of 293T cells overexpressing S-3′UTR was checked by CCK-8 assay and was significantly reduced by approximately 33% compared with the control ( Figure 3B ). Cell-cycle monitoring revealed that the number of cells in S phase was increased by approximately 10% in the S-3′UTR group compared with the control group ( Figure 3C ). Flow cytometry demonstrated that the amount of apoptosis in the S-3′UTR group was twice that of the control group ( Figure 3D ).
To further explore the functional mechanism of S-3′UTR through miR-296, a microRNA mimic was used to restore the level of miR-296 in 293T cells overexpressing S-3′UTR ( Figure 4A ). Cell proliferation in the S-3′UTR group without microRNA mimic was significantly reduced by approximately 40% compared with the control, while cells overexpressing S-3′UTR plus miR-296 mimic exhibited restored proliferation ability, at approximately 90% of the control cells ( Figure 4B ). In addition, the miR-296 mimic group without S-3′UTR increased the cell proliferation ability by 20%. Cell-cycle analysis revealed that the S-3′UTR, miR-296 mimic, and S-3′UTR plus miR-296 mimic groups all had an increased percentage of cells in S phase and a decreased percentage of cells in G2 phase compared with the control ( Figures 4C, D ). Furthermore, the S-3′UTR group showed an increased apoptosis ratio of three times that of the control group, while the S-3′UTR plus miR-296 mimic group only showed an increase of 1.5 times that of the control group. In addition, the miR-296 mimic group exhibited a 50% reduction in apoptosis ratio compared with control ( Figures 4E, F ). The caspase assay checked the level of caspase-3/8/9, results indicated the same pattern of apoptosis ( Figure 4G ). This suggested that miR-296 could recover the cell proliferation and reduce apoptosis in 293T cells disturbed by S-3′UTR.
SARS-CoV-2 can directly target endothelial cells. Therefore, to further explore the effect of S-3′UTR on endothelial cells, a viral vector was constructed to overexpress S-3′UTR in HUVECs. Expression levels of miRNAs and cell phenotypes were then determined in these cells. Among seven miRNAs targeted to S-3′UTR, expression of miR-602, miR-1299, miR-296, miR-520h, and miR-573 was significantly reduced in HUVECs overexpressing S-3′UTR ( Figure 5A ). Cell proliferation ability of HUVECs in the S-3’UTR group was increased by approximately 40% compared with the control group ( Figure 5B ). Furthermore, the proportion of cells in G1 phase increased approximately 10% in the S-3′UTR group ( Figure 5C ), and the percentage of apoptotic cells in the S-3’UTR group was reduced to 10%, whereas it was approximately 17% in the control ( Figure 5D ). Moreover, levels of cell secreted IL-6 and TNF-α and IL-6R in cell—important molecules in the cytokine storm caused by SARS-CoV-2 infection—were determined. IL-6 and TNF-α were significantly upregulated, by approximately 12% and 40%, respectively, in S-3′UTR group compared with the control group, IL-6R were also increased in cells, other anti-inflammatory cytokines such as IL-10 and IL-1Ra has no significant difference ( Figure 5E ).
The role of miR-S-3’UTR interaction(s) was further clarified by analyzing potential target genes of miRNAs that were downregulated by S-3′UTR in HUEVCs. Among miR-602, miR-1299, miR-296, miR-520h, and miR-573, only miR-520h has predicted gene targets, which are IL-6R and HiF-α, molecules involved in IL-6 and TNF-α signaling pathways. Analysis of miR-520h expression revealed that miR-520h was significantly downregulated following overexpression of 3′UTR but markedly upregulated after transfection with the miR-520h mimic ( Figure 6A ). Accordingly, S-3′UTR significantly induced the cell proliferation ability and the miR-520h mimic reduced the cell proliferation ability by approximately 30%, while the S-3’UTR plus miR-520h mimic restored the cell proliferation ability to that of the control group ( Figure 6B ). Next, IL-6 concentrations were examined using an enzyme-linked immunosorbent assay (ELISA). IL-6 was significantly increased in the S-3′UTR group and restored to the control level in the S-3′UTR plus miR-520h mimic group ( Figure 6C ). Analysis of cell cycle distribution showed that the miR-520h mimic group had a markedly reduced percentage of cells in S phase and an increased number of cells in G2 phase. In contrast, the S-3’UTR group and S-3’UTR plus miR-520h mimic group had an increased number of cells in G1 phase ( Figures 6D, E ). Furthermore, the amount of apoptosis in the S-3′UTR group was reduced to 12.5%, while the S-3′UTR plus miR-520h mimic group had 17.5% apoptotic cells ( Figures 6F, G ). The caspase assay checked the level of caspase-3/8/9, results indicated the same pattern of apoptosis ( Figure 6H ). These observations indicate that miR-520h could recover the HUVECs disturbed by S-3′UTR.
SARS-CoV2 predominantly infects nasal and bronchial epithelial cells, type I and type II alveolar pneumocytes, and capillary endothelial cells via the viral structural spike (S) protein binding to the ACE2 receptor (9). In responding to infection, T lymphocytes, monocytes, and neutrophils are recruited to infection sites and secrete various cytokines, such as TNF-α, IL-1, and IL-6. During the late stage of infection, hyper-inflammation—also known as a “cytokine storm”—results in alveolar interstitial thickening, pulmonary edema, and compromised epithelial-endothelial barrier integrity, collectively referred to as acute respiratory distress syndrome (ARDS) (10). ARDS and multiorgan dysfunction are two leading causes of death in severe cases of COVID-19 and are frequent consequences of cytokine storm (11). Cytokines are an essential part of the inflammatory response, participating in a wide range of pathophysiological processes and assisting the host in eliminating pathogens. However, inappropriate inflammatory responses trigger over-production of cytokines, which causes tissue damage. Cytokine storm is an umbrella term describing a group of clinical manifestations caused by cytokine dysregulation, such as systemic inflammation, constitutional symptoms, and multiorgan dysfunction (12). An aggressive inflammatory response, accompanied by high levels of chemokines and cytokines, such as IL-2, IL-6, IL-7, IL-10, TNF-α, IFN-γ, IP10, and MCP1, was identified in patients with COVID-19 (13–15). Patients requiring admission to intensive care units (ICU) displayed higher levels of proinflammatory cytokines including IL-6 and TNF-α (13, 15). IL-6 is a cytokine that promotes inflammation, immune reactions, and hematopoiesis (16), while TNF-α plays an important role in cellular activation and recruitment of leukocytes to inflammatory sites (17). IL-6 and TNF-α are two crucial cytokines in the pathogenesis of the SARS-CoV-2-induced cytokine storm and are probably responsible for severe clinical presentation and poor prognosis (18). In the current study, overexpression of S-3′UTR was observed to significantly upregulate both IL-6 and TNF-α in HUVEC cultures. The interaction between miR-520h and S-3′UTR was likely responsible for this upregulation since overexpression of S-3′UTR in HUVECs led to a significant decrease in expression of miR-520h and this could be restored by inclusion of a miR-520h mimic. Bioinformatic analysis identified that miR-520h could downregulate IL-6R and HiF-α and might play a role in regulating immune homeostasis and inflammation during SARS-CoV-2 infection. IL-6 binds membrane-bound IL-6R (mIL-6R), which induces homodimerization of membrane-bound gp130 (mgp130), or alternatively, IL-6 can bind to soluble IL-6R (sIL-6R), forming a complex of IL-6 and sIL-6R to interact with mgp130, and then initiates downstream signaling cascades (19). HiF-α is an important signaling molecule contributing to pathological and physiological changes of homoeostasis under hypoxia stress (20). Downregulation of HiF-α was previously shown to inhibit the expression of IL-6 and TNF-α (21). We hypothesize that miR-520h was targeted by S-3′UTR and thus the biological functions of miR-520h—including inhibition of IL-6R and HiF-α—were silenced, leading to inappropriate secretion of IL-6 and TNF-α and a severe inflammatory response. Changes in the expression levels of miRNAs identified by transcriptomic and bioinformatic analysis in SARS-CoV-2 infected patients have been reported and include the upregulation of miR-2392 and miR-3605-3p, and the downregulation of miR-146a-5p, miR-21-5p, and miR-142-3p (22, 23). Furthermore, differentially expressed genes in SARS-CoV-2-infected human lung epithelial cells were predicted to be targeted by some miRNAs, such as hsa-miR-342-5p, hsa-miR-432-5p, hsa-miR-98-5p, and hsa-miR-17-5p (24). These studies indicate that miRNAs have a role in the pathogenesis of SARS-CoV-2. miRNAs are a group of single-stranded, small (~21–22 nt), noncoding RNAs, which are known as negative regulators of gene expression and essential biological processes predominantly through binding to the 3′UTR of target mRNAs at post-transcriptional levels (25). miRNAs can bind to a wide range of RNA viruses, mostly in the 5′- and 3′-UTRs and regulate viral pathogenesis in different ways (26, 27). For example, miR-323, miR-491, and miR-654 could bind to the PB1 gene of H1N1 influenza A virus and subsequently suppress its replication (28), while miR-28-5p, miR-150, miR-223, and miR-382 could decrease HIV-1 translation but were pivotal in HIV-1 latency and reservoir (29). In the current study, 19 miRNAs with a predicted interaction site on the 3′UTR of the S gene of SARS-Cov-2 were identified by screening a bioinformatic database and eight of these miRNAs were subsequently proven to bind to S-3′UTR in a series of dual-luciferase reporter assays. These eight miRNAs were miR-1299, miR-23b, miR-214, miR-296, miR-302c, miR-520h, miR-602, and miR-766. In addition to miR-602 described above, miR-766, miR-214, miR-23b, miR-1299, miR-520h, and miR-302 were previously reported to be highly expressed in tumor cells that were frequently involved in the processes of carcinogenesis, tumor progression, and metastasis (30–35). Expression levels of miR-296 were frequently associated with cardiovascular diseases. In the current study, they could directly bind to the S-3′UTR of SARS-CoV-2, while their mutant could not reduce the signal of S-3′UTR. In addition, RNA viruses can induce changes in cellular miRNA expression, which might help the viruses replicate and avoid host immune responses. Influenza virus could downregulate miR-24 levels in A549 cells to increase expression of furin protein and allow the progeny virus numbers to increase (36). Coronavirus OC43 nucleocapsid protein downregulated expression of miR-9, which is a negative regulator of NF-κB, leading to continual NF-κB translation (37). Decreased levels of miR-221 were found in RSV-infected human bronchial epithelial cells, and this could prevent cell apoptosis and boost viral replication (38). In the present study, miR-296 was significantly downregulated after overexpression of S-3′UTR in 293T cells, while miR-602, miR-1299, miR-296, miR-520h, and miR-573 were significantly downregulated after overexpression of S-3′UTR in HUVECs. In 293T cells overexpressing S-3′UTR, only miR-296-3p was significantly downregulated. Furthermore, cell proliferation ability was suppressed approximately 33% compared with the control, and from the cell-cycle analysis, more cells (approximately 10% increase compared with control) were trapped in S phase. miR-296 could regulate cellular proliferation via several pathways. First, the p53/p21 axis is a crucial mediator in cell cycle control. Yoon et al. showed that overexpression of miR-296 could suppress the p53-p21 pathway and decrease mRNA expression of p21 by targeting the 3′UTR of p21 (39). miR-296-3p could also target phosphatase and tension homologue (PTEN) and inhibit its downstream phosphoinositide 3-kinase (PI3K)/Akt signaling pathway (40), which is involved in cell proliferation, growth, cell size, metabolism, and motility (41). S-3′UTR of SARS-CoV-2 probably disturbed the physiological function of miR-296 and subsequently led to suppression of proliferation. In addition, the S-3′UTR group displayed enhanced apoptosis activities compared with the control group. In HUVECs overexpressing S-3′UTR, downregulation of miR-520h led to significant induction of cell proliferation and reduction of apoptosis activity. The profile of the cell cycle also changed, with the proportion of cells in G1 phase increasing by approximately 10%. miR-520h has a negative effect on HUVECs cell proliferation and other tumor cells including granulosa-like tumor cell (35, 42–45). It was reported that miR-520h could target on IL-6R to inhibit cell growth (42).In the current study, an anti-proliferation property of miR-602 was revealed, we also identified that IL-6R was turned downed by miR-602 and induced by S-3′UTR. These indicate that this miRNA might play the same biological functions in different cells. Overall, this study demonstrated that S-3′UTR of SARS-CoV-2 could bind to different miRNAs and alter the expression levels of these miRNAs in different cells (293T and HUVECs), leading to disturbances in cellular activity and various pathophysiological processes of infected cells. mRNA vaccines are an effective prophylaxis against SARS-CoV-2 and help to prevent severe clinical presentations and poor outcomes (46, 47). RNA therapy has always been considered a promising therapeutic approach against a wide range of diseases. Insights into the roles of miRNA in disease pathogenesis have resulted in miRNAs becoming attractive targets for drug development. Mirvirasen and RG-101 are two miRNA-based medicines for acute and chronic hepatitis C, and target miR-122, which is crucial for the stability and propagation of HCV RNA (48, 49). RG-125/AZD4076, targeting miR-103/107, is undergoing clinical trials for applications in patients with type 2 diabetes and non-alcoholic fatty liver diseases (50). Moreover, MRX34, a miR-34 mimic, is used to treat multiple solid tumors (51). In the current study, the miR-296 mimic and miR-602 mimic could rescue the disturbances in cell proliferation and apoptosis induced by S-3′UTR in 293T cells and HUVECs, respectively. Therefore, development of therapeutics based on miRNAs might be an alternative and promising approach for the treatment of SARS-CoV-2 infection.
293T cells and HUVECs were cultured, respectively, supplemented with 10% FBS and 1% penicillin-streptomycin (PS), at 37°C in a humidified environment with 5% CO2. Transfection of 293T cells and HUVECs was performed 24 h after cell seeding and used the transfection reagent Lipofectamine™ 2000 according to the manufacturer’s instructions. Briefly, 3′UTR overexpressing plasmid and miR-486 mimic were mixed with Lipofectamine™ 2000 and the mixture was added to the cell culture medium. The medium was replaced with fresh medium after 6–10 h.
Total RNA was extracted from cells with TRIzol reagent (Invitrogen, USA) following the manufacturer’s instructions, and cDNA was synthesized using the GoScript™ Reverse Transcription System (Promega) according to the manufacturer’s instructions. The qPCR reactions were performed using standard mode on a real-time PCR instrument with GoTaq® qPCR Master Mix kit (Promega). Specific primers for the target miRNA and internal control were designed as: miR-1299 forward 5′-CCGCGCTTCTGGAATTCTGTGT-3′, and miR-1299 reverse 5′-AGTGCAGGGTCCGAGGTATT-3′; miR-214 forward, and miR-214 reverse; miR-296 forward 5′-CGAATATGAGGGTTGGGTGGAGG-3′, and miR-296 reverse 5′-AGTGCAGGGTCCGAGGTATT-3′; miR -302c forward, and miR -302c reverse; miR-520h forward 5′-CCGCGACAAAGTGCTTCCCTT-3′, and miR-520h reverse 5′-AGTGCAGGGTCCGAGGTATT-3′; miR-602 forward 5′-AATGACACGGGCGACAGCTG-3′, and miR-602 reverse 5′-AGTGCAGGGTCCGAGGTATT-3′; miR-766 forward 5′-CGAATACTCCAGCCCCACAGC-3′, and miR-766 reverse 5′-AGTGCAGGGTCCGAGGTATT-3′; and U6 forward, and U6 reverse. Expression levels were normalized to internal controls (U6) and results were shown in form of relative expression calculated by the 2−ΔΔCT method.
Plasmid pDC316 (Microbix Biosystems Inc., Toronto, ON, Canada) is an E1 shuttle plasmid derived from the left end of the adenovirus type 5 (Ad5) genome. The shuttle vector pDC316-mCMV-EGFP and antisense fragment of the 3′UTR gene of SARS-CoV-2 were restriction digested with NotI and EcoRV, respectively. The digested products were purified and ligated with T4 DNA ligase, and then co-transformed into Escherichia coli DH-5α. Thus, the fragment of the 3′UTR gene was cloned into the shuttle plasmid pDC316-mCMV-EGFP, and the homologous recombinant adenoviral plasmid was generated. The resulting pDC316-3′UTR-mCMV-EGFP plasmid was restriction digested with NotI and EcoRV to validate successful construction.
Cell Counting Kit‐8 (CCK‐8, Dojindo, Tokyo, Japan) was used to detect cell proliferation according to the manufacturer’s instructions. Cells (approximately 2,000 per well) were seeded into 96‐well plates and cultured as previously described. Ten microliters of CCK-8 solution mixed with serum‐free medium were added every 24 h. After incubation for 2 h, the absorbance of the wells was detected using a microplate reader at a test wavelength of 450 nm.
The apoptosis rate was evaluated using an Annexin V-FITC/PI Apoptosis Detection kit according to the instructions from the manufacturer. Cells were seeded in 6-well tissue culture plates at 4×105 cells/well. Following treatment, the cells were collected, washed with PBS, and resuspended in 500 μL binding buffer. Next, 5 μL Annexin V-FITC and 5 μL propidium iodide (PI) were added to the cell mixture and incubated at room temperature for 15 min in the dark. Cells were analyzed by flow cytometry (BD FACSCanto) within 1 h.
Cells were seeded in a 6-well tissue culture plate at 4×105 cells/well. After treatment, the cells were collected, washed twice with PBS, and then 100 μL RNase A solution was added and the cells were incubated for 30 min at 37°C. Finally, 500 μL PI was added and incubated for 15 min at room temperature. The cell cycle was analyzed by flow cytometry, with data detection by Cell Quest software (Becton Dickinson, Franklin Lakes, NJ, USA). The percentage of cells in the G1, S, and G2 phases of the cell cycle were analyzed.
Total proteins were extracted from the cells and ELISA kits were employed to analyze the levels of TNF-α and IL-6 following the manufacturer’s instructions (Sangon Biotch, China). The absorbance at 450 nm was detected using a Power Wave Microplate Reader.
The 3′-UTR of the SARS-CoV-2 fragment containing the putative binding site of miRNAs was amplified and cloned downstream of the luciferase gene in the pmirGlo vector (Sangon Biotch, China). The mutant 3′-UTR was used to construct the 3′-UTR-MUT plasmids. 293T cells, at 70–80% confluency, were co-transfected with miRNA (miR-1299, miR-214, miR-296, miR -302c, miR-520h, miR-602, and miR-766) mimics and 3′-UTR-WT. Luciferase activities were assessed 48 h post-transfection using the Dual-Luciferase Reporter Assay System (Promega Biotech Co., Madison, USA).
All data in this study are shown as mean ± standard deviation. Statistical significance was analyzed using a two-tailed Student’s t-test to compare differences between two groups or using one-way analysis of variance (ANOVA; SPSS version 24.0, Chicago, IL, USA) to compare data among groups when they had a normal distribution and homogeneous variances. A p-value < 0.05 was considered statistically significant; *p < 0.05, **p < 0.01, ***p < 0.001.
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
XH, LX, and HY designed the experiment, analyzed data and wrote the manuscript. JY, ZF, QW, and LH did almost molecular experiments and data analysis. ZF did bioinformatics. SG and LL did data analysis and helped experiment design. All authors contributed to the article and approved the submitted version.
This work was supported by Joint Research Project of Health and Education in Fujian Province (2019-WJ-15); Fuzhou Health Science and technology innovation platform construction project (2020-S-wp5); National Natural Science Foundation of China (82172275).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9552444 | Yue Li,Chen Chen,Hai-lin Liu,Zhen-fa Zhang,Chang-li Wang | LARRPM restricts lung adenocarcinoma progression and M2 macrophage polarization through epigenetically regulating LINC00240 and CSF1 | 11-10-2022 | Tumor-associated macrophage,Lung adenocarcinoma,Progression,DNA methylation,CSF1 | Background Long non-coding RNAs (lncRNAs) are critical regulators in lung adenocarcinoma (LUAD). M2-type tumor-associated macrophages (TAMs) also play oncogenic roles in LUAD. However, the involvement of lncRNAs in TAM activation is still largely unknown. Methods The expressions of LARRPM, LINC00240 and CSF1 were determined by RT-qPCR. The regulation of LINC00240 and CSF1 by LARRPM was investigated by RNA–protein pull-down, RNA immunoprecipitation, chromatin immunoprecipitation and bisulfite DNA sequencing. In vitro and in vivo gain- and loss-of-function assays were performed to investigate the roles of LARRPM. Results The lncRNA LARRPM was expressed at low levels in LUAD tissues and cells. The low expression of LARRPM was correlated with advanced stage and poor survival of patients with LUAD. Functional experiments revealed that LARRPM suppressed LUAD cell proliferation, migration and invasion, and promoted apoptosis. LARRPM also repressed macrophage M2 polarization and infiltration. Taken together, LARRPM significantly restricted LUAD progression in vivo. Mechanistically, LARRPM bound and recruited DNA demethylase TET1 to the promoter of its anti-sense strand gene LINC00240, leading to a decrease in DNA methylation level of the LINC00240 promoter and transcriptional activation of LINC00240. Functional rescue assays suggested that the lncRNA LINC00240 was responsible for the roles of LARRPM in the malignant behavior of LUAD cells. LARRPM decreased the binding of TET1 to the CSF1 promoter, resulting in increased DNA methylation of the CSF1 promoter and transcriptional repression of CSF1, which is responsible for the roles of LARRPM in macrophage M2 polarization and infiltration. The TAMs educated by LUAD cells exerted oncogenic roles, which was negatively regulated by LARRPM expressed in LUAD cells. Conclusions LARRPM restricts LUAD progression through repressing both LUAD cell and macrophages. These data shed new insights into the regulation of LUAD progression by lncRNAs and provide data on the potential utility of LARRPM as a target for LUAD treatment. Supplementary Information The online version contains supplementary material available at 10.1186/s11658-022-00376-y. | LARRPM restricts lung adenocarcinoma progression and M2 macrophage polarization through epigenetically regulating LINC00240 and CSF1
Long non-coding RNAs (lncRNAs) are critical regulators in lung adenocarcinoma (LUAD). M2-type tumor-associated macrophages (TAMs) also play oncogenic roles in LUAD. However, the involvement of lncRNAs in TAM activation is still largely unknown.
The expressions of LARRPM, LINC00240 and CSF1 were determined by RT-qPCR. The regulation of LINC00240 and CSF1 by LARRPM was investigated by RNA–protein pull-down, RNA immunoprecipitation, chromatin immunoprecipitation and bisulfite DNA sequencing. In vitro and in vivo gain- and loss-of-function assays were performed to investigate the roles of LARRPM.
The lncRNA LARRPM was expressed at low levels in LUAD tissues and cells. The low expression of LARRPM was correlated with advanced stage and poor survival of patients with LUAD. Functional experiments revealed that LARRPM suppressed LUAD cell proliferation, migration and invasion, and promoted apoptosis. LARRPM also repressed macrophage M2 polarization and infiltration. Taken together, LARRPM significantly restricted LUAD progression in vivo. Mechanistically, LARRPM bound and recruited DNA demethylase TET1 to the promoter of its anti-sense strand gene LINC00240, leading to a decrease in DNA methylation level of the LINC00240 promoter and transcriptional activation of LINC00240. Functional rescue assays suggested that the lncRNA LINC00240 was responsible for the roles of LARRPM in the malignant behavior of LUAD cells. LARRPM decreased the binding of TET1 to the CSF1 promoter, resulting in increased DNA methylation of the CSF1 promoter and transcriptional repression of CSF1, which is responsible for the roles of LARRPM in macrophage M2 polarization and infiltration. The TAMs educated by LUAD cells exerted oncogenic roles, which was negatively regulated by LARRPM expressed in LUAD cells.
LARRPM restricts LUAD progression through repressing both LUAD cell and macrophages. These data shed new insights into the regulation of LUAD progression by lncRNAs and provide data on the potential utility of LARRPM as a target for LUAD treatment.
The online version contains supplementary material available at 10.1186/s11658-022-00376-y.
Although the incidence of lung cancer has been surpassed by that of breast cancer, lung cancer remains the leading cause of cancer death worldwide, with an estimated 2.2 million new cases and 1.8 million deaths in 2020 [1]. Lung adenocarcinoma (LUAD) has become the major histological subtype of lung cancer [2, 3]. Surgical resection is still the major treatment for patients wit LUAD [4]. However, for unresectable and recurrent LUAD, the prognosis is still very poor with currently available chemotherapy and molecule-targeted therapy [5]. More in-depth investigations of the mechanisms driving LUAD progression are urgently needed to develop more efficient treatment. An increasing body of evidence is showing that the tumor microenvironment (TME) plays critical roles in LUAD [6]. In the TME, aberrant apoptosis of T cells is well known, which promotes the development of PD-1/PD-L1 antibodies for LUAD treatment [7]. In addition to T cells, tumor-associated macrophages (TAMs) are critical factors influencing LUAD by significantly promoting LUAD progression [8, 9]. Under specific local environments, monocytes/macrophages generally differentiate into the M1 or M2 subtype [10–12]. M1-polarized macrophages, also known as classical activated macrophages, routinely exert anti-cancerous effects [13, 14]. M2-polarized macrophages, also known as alternatively activated macrophage, routinely exert tumor-promoting effects [12, 15, 16]. Results from an increasing number of investigations suggest that TAMs resemble M2-polarized macrophages [17]. Given the critical roles of TAM in malignancies, many studies have been undertaken to dissect the mechanisms regulating TAM infiltration, polarization and functions [18–21]. Genome and transcriptome high-throughput sequencings have revealed that < 2% of the human genome encodes the information needed to make a protein while about 75% of the human genome encodes for RNAs [22]. Thus, most of RNA transcripts are non-coding RNAs (ncRNAs). Among these ncRNAs, long non-coding RNAs (lncRNAs) are a class of ncRNAs with more than 200 nucleotides in length [23–25]. Many studies have uncovered the critical roles of lncRNAs in many pathophysiological processes [26–31]. A lot of tumor-related lncRNAs have been identified that have oncogenic or tumor suppressive effects, including the regulation of cell proliferation, cell-cycle, apoptosis, motility, drug sensitivity, among others [32–39]. However, the involvement of lncRNAs in TAM activation is still unclear. In the present study, we identified a LUAD-related lncRNA, LOC100270746, with the National Center for Biotechnology Information (NCBI) Reference Sequence Number of NR_026776.1. LOC100270746 is located at chromosome 6p22.2 and at the anti-sense strand of LINC00240. We found that LOC100270746 modulated DNA methylation of the LINC00240 promoter. Thus, LOC100270746 was named LINC00240 antisense RNA regulating promoter methylation (LARRPM). LARRPM is 954 nucleotides (nt) long and has a poly(A) tail. Two online in silico tools, namely Coding Potential Calculator 2 (CPC2) (http://cpc2.gao-lab.org/) and Coding Potential Assessment Tool (CPAT) (http://lilab.research.bcm.edu/), both indicated that LARRPM has no protein-encoding potential. The expression, clinical relevance, functions and mechanisms of action of LARRPM in LUAD were further investigated.
Seventy pairs of frozen LUAD tissues and adjacent lung tissues were acquired from patients with LUAD who had received surgery at our hospital. Written informed consent was obtained from all patients. Clinicopathological features of these 70 patients are provided in Additional file 1: Table S1. This study was conducted in accordance with the Declaration of Helsinki and with the approval of the Ethics Committee of Tianjin Medical University Cancer Institute and Hospital (No. Ek2020183).
Human bronchial epithelial cell 16HBE (Cat. SCC150) was acquired from Merck Millipore (MilliporeSigma, Burlington, MA, USA) and cultured in Airway Epithelial Cell Basal Media (American Type Culture Collection [ATCC], Manassas, VA, USA) supplemented with Bronchial/Tracheal Epithelial Cell Growth Kit components (ATCC). Human LUAD cells A549 (Cat. CCL185), H1299 (Cat. CRL5803), H1975 (Cat. CRL5908), HCC827 (Cat. CRL-2868) and human monocyte line THP-1 (Cat. TIB-202) were obtained from the ATCC and cultured in F12K (A549) or RPMI1640 (H1299, H1975, HCC827, and THP-1) media (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS; Invitrogen, Thermo Fisher Scientific). All cells were cultured in a humidified incubator at 37 °C and under 5% CO2 . These cells were authenticated by their short tandem repeat (STR) profiles and determined to be mycoplasma free. LUAD cells were treated with 0.2 µg/ml anti-CSF1 antibody (AF216; R&D Systems, Minneapolis, MN, USA) and THP-1 cells were treated with 100 ng/ml phorbol-12-myristate-13-acetate (PMA; Sigma-Aldrich, St. Louis, MO, USA).
Total RNA was extracted using the TRIzol Reagent (Invitrogen, Thermo Fisher Scientific). Following quantification by the NanoDrop (Thermo Fisher Scientific), the RNA was subjected to reverse transcription (RT) to generate the first-strand complementary DNA (cDNA) with the M-MLV Reverse Transcriptase (Invitrogen, Thermo Fisher Scientific) and random primers. The cDNA was then subjected to quantitative PCR (qPCR) with the TB Green Premix Ex Taq II (TaKaRa, Tokyo, Japan) on the StepOnePlus Real-Time PCR System (Thermo Fisher Scientific). The primer sequences were as follows: 5′-ATTCATGGTGTCTCTACGCTG-3′ (sense) and 5′-TTTCCCCAAACTCTCCTCTC-3′ (anti-sense) for LARRPM; 5′-TATTCCTTGCCAACCCTCA-3′ (sense) and 5′-GCAGCCAGACAACTTTTTTC-3′ (anti-sense) for LINC00240; 5′-GATCTAGCACAGACCCTTCAC-3′ (sense) and 5′-CGACACCATCGTTACCTTGA-3′ (anti-sense) for MALAT1; 5′-GACTTTAAGGGTTACCTGGGTTG-3′ (sense) and 5′-TCACATGCGCCTTGATGTCTG-3′ (anti-sense) for IL10; 5'-TTTGATGTTGACGGACTG-3' (sense) and 5'-ATAGGCTTGTGATTACCC-3′ (anti-sense) for ARG1; 5′-TTTGTCAACTTGAGTCCCTTCAC-3′ (sense) and 5′-TCCCGCTACACTTGTTTTCAC-3′ (anti-sense) for CD163; 5′-TCCGGGTGCTGTTCTCCTA-3′ (sense) and 5′-CCAGTCTGTTTTTGATGGCACT-3′ (anti-sense) for CD206; 5′-ACCAGGTGGAGTTCAAGAC-3′ (sense) and 5′-CAATAGTCACTGCCCGAAT-3′ (anti-sense) for IL12; 5′-CCTCTCTCTAATCAGCCCTCTG-3′ (sense) and 5′-GAGGACCTGGGAGTAGATGAG-3′ (anti-sense) for TNF-α; 5′-TTCTGTGCCTGCTGCTCA-3′ (sense) and 5′-GGGACACTTGCTGCTGGT-3′ (anti-sense) for CCL2; 5′-AGTTCTCTGCATCACTTGCTG-3′ (sense) and 5′-CGGCTTCGCTTGGTTAGGAA-3′ (anti-sense) for CCL3; 5′-TCTGCGTGACTGTCCTGT-3′ (sense) and 5′-GGCTGCTGGTCTCATAGT-3′ (anti-sense) for CCL4; 5′-TGGCGAGCAGGAGTATCAC-3′ (sense) and 5′-AGGTCTCCATCTGACTGTCAAT-3′ (anti-sense) for CSF1; 5′-ACTCACCTCTTCAGAACGAATTG-3′ (sense) and 5′-CCATCTTTGGAAGGTTCAGGTTG-3′ (anti-sense) for IL6; 5′-ATGTAGCGGATAATGGAAC-3′ (sense) and 5′-ATGTATTGCTTTGCGTTGG-3′ (anti-sense) for IFN-γ; 5′-GAAACCCACAACGAAATCTATG-3′ (sense) and 5′-GCTGAGGTATCGCCAGGAAT-3′ (anti-sense) for TGF-β1; 5′-GGTCTCCTCTGACTTCAACA-3′ (sense) and 5′-GTGAGGGTCTCTCTCTTCCT-3′ (anti-sense) for glyceraldehyde 3-phosphate dehydrogenase (GAPDH). GAPDH was used as endogenous control.
Full-length sequences of the lncRNA LARRPM were amplified by PCR with the primers 5′-CCCAAGCTTACAGGAACATCCGGCGT-3′ (sense) and 5′-CGGGATCCACACCTTAAATATATAGTTTT-3′ (anti-sense), which were further cloned into the HindIII and BamHI sites of the pcDNA3.1(+) vector (Invitrogen, Thermo Fisher Scientific) to construct the LARRPM expression vector. LARRPM full-length sequences were also cloned into the HindIII and BamHI sites of the pSPT19 vector (Roche, Basel, Switzerland) to construct the LARRPM in vitro transcription vector. LINC00240 full-length sequences were amplified by PCR with the primers 5′-GGAATTCGTAATCCTCCCAGGGATT-3′ (sense) and 5′-GCTCTAGATATCTTCAAAGCTCAAGGTCAC-3′ (anti-sense) and the sequences subsequently cloned into the EcoRI and XbaI sites of the pcDNA3.1(+) vector to construct the LINC00240 expression vector. To generate LUAD cells with LARRPM stable overexpression, the LARRPM expression plasmid or pcDNA3.1(+) vector was transfected into A549 and H1975 cells by Lipofectamine 3000 (Invitrogen, Thermo Fisher Scientific). The cells were then treated with 1000 µg/ml neomycin to select cells overexpressing LARRPM or control cells. To generate LUAD cells with LINC00240 stable overexpression, the LINC00240 expression vector or the pcDNA3.1(+) vector was transfected into A549 cells using Lipofectamine 3000. The cells were then treated with 1000 µg/ml neomycin to select LINC00240-overexpressing cells. Two pairs of cDNA oligonucleotides targeting LARRPM and one pair of cDNA oligonucleotides targeting LINC00240 were generated and cloned into the GenePharma Supersilencing Vector pGLVU6/Puro (GenePharma, Shanghai, China), which were further used to generate lentivirus short hairpin RnAs (shRNAs). Scrambled non-targeting lentivirus shRNA was employed as the control. The shRNA oligonucleotide sequences were as follows: 5′-GATCCGGGATTTACCAAACGCATTCCTTCAAGAGAGGAATGCGTTTGGTAAATCCCTTTTTTG-3′ (sense) and 5′-AATTCAAAAAAGGGATTTACCAAACGCATTCCTCTCTTGAAGGAATGCGTTTGGTAAATCCCG-3′ (anti-sense) for shRNA-LARRPM-1; 5′-GATCCGGTGTCTCTACGCTGAGTTAATTCAAGAGATTAACTCAGCGTAGAGACACCTTTTTTG-3′ (sense) and 5′-AATTCAAAAAAGGTGTCTCTACGCTGAGTTAATCTCTTGAATTAACTCAGCGTAGAGACACCG-3′ (anti-sense) for shRNA-LARRPM-2; 5′-GATCCGCAGTGAGTTAGCTACCTTCTTTCAAGAGAAGAAGGTAGCTAACTCACTGCTTTTTTG-3′ (sense) and 5′-AATTCAAAAAAGCAGTGAGTTAGCTACCTTCTTCTCTTGAAAGAAGGTAGCTAACTCACTGCG-3′ (anti-sense) for shRNA-LINC00240; 5′-GATCCGTTCTCCGAACGTGTCACGTTTCAAGAGAACGTGACACGTTCGGAGAACTTTTTTG-3′ (sense) and 5′-AATTCAAAAAAGTTCTCCGAACGTGTCACGTTCTCTTGAAACGTGACACGTTCGGAGAACG-3′ (anti-sense) for the shRNA-control. To generate LUAD cells with LARRPM stable silencing, LARRPM specific or control lentivirus shRNAs were infected into HCC827 cells. The cells were then treated with 2 µg/ml puromycin to select the LARRPM silenced cells or the control cells. To generate LUAD cells with LINC00240 stable silencing and LARRPM stable overexpression, LINC00240-specific or control lentivirus shRNAs were infected into A549 cells overexpressing LARRPM. The cells were then treated with 2 µg/ml puromycin and 1000 µg/ml neomycin to select cells with silencing of the lncRNA LINC00240 and LARRPM overexpression.
Cell proliferation was assessed by the Cell Counting Kit-8 (CCK-8) and 5-ethynyl-2′-deoxyuridine (EdU) incorporation assays. The CCK-8 assay was carried out using the Cell Counting Kit-8 (Cat. CK04-11; Dojindo, Kumamoto, Japan), and the EdU incorporation assay was performed using the Cell-Light EdU Apollo567 In Vitro Kit (Cat. C10310-1; RiboBio, Guangzhou, China). Cell apoptosis was evaluated using the caspase-3 activity assay and terminal deoxynucleotidyl transferase (TdT)-mediated dUTP nick end labelling (TUNEL) assay. Caspase-3 activity assay was carried out using the Caspase 3 Activity Assay Kit (Cat. C1115; Beyotime, Shanghai, China). The TUNEL assay was carried out using the One Step TUNEL Apoptosis Assay Kit (Cat. C1086; Beyotime). Cell migration and invasion were evaluated by transwell migration and invasion assays, respectively, both of which were performed as previously described without or with precoated Matrigel [40].
Female BALB/C athymic nude mice (7–8 weeks old) were acquired from the Model Animal Research Center of Nanjing University (Nanjing, China) and fed under specific pathogen-free (SPF) conditions. The chosen LUAD cells were injected into the tail vein of the mice, and 6 weeks later the mice were sacrificed, following which the lungs were resected and stained with hematoxylin and eosin (HE) to evaluate the growth and metastasis of LUAD cells in the lungs. In vivo proliferation was evaluated by immunohistochemistry (IHC) assay using primary antibodies against Ki67 (ab15580, 1:200; Abcam, Cambridge, UK) or PCNA (ab29, 1:6000; Abcam) as previously described [41]. In vivo apoptosis was evaluated using the TUNEL assay with the In Situ Cell Death Detection Kit TMR red (Cat. 12156792910; Roche) following the manufacturer’s manual. Macrophage infiltration was evaluated using immunofluorescence (IF) staining with the primary antibody against the F4/80 antigen (#30325, 1:400; Cell Signaling Technology, Boston, MA, USA). The investigators performing the HE, IHC, IF and TUNEL assays were blinded to mice allocation. The animal experiments were approved by the Ethics Committee of Tianjin Medical University Cancer Institute and Hospital (No. Ek2020183).
Cytoplasmic and nuclear RNA were isolated from A549 cells using the PARIS Kit (Cat. AM1921; Invitrogen, Thermo Fisher Scientific). The isolated RNA was further subjected to RT-qPCR.
LARRPM was transcribed from the LARRPM in vitro transcription plasmid with T7 RNA polymerase (Roche). After purification, LARRPM was end-labeled with desthiobiotin by the RNA 3' End Desthiobiotinylation Kit (Pierce, Thermo Fisher Scientific). The desthiobiotinylated RNA was further subjected to RNA–protein pull-down reaction with the Magnetic RNA–Protein Pull-Down Kit (Pierce, Thermo Fisher Scientific). The enriched protein was measured by western blot using the primary antibodies against DNA demethylase TET1 (ab191698 1 µg/ml; Abcam) or GAPDH (60004-1-Ig, 1:10000; Proteintech, Chicago, IN, USA) as previously described [42].
The RNA immunoprecipitation (RIP) assay was conducted using the EZ-Magna RIP Kit (MilliporeSigma) and primary antibody against TET1 (SAB2700730, 5 µg; Sigma-Aldrich). The enriched RNA was measured by RT-qPCR.
The chromatin immunoprecipitation (ChIP) assay was conducted with the ChIP Kit (ab500; Abcam) and the primary antibody against TET1 (SAB2700730, 5 µg; Sigma-Aldrich). The enriched DNA was measured by qPCR with the primers 5′-TTCCAGGGCTGTTTCTCG-3′ (sense) and 5′-CACTTCCGTTCCCGCTTA-3′ (anti-sense) for the LINC00240 promoter and the primers 5′-GATTTCCCATAAACCACAT-3′ (sense) and 5′-CCCAGGCAAACTTTCACT-3′ (anti-sense) for the CSF1 promoter. Their respective distal regions were used as negative controls, and the primer sequences were as follows: 5′-TCAACTAATGGTGGAAAG-3′ (sense) and 5′-CCAATGTAATGGTGCTAA-3′ (anti-sense) for the negative control of the LINC00240 promoter; 5′-ACAAGGGCATTCAGTCCA-3′ (sense) and 5′-CGTCAGAGCCAGAGCATC-3′ (anti-sense) for the negative control for the CSF1 promoter.
DNA methylation was measured using the bisulfite DNA sequencing method. DNA was extracted with the TIANamp Genomic DNA Kit (TIANGEN, Beijing, China), followed by bisulfite treatment with the EZ DNA Methylation-Gold Kit (Zymo Research, Irvine, CA, USA). Modified genomic DNA was amplified by PCR with the primers 5′-AGTTTTTTTGGAAAGAAGTA-3′ (sense) and 5′-TCCTTACACAACCTACAC-3′ (anti-sense) for CpG43, and 5′-AGGGTTGGTTAGTGAGGTT-3′ (sense) and 5′-ATCATACAAACAACTAAATCC-3′ (anti-sense) for CpG82. The PCR products were gel-extracted, cloned into the pMD-19 T vector (Takara), transformed into Escherichia coli cells and sequenced. DNA hydroxymethylation was measured using the EpiMark 5-hmC Analysis Kit (New England Biolabs, Ipswich, MA, USA), followed by qPCR to detect DNA hydromethylation of CpG43 and CpG82 with the above-described premiers.
After co-culture with LUAD cells, the PMA-stimulated THP-1 cells were first incubated with primary antibodies against CD163 (ab87099, 5 µg/ml; Abcam) or CD206 (#91992, 1:200; Cell Signaling Technology Cell Signaling). The cells were then incubated with goat anti-rabbit IgG (Alexa Fluor 488; Invitrogen, Thermo Fisher Scientific), stained with DAPI and photographed on a Zeiss photomicroscope (Carl Zeiss, Oberkochen, Germany).
An enzyme-linked immubosorbent assay (ELISA) was performed to measure CSF1 concentrations in cell culture supernates of the indicated LUAD cells using the Human M-CSF ELISA Kit (Cat. DY216; R&D Systems).
The GraphPad Prism version 6.0 software package (GraphPad Software, San Diego, CA, USA) was used to conduct all statistical analyses. Details on the statistical methods applied are shown in the figure and provided in the table captions. P < 0.05 was considered to indicate statistically significance.
To analyze the clinical significance of LARRPM in LUAD, we first explored The Cancer Genome Atlas (TCGA) LUAD dataset using the online in silico tool R2 (https://hgserver1.amc.nl/cgi-bin/r2/main.cgi). The results showed that low LARRPM expression was correlated with poor overall survival in LUAD (Fig. 1a). The TCGA LUAD dataset also revealed that the expression of LARRPM was lower in tumor (T)2-stage LUAD tissues than in T1-stage LUAD tissues (Fig. 1b). The expression of LARRPM was also lower in stage II LUAD tissues than that in stage I LUAD tissues (Fig. 1c). To further confirm the clinical relevance of LARRPM in LUAD, we collected 70 pairs of LUAD and matched adjacent lung tissues. In our cohort, we also found that low expression of LARRPM in LUAD tissues was correlated with poor overall survival of patients with LUAD (Fig. 1d). Low expression of LARRPM was also correlated with large tumor size, local invasion and advanced TNM stages in our cohort (Additional file 1: Table S1). Furthermore, LARRPM was lowly expressed in LUAD tissues compared with that in noncancerous lung tissues (Fig. 1e). The expression of LARRPM in cells of human bronchial epithelial cell line 16HBE and in LUAD cells A549, H1299, H1975, and HCC827 was measured. The results revealed that, consistent with the expression pattern in tissues, LARRPM was also lowly expressed in LUAD cells compared with bronchial epithelial cell (Fig. 1f). These findings identified LARRPM as a lowly expressed and prognosis-related lncRNA in LUAD.
To investigate whether LARRPM plays active roles in LUAD progression, we constructed A549 and H1975 cells with LARRPM stable overexpression (Fig. 2a). CCK-8 assays showed that both A549 and H1975 cells with LARRPM overexpression had reduced cell viability (Fig. 2b). EdU incorporation assays revealed that both A549 and H1975 cells with LARRPM overexpression had reduced EdU-positive cells (Fig. 2c), indicating decreased cell proliferation. Caspase-3 activity assays revealed that both A549 and H1975 cells with LARRPM overexpression had increased caspase-3 activity (Fig. 2d), indicating increased cell apoptosis. TUNEL assays revealed that both A549 and H1975 cells with LARRPM overexpression had an increased number of TUNEL-positive cells (Fig. 2e), also indicating increased cell apoptosis. Transwell migration assays revealed that both A549 and H1975 cells with LARRPM overexpression had decreased cell migration (Fig. 2f). Transwell invasion assays revealed that both A549 and H1975 cells with LARRPM overexpression had decreased cell invasion (Fig. 2g). To further investigate the roles of LARRPM in LUAD, we constructed HCC827 cells with LARRPM stable silencing via infection by two independent LARRPM-specific lentivirus shRNAs (Additional file 2: Figure S1A). The CCK-8 and EdU incorporation assays revealed that LARRPM silencing promoted cell proliferation (Additional file 2: Figure S1B, C). Caspase-3 activity assays and TUNEL assays showed that LARRPM silencing reduced cell apoptosis (Additional file 2: Fig. S1D, E). Transwell migration and invasion assays revealed that LARRPM silencing increased cell migration and invasion (Additional file 2: Figure S1F, G). Collectively, these findings suggested that LARRPM exerted tumor suppressive roles in LUAD in vitro.
The roles of LARRPM in LUAD in vivo were then explored. A549 cells with LARRPM stable overexpression or control cells were injected into the tail vein of nude mice. Six weeks later, the lungs were resected and detected by HE staining. As shown in Fig. 3a, A549 cells with LARRPM overexpression formed significantly smaller and fewer lung metastatic nodules than the control A549 cells. IHC staining of proliferation markers Ki67 and PCNA revealed that the tumors formed by A549 cells with LARRPM overexpression had significantly fewer Ki67- and PCNA-positive cells (Fig. 3b, c), indicating that LARRPM inhibited cell proliferation in vivo. TUNEL assays revealed that the tumors formed by A549 cells with LARRPM overexpression had increased proportion of TUNEL-positive cells (Fig. 3d), indicating that LARRPM promoted cell apoptosis in vivo. In addition, IF staining of macrophage marker F4/80 revealed that the tumors formed by A549 cells with LARRPM overexpression had significantly reduced macrophage infiltration (Fig. 3e). Taken together, these findings suggested that LARRPM restricted LUAD progression via regulating both cancer cells and macrophages.
To dissect the mechanisms mediating the roles of LARRPM in LUAD, we first detected the subcellular localization of LARRPM in LUAD cells. Subcellular fractionation followed by qRT-PCR revealed that LARRPM was predominantly localized in the nucleus (Fig. 4a). The genomic localization of LARRPM was at the anti-sense strand of LINC00240 (Fig. 4b), which has been reported to play various roles in different cancers [43–45]. We then studied the effect of LARRPM on LINC00240. The qRT-PCR results showed that LINC00240 increased when LARRPM was overexpressed (Fig. 4c) and decreased when LARRPM was silenced (Fig. 4d). Taking into account that the promoter of LINC00240 contained the CpG island CpG43 (Fig. 4b), we hypothesized that LARRPM may modulate LINC00240 expression via DNA methylation. Intriguingly, the online in silico tool RNA–Protein Interaction Prediction (RPISeq) (http://pridb.gdcb.iastate.edu/RPISeq/index.html) predicted a strong interaction between LARRPM and DNA demethylase TET1, with an interaction probability score of 0.9. RNA–protein pull-down assays showed that TET1 was specifically enriched by LARRPM (Fig. 4e), and RIP assays showed that LARRPM was specifically enriched with TET1 antibody (Fig. 4f). Both the RNA–protein pull-down assays and RIP assays indicated interaction between LARRPM and TET1. ChIP assays were performed to investigate whether LARRPM modulates the binding of TET1 to the LINC00240 promoter. The results showed that ectopic expression of LARRPM promoted the binding of TET1 to the LINC00240 promoter, while depletion of LARRPM inhibited the binding of TET1 to the LINC00240 promoter (Fig. 4g, h). In line with the binding of TET1 to the LINC00240 promoter, ectopic expression of LARRPM increased the level of 5-hydroxymethylcyctosine (5hmC), while depletion of LARRPM decreased the level of 5hmC at the LINC00240 promoter (Fig. 4i, j). The DNA methylation level of CpG43 was reduced when LARRPM was overexpressed, and increased when LARRPM was depleted (Fig. 4k, l). The TCGA LUAD dataset showed a significantly positive correlation between LINC00240 and LARRPM expression in LUAD tissues (Additional file 3: Figure S2A). In our own cohort, there was a significant positive correlation between LINC00240 and LARRPM expression in LUAD tissues (Additional file 3: Fig. S2B). We also randomly selected 20 LUAD tissues and measured 5hmC levels at the LINC00240 promoter; the results showed that LUAD tissues with high LARRPM expression had higher 5hmC levels at the LINC00240 promoter compared with LUAD tissues with low LARRPM expression (Additional file 3: Figure S2C). In these 20 LUAD tissues we further found that LUAD tissues with high LARRPM expression had a reduced DNA methylation level of CpG43 compared with LUAD tissues with low LARRPM expression (Additional file 3: Figure S2D). These clinical data supported the regulation of LINC00240 by LARRPM via TET1-mediated DNA demethylation. Collectively, these findings suggested that LARRPM bound to and recruited TET1 to LINC00240 promoter, induced DNA demethylation of LINC00240 promoter, and activated LINC00240 expression.
To further confirm the roles of LINC00240 in LUAD, we constructed A549 cells with LINC00240 stable overexpression (Additional file 4: Figure S3A). CCK-8 and EdU incorporation assays showed that overexpression of LINC00240 repressed cell proliferation (Additional file 4: Figure S3B, C). The results of the caspase-3 activity and TUNEL assays showed that overexpression of LINC00240 promoted cell apoptosis (Additional file 4: Figure S3D, E), and the results of the transwell migration and invasion assays showed that ectopic expression of LINC00240 repressed cell migration and invasion (Additional file 4: Figure S3F, G). These findings suggested that consistent with LARRPM, LINC00240 also exerted tumor suppressive effects in LUAD. To investigate whether LINC00240 mediates the tumor suppressive roles of LARRPM in LUAD, we stably depleted LINC00240 expression in A549 cells with LARRPM stable overexpression (Fig. 5a). The CCK-8 and EdU incorporation assays revealed that depletion of LINC00240 attenuated the roles of LARRPM in repressing cell proliferation (Fig. 5b, c); the caspase-3 activity and TUNEL assays revealed that depletion of LINC00240 attenuated the roles of LARRPM in promoting cell apoptosis (Fig. 5e, e); and the transwell migration and invasion assays revealed that depletion of LINC00240 attenuated the roles of LARRPM in repressing cell migration and invasion (Fig. 5f, g). Take together, these findings suggested that LINC00240 at least partially mediated the tumor suppressive roles of LARRPM in LUAD.
Observing that LARRPM repressed macrophage infiltration in vivo, we further investigated the effects of LARRPM on macrophages by in vitro co-culture system (Fig. 6a). A549 cells with LARRPM overexpression inhibited macrophage migration compared with control A549 cells (Fig. 6b). HCC827 cells with LARRPM silencing promoted macrophage migration compared with control HCC827 cells (Fig. 6c). The expressions of M1 and M2 markers in macrophages after co-culture with LUAD cells were measured. It was noted that after co-culture with LARRPM overexpressed A549 cells, M2 markers in macrophages were decreased and M1 markers were increased, compared with those co-cultured with control A549 cells (Fig. 6d). Consistently, M2 markers were increased and M1 markers were decreased after co-culture with LARRPM silenced HCC827 cells, compared with those co-cultured with control HCC827 cells (Fig. 6e). IF staining of cell surface protein CD163 and CD206, which are classical M2 markers, revealed that both CD163 and CD206 levels were decreased after co-culture with A549 cells overexpressing LARRPM and increased after co-culture with LARRPM silenced HCC827 cells (Fig. 6f, g). These findings suggested that LARRPM repressed infiltration of macrophages and M2 polarization.
To dissect the mechanisms mediating the roles of LARRPM in M2 macrophage infiltration, we measured the expression of cytokines which were involved in macrophage recruitment and polarization [46, 47]. The results showed that CSF1 was the most significantly altered molecule after LARRPM overexpression or depletion (Fig. 7a, b), with its level decreasing after LARRPM overexpression and increasing after LARRPM silencing (Fig. 7a–c). Given that the promoter of CSF1 was also occupied by the CpG island CpG82, we investigated whether LARRPM modulates the binding of TET1 to the CSF1 promoter. Conversely to the effects of LARRPM on the LINC00240 promoter, ectopic expression of LARRPM decreased the binding of TET1 to the CSF1 promoter (Fig. 7d), while depletion of LARRPM increased the binding of TET1 to the CSF1 promoter (Fig. 7e). In line with the binding of TET1 to the CSF1 promoter, ectopic expression of LARRPM decreased the 5hmC level at the CSF1 promoter, while depletion of LARRPM increased the 5hmC level (Fig. 7f, g). The DNA methylation level of CpG82 increased when LARRPM was overexpressed, and decreased when LARRPM was depleted (Fig. 7h, i). An ELISA showed that ectopic expression of LARRPM decreased CSF1 concentration in the supernatant, while silencing of LARRPM increased CSF1 concentration in the supernatant (Fig. 7j, k). The TCGA LUAD dataset showed a negative correlation between CSF1 and LARRPM expression in LUAD tissues (Additional file 5: Figure S4A). In our own cohort, a significant negative correlation between CSF1 and LARRPM expression was also found in LUAD tissues (Additional file 5: Figure S4B). Furthermore, LUAD tissues with high LARRPM expression had a reduced 5hmC level at the CSF1 promoter compared with LUAD tissues with low LARRPM expression (Additional file 5: Figure S4C). LUAD tissues with high LARRPM expression had an increased DNA methylation level of CpG82 compared with LUAD tissues with low LARRPM expression (Additional file 5: Figure S4D). These findings supported the negative regulation of CSF1 by LARRPM via TET1-mediated DNA demethylation. To assess whether CSF1 mediates the roles of LARRPM in repressing M2 macrophage infiltration, anti-CSF1 antibody was added to LUAD cells. In the presence of anti-CSF1, LARRPM overexpression in A549 cells did not regulate macrophage migration (Additional file 6: Figure S5A). Similarly, in the presence of anti-CSF1, LARRPM silencing in HCC827 cells also did not regulate macrophage migration (Additional file 6: Figure S5B). In the presence of anti-CSF1, LARRPM overexpression in A549 cells did not regulate the expressions of M1 and M2 markers in macrophages after co-culture (Additional file 6: Figure S5C). Similarly, in the presence of anti-CSF1, LARRPM silencing in HCC827 cells also not regulate the expressions of M1 and M2 markers in macrophages after co-culture (Additional file 6: Figure S5D). Collectively, these findings suggested that LARRPM repressed CSF1 production via increasing DNA methylation level of CSF1 promoter. CSF1 was the critical mediator of the roles of LARRPM in repressing M2 macrophage infiltration.
We also looked at the roles of infiltrated M2 macrophages on LUAD cells. The conditioned medium (CM) was collected from co-culture of macrophages with A549 cells with LARRPM overexpression or control A549 cells. Next, mock A549 cells were treated with the the CM. CCK-8 and EdU incorporation assays revealed that macrophage/A549 co-culture CM promoted A549 cell proliferation compared with A549 CM (Fig. 8a, b). Ectopic expression of LARRPM repressed the increased proliferation of A549 cells induced by macrophages (Fig. 8a, b). The results of the caspase-3 activity and TUNEL assays showed that macrophage/A549 co-culture CM inhibited A549 cell apoptosis compared with A549 CM (Fig. 8c, d). Ectopic expression of LARRPM reversed the reduced apoptosis of A549 cells induced by macrophages (Fig. 8c, d). Transwell migration and invasion assays revealed that macrophage/A549 co-ulture CM promoted A549 cell migration and invasion compared with A549 CM (Fig. 8e, f). Ectopic expression of LARRPM repressed the increased migration and invasion of A549 cells induced by macrophages (Fig. 8e, f). CM was also collected from co-culture of macrophages with HCC827 with LARRPM depletion or control HCC827 cells, and this CM used to stimulate mock HCC827 cells. The CCK-8 and EdU incorporation assays revealed that macrophage/HCC827 co-culture CM promoted HCC827 cell proliferation compared with HCC827 CM (Additional file 7: Figure S6A, B). CM from the co-culture of macrophages with HCC827 cells with LARRPM depletion more strongly promoted HCC827 cell proliferation (Additional file 7: Figure S6A, B). The results of the caspase-3 activity and TUNEL assays showed that macrophage/HCC827 co-culture CM inhibited HCC827 cell apoptosis compared with HCC827 CM (Additional file 7: Figure S6C, D). CM from co-culture of macrophages with HCC827 cells with LARRPM more strongly inhibited HCC827 cell apoptosis (Additional file 7: Figure S6C, D). The transwell migration and invasion assays revealed that macrophage/HCC827 co-culture CM promoted HCC827 cell migration and invasion compared with HCC827 CM (Additional file 7: Figure S6E, F). CM from co-culture of macrophages with HCC827 cells with LARRPM depletion more strongly promoted HCC827 cell migration and invasion (Additional file 7: Figure S6E, F). These findings suggested that LUAD cells-educated M2 macrophages exerted oncogenic effects in LUAD, which were negatively modulated by LARRPM in LUAD cells.
We identified a novel lncRNA, LARRPM, which mediates the crosstalk between LUAD cells and macrophages. LARRPM is 954 nt long and has only one exon. It is predominantly distributed in the nucleus and has a polyA tail. In the present study, LARRPM was downregulated in LUAD tissues and cells compared with noncancerous lung tissues and bronchial epithelial cells. Low expression of LARRPM was correlated with large tumor size, local invasion, advanced TMN stage, and poor prognosis of patients with LUAD. Our data suggest that LARRPM is a potential prognostic biomarker for LUAD. The clinical relevance of LARRPM in other histological subtypes of lung cancer requires further study. Our functional investigations showed that LARRPM repressed LUAD cell proliferation, migration and invasion, and promoted LUAD cell apoptosis in vitro. In vivo xenograft assays showed that LARRPM suppressed LUAD tumor growth and metastasis, repressed LUAD cell proliferation and induced LUAD cell apoptosis in vivo. Further, LARRPM was found to reduce the number of M2 macrophages in xenografts. In vitro dissections revealed that LARRPM repressed macrophage M2 polarization and migration. TAMs have been reported to have tumor promotive effects in many tumors [48–50]. In the present study, we also found that TAMs educated by LUAD cells promoted LUAD cell proliferation, migration and invasion, and repressed LUAD cell apoptosis. The oncogenic roles of TAMs decreased after co-culture with LUAD cells overexpressing LARRPM and increased after co-culture with LUAD cells with LARRPM depletion. Our findings suggest that LARRPM functions as a tumor repressor in LUAD through regulating both LUAD cells and TAMs. Mechanistic dissections revealed that as a nuclear lncRNA, LARRPM bound to DNA demethylase TET1 and recruited TET1 to the promoter of its anti-sense strand gene LINC00240. Intriguingly, a CpG island was located at the promoter of LINC00240. Thus, LARRPM decreased the DNA methylation level of the LINC00240 promoter, leading to the transcriptional activation of LINC00240. The positive correlation between the expression of LARRPM and LINC00240 in LUAD tissues supported the upregulation of LINC00240 by LARRPM in vivo. Functional rescue assays documented that LINC00240 was the critical mediator of the roles of LARRPM in LUAD cell proliferation, apoptosis, migration and invasion. The current study provides novel evidence for the roles of lncRNAs as epigenetic modulators. Many nuclear lncRNAs have been found to bind to epigenetic modification enzymes, such as histone methyltransferase, histone acetyltransferase, histone deacetylase and DNA methyltransferase [51–53]. Through binding to these epigenetic modification enzymes, lncRNAs change their genomic location, leading to alteration of the epigenetic modification status of target genes, and further the activation or repression of target gene transcription [51–53]. In this study, we further found that, with the exception of LINC00240, LARRPM also modulated the genomic binding of TET1 to the CSF1 promoter. The CSF1 promoter also had a CpG island. In contrast to the LINC00240 promoter, LARRPM decreased the binding of TET1 to the CSF1 promoter. Therefore, LARRPM increased the DNA methylation level of the CSF1 promoter, leading to the transcriptional repression of CSF1. The negative correlation between LARRPM expression and CSF1 expression in LUAD tissues supports the downregulation of CSF1 by LARRPM in vivo. As a methylcytosine dioxygenase and a DNA demethylase, TET1 binds and regulates many genomic sites, such as the tumor suppressor TCF21 [54]. The potential influence of LARRPM on other TET1 targets needs further investigation. CSF1, also known as macrophage colony stimulating factor (M-CSF), has been documented to induce M2 polarization, recruitment and survival in macrophages [47, 55]. In the present study, we identified CSF1 as a critical downstream target of LARRPM. LARRPM repressed CSF1 transcription, leading to the decreasing of CSF1 secretion. Functional rescue assays using CSF1 blocking antibody documented that CSF1 was a critical mediator of the roles of LARRPM in macrophage polarization and recruitment. M2-polarized TAMs have been found to be correlated with poor survival in lung cancer [56]. Here we also found that macrophages educated by LUAD cells exerted oncogenic effects on LUAD cells. LARRPM overexpressed LUAD cells overexpression LARRPM repressed the oncogenic roles of macrophages after co-culture, which was consistent with the repressive roles of LARRPM on macrophage infiltration and M2 polarization. Our findings suggest that the LARRPM-CSF1 regulatory axis at least partially mediated the crosstalk between LUAD cells and macrophages.
In summary, we identified LARRPM as a novel LUAD-related lncRNA. LARRPM was lowly expressed in LUAD, and its low expression was correlated with poor prognosis of patients with LUAD. LARRPM was observed to act as a tumor suppressor in LUAD through regulating both LUAD cells and macrophages. LARRPM repressed the malignant behaviors of LUAD cells via epigenetically upregulating LINC00240. LARRPM repressed macrophage infiltration and M2 polarization via epigenetically repressing CSF1. Our findings suggest LARRPM as a prognostic biomarker for LUAD, and enhancing LARRPM expression might be a novel strategy for LUAD treatment.
Additional file 1: Table S1. Relationships between LARRPM expression and clinicopathological features in LUAD.Additional file 2: Figure S1. Depletion of LARRPM promoted proliferation, repressed apoptosis and promoted migration and invasion of LUAD cells. A LARRPM expression in HCC827 cells with LARRPM stable depletion or control was detected by qRT-PCR. B Cell proliferation of HCC827 cells with LARRPM stable depletion or control was detected using CCK-8 assays. C Cell proliferation of HCC827 cells with LARRPM stable overexpression or control was detected using EdU incorporation assays. Scale bar: 100 µm. Red color indicates EdU-positive cells. D Cell apoptosis of HCC827 cells with LARRPM stable depletion or control was detected using caspase-3 activity assays. E Cell apoptosis of HCC827 cells with LARRPM stable depletion or control was detected using TUNEL assays. Scale bar: 100 µm. Green color indicates TUNEL-positive cells. F Cell migration of HCC827 cells with LARRPM stable depletion or control was detected using transwell migration assays. Scale bar: 100 µm. G Cell invasion of HCC827 cells with LARRPM stable depletion or control was detected using transwell invasion assays. Scale bar: 100 µm. Results are shown as mean ± SD based on three independent experiments. *P < 0.05, **P < 0.01, ***P < 0.001 by one-way ANOVA followed by Dunnett's multiple comparisons test.Additional file 3: Figure S2. The correlation between LARRPM expression, 5hmC level at LINC00240 promoter, CpG43 methylation level and LINC00240 expression in LUAD tissues. A Correlation between LINC00240 and LARRPM expression analysed using the TCGA LUAD data. r = 0.6164, P < 0.0001 by Spearman correlation analysis. B Correlation between LINC00240 and LARRPM expression analyzed in our LUAD cohort. r = 0.5521, P < 0.0001 by Spearman correlation analysis. C 5hmC levels of CpG43 from 20 LUAD tissues were measured using the EpiMark 5-hmC Analysis Kit. Median LARRPM expression level was used as cut-off. P = 0.0094 by Mann–Whitney test. D DNA methylation levels of CpG43 from 20 LUAD tissues were measured using bisulfate DNA sequencing. Median LARRPM expression level was used as cut-off. P = 0.0015 by Mann–Whitney test.Additional file 4: Figure S3. LINC00240 repressed proliferation, induced apoptosis and inhibited migration and invasion of LUAD cells. A LINC00240 expression in A549 cells with LINC00240 stable overexpression or control was detected by qRT-PCR. B Cell proliferation of A549 cells with LINC00240 stable overexpression or control was detected using CCK-8 assays. C Cell proliferation of A549 cells with LINC00240 stable overexpression or control was detected using EdU incorporation assays. Scale bar: 100 µm. Red color indicates EdU-positive cells. D Cell apoptosis of A549 cells with LINC00240 stable overexpression or control was detected using caspase-3 activity assays. E Cell apoptosis of A549 cells with LINC00240 stable overexpression or control was detected using TUNEL assays. Scale bar: 100 µm. Green color indicates TUNEL-positive cells. F Cell migration of A549 cells with LINC00240 stable overexpression or control was detected using transwell migration assays. Scale bar: 100 µm. G Cell invasion of A549 cells with LINC00240 stable overexpression or control was detected using transwell invasion assays. Scale bar: 100 µm. Results are shown as mean ± SD based on three independent experiments. *P < 0.05, **P < 0.01 by Student’s t-test.Additional file 5: Figure S4. The correlation between LARRPM expression, 5hmC level at CSF1 promoter, CpG82 methylation level and CSF1 expression in LUAD tissues. A Correlation between CSF1 and LARRPM expression analysed using the TCGA LUAD data. r = − 0.3069, P < 0.0001 by Spearman correlation analysis. B Correlation between CSF1 and LARRPM expression analysed in our LUAD cohort. r = − 0.5774, P < 0.0001 by Spearman correlation analysis. C 5hmC levels of CpG82 from 20 LUAD tissues were measured using the EpiMark 5-hmC Analysis Kit. Median LARRPM expression level was used as cut-off. P = 0.0245 by Mann–Whitney test. D DNA methylation levels of CpG82 from 20 LUAD tissues were measured using bisulfate DNA sequencing. Median LARRPM expression level was used as cut-off. P = 0.0288 by Mann–Whitney test.Additional file 6: Fig. S5. Anti-CSF1 antibody abolished the effects of LARRPM on M2 macrophage infiltration. A THP-1 cells were subjected to transwell migration assays towards A549 cells with LARRPM overexpression or A549 control cells treated with anti-CSF1. Scale bar: 100 µm. B THP-1 cells were subjected to transwell migration assays towards HCC827 cells with LARRPM depletion or HCC827 control treated with anti-CSF1. Scale bar: 100 µm. C M1 and M2 polarization markers expression in THP-1 cells co-cultured with A549 cells with LARRPM overexpression or control A549 cells treated with anti-CSF1 were detected by qRT-PCR. D Expression of M1 and M2 polarization markers in THP-1 cells co-cultured with HCC827 cells with LARRPM depletion or control HCC827 cells treated with anti-CSF1 were detected by qRT-PCR. Results are shown as the mean ± SD based on three independent experiments. ns: Not significant by Student’s t-test.Additional file 7: Fig. S6. Depletion of LARRPM in LUAD cells enhanced the oncogenic roles of infiltrated M2 macrophages. A–F Conditioned medium (CM) was collected from co-culture of macrophages with HCC827 cells with LARRPM depletion or control HCC827 cells, or collected from only HCC827 cells with LARRPM depletion or control HCC827 cells. A Cell proliferation of HCC827 cells treated with the CM was detected using CCK-8 assays. B Cell proliferation of HCC827 cells treated with the CM was detected using EdU incorporation assays. Scale bar: 100 µm. Red color indicates EdU-positive cells. C Cell apoptosis of HCC827 cells treated with the CM was detected using caspase-3 activity assays. D Cell apoptosis of HCC827 cells treated with the CM was detected using TUNEL assays. Scale bar: 100 µm. Green color indicates TUNEL-positive cells. E Cell migration of HCC827 cells treated with the CM was detected using transwell migration assays. Scale bar: 100 µm. F Cell invasion of HCC827 cells treated with the CM was detected using transwell invasion assays. Scale bar: 100 µm. Results are shown as the mean ± SD based on three independent experiments. *P < 0.05, **P < 0.01, ns, not significant, by Student’s t-test (comparison between shCtrl CM and shCtrl/THP-1 CM groups) or one-way ANOVA followed by Dunnett's multiple comparisons test (comparison between shCtrl CM, shLARRPM-1 CM, and shLARRPM-2 CM groups, and between shCtrl/THP-1 CM, shLARRPM-1/THP-1 CM, and shLARRPM-2/THP-1 CM groups). | true | true | true |
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PMC9552455 | Hongwu Li,Ping Liu,Dapeng Li,Zixi Wang,Zhao Ding,Meng Zhou,Xu Chen,Manli Miao,Junli Ding,Wei Lin,Yehai Liu,Xiaojun Zha | STAT3/miR-130b-3p/MBNL1 feedback loop regulated by mTORC1 signaling promotes angiogenesis and tumor growth | 11-10-2022 | mTOR,miR-130b-3p,STAT3,MBNL1,Angiogenesis,Tumor growth | Background Aberrantly activated mammalian target of rapamycin complex 1 (mTORC1) plays a vital role in tumor angiogenesis, but its precise mechanisms are still unclear. Methods Micro-RNA-130b-3p (miR-130b-3p) expression in mTORC1-activated and control cells was examined by quantitative real-time PCR (qRT-PCR). MiR-130b-3p levels and their correlation with mTORC1 activity were evaluated by analyzing publicly available databases and in-house head and neck squamous cell carcinoma (HNSCC) tissues. The role of miR-130b-3p in mTORC1-mediated angiogenesis and tumor growth was examined using tube formation assay, chicken chorioallantoic membrane assay, cell line − derived xenograft models, and an HNSCC patient-derived xenograft (PDX) model. The regulatory mechanisms among signal transducer and activator of transcription 3 (STAT3), miR-130b-3p, and muscleblind-like protein 1 (MBNL1) were investigated via bioinformatics analyses, qRT-PCR, western blot, RNA immunoprecipitation, immunofluorescence, luciferase reporter assay, and chromatin immunoprecipitation assay. Results Elevated miR-130b-3p enhanced the angiogenic and tumorigenic abilities of mTORC1-activated cells both in vitro and in vivo. STAT3, a downstream effector of mTORC1, transactivated miR-130b-3p by direct binding promoter of the miR-130b gene. MBNL1 was identified as a direct target of miR-130b-3p. MBNL1 depletion rescued the compromised angiogenesis and tumor growth caused by miR-130b-3p inhibition. MiR-130b-3p levels were significantly upregulated and positively correlated with mTORC1 signaling in multiple cancers. MiR-130b-3p inhibition attenuated tumor angiogenesis and growth in an HNSCC PDX model. MBNL1 feedback inhibited STAT3 activation in mTORC1-activated cells. Conclusions The STAT3/miR-130b-3p/MBNL1 feedback loop plays a vital role in mTORC1-mediated angiogenesis and tumor progression. This pathway could be targeted for therapeutic intervention of mTORC1-related cancers. Supplementary Information The online version contains supplementary material available at 10.1186/s13046-022-02513-z. | STAT3/miR-130b-3p/MBNL1 feedback loop regulated by mTORC1 signaling promotes angiogenesis and tumor growth
Aberrantly activated mammalian target of rapamycin complex 1 (mTORC1) plays a vital role in tumor angiogenesis, but its precise mechanisms are still unclear.
Micro-RNA-130b-3p (miR-130b-3p) expression in mTORC1-activated and control cells was examined by quantitative real-time PCR (qRT-PCR). MiR-130b-3p levels and their correlation with mTORC1 activity were evaluated by analyzing publicly available databases and in-house head and neck squamous cell carcinoma (HNSCC) tissues. The role of miR-130b-3p in mTORC1-mediated angiogenesis and tumor growth was examined using tube formation assay, chicken chorioallantoic membrane assay, cell line − derived xenograft models, and an HNSCC patient-derived xenograft (PDX) model. The regulatory mechanisms among signal transducer and activator of transcription 3 (STAT3), miR-130b-3p, and muscleblind-like protein 1 (MBNL1) were investigated via bioinformatics analyses, qRT-PCR, western blot, RNA immunoprecipitation, immunofluorescence, luciferase reporter assay, and chromatin immunoprecipitation assay.
Elevated miR-130b-3p enhanced the angiogenic and tumorigenic abilities of mTORC1-activated cells both in vitro and in vivo. STAT3, a downstream effector of mTORC1, transactivated miR-130b-3p by direct binding promoter of the miR-130b gene. MBNL1 was identified as a direct target of miR-130b-3p. MBNL1 depletion rescued the compromised angiogenesis and tumor growth caused by miR-130b-3p inhibition. MiR-130b-3p levels were significantly upregulated and positively correlated with mTORC1 signaling in multiple cancers. MiR-130b-3p inhibition attenuated tumor angiogenesis and growth in an HNSCC PDX model. MBNL1 feedback inhibited STAT3 activation in mTORC1-activated cells.
The STAT3/miR-130b-3p/MBNL1 feedback loop plays a vital role in mTORC1-mediated angiogenesis and tumor progression. This pathway could be targeted for therapeutic intervention of mTORC1-related cancers.
The online version contains supplementary material available at 10.1186/s13046-022-02513-z.
Angiogenesis is recognized as one of the hallmarks of cancer [1–3]. Tumor-associated angiogenesis has a critical role in the delivery of oxygen and nutrients to expanding tumors, thus significantly influencing various aspects of cancer development, such as tumor cell metastasis and metabolic dysregulation [4, 5]. Because of its fundamental role in tumor progression, angiogenesis has become an attractive target in cancer treatment [6, 7]. However, the mechanisms and pathways that drive tumor angiogenesis are not fully understood. The mammalian target of rapamycin (mTOR), a highly conserved serine/threonine protein kinase, regulates a wide repertoire of biological processes important for cell growth and proliferation, including protein translation, metabolism, autophagy, and ferroptosis [8, 9]. mTOR can form two functional complexes, mTOR complex 1 (mTORC1) and mTOR complex 2 (mTORC2), which are different with regard to specific binding components, upstream and downstream signaling, and rapamycin sensitivity [10]. The heterodimer tuberous sclerosis 1 (TSC1)/tuberous sclerosis 2 (TSC2) is an important upstream negative regulator of mTORC1 [11]. TSC1/TSC2 complex suppresses a small GTPase, Ras homolog enriched in the brain (Rheb), by stimulating the conversion of active Rheb-GTP into inactive Rheb-GDP through the GTPase activating (GAP) activity of TSC2 [12]. The activity of the TSC1/TSC2 complex relies on heterodimer formation and is controlled by several kinases, particularly AKT [13]. Disruption of the TSC1/TSC2 complex by the activated PI3K/AKT pathway, or by inactivating mutations in either TSC1 or TSC2, results in the accumulation of GTP-bound Rheb, which in turn activates mTORC1 [14]. mTORC1 promotes protein synthesis through phosphorylating ribosomal protein S6 kinase 1 and eukaryotic translation initiation factor 4E-binding protein 1, leading to accelerated cell growth and proliferation [8]. mTORC1 signaling is frequently over-activated in human cancers [11], but its precise mechanisms still require further clarification. It has been well-recognized that mTORC1 is a positive regulator of angiogenesis [15, 16]. Hyperactivated mTORC1 upregulates hypoxia-inducible factor -1α at numerous levels, which in turn promotes angiogenesis by enhancing the transcription of pro-angiogenic factors, such as vascular endothelial growth factor (VEGF) and transforming growth factor -α [17]. It has also been demonstrated that the mTORC1 specific inhibitor rapamycin exerts anti-angiogenic properties by reducing the proliferation, migration, and tubular structure formation of endothelial cells [18]. We have previously reported that mTORC1 signaling activation promotes angiogenesis through the upregulation of brain-expressed X-linked 2 [19]. However, whether noncoding RNAs are involved in mTORC1-mediated angiogenesis remains unclear. In this study, we showed that micro-RNA-130b-3p (miR-130b-3p) is involved in hyperactivated mTORC1-mediated angiogenesis and tumor growth. The transcription factor signal transducer and activator of transcription 3 (STAT3), serves as a downstream effector of mTORC1 and transcriptionally upregulates miR-130b-3p expression. Furthermore, miR-130b-3p exerts an angiogenesis-promoting role in mTORC1-activated cells by targeting muscleblind-like protein 1 (MBNL1). In addition, MBNL1 depletion led to an increase in STAT3 activity. We suggest that the STAT3/miR-130b-3p/MBNL1 feedback loop is critical for mTORC1-mediated angiogenesis and tumor growth, and that it can be targeted for the treatment of cancers associated with dysregulated mTORC1 activity.
A total of 60 paired head and neck squamous cell carcinoma (HNSCC) and adjacent normal mucosal (ANM) tissues were acquired at the First Affiliated Hospital of Anhui Medical University (Anhui, China) from 2014 to 2020. All recruited patients had not received chemotherapy, radiotherapy, or other antitumor therapies before surgery. The study was approved by the Research Ethics Committee of the First Affiliated Hospital of Anhui Medical University. All of the patients provided written informed consent before surgery. The patients’ detailed information is presented in Supplementary Table S1.
All the mouse embryonic fibroblast (MEF) cell lines (including Tsc1 + / + , Tsc1 − / − , Tsc2 + / + , Tsc2 − / − , STAT3C-overexpressing Tsc2 + / + and the empty vector pBabe-transduced Tsc2 + / + MEFs) and NTC/T2 null (a cell line with potent tumorigenicity derived from a subcutaneous tumor formed by the injection of Tsc2 − / − MEFs in immunodeficient mice) cells have been described previously [20–22]. The HNSCC cell line FaDu, human umbilical vein endothelial cells (HUVECs), and HEK 293 T cells were obtained from the ATCC (VA, USA). The HNSCC cell line TU686 was obtained from the BeNa Culture Collection (Beijing, China). The HNSCC cell line TU212 and human normal oral keratinocyte (NOK) cells were obtained from Otwo Biotech (Shenzhen, China). HNSCC cell lines and NOK cells were cultured in 1640 medium (BOSTER, Wuhan, China) containing 10% fetal bovine serum (Gibco, CA, USA) (containing 100 U/mL of penicillin and 100 μg/mL of streptomycin); other cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM) (BOSTER) with the same composition at 37 °C in a humidified incubator containing 5% CO2. For drug treatment, cells were seeded into 12-well plates at 30% − 40% density 24 h before treatment. The Dimethyl sulfoxide (DMSO) stocks of the agents used, including rapamycin, MHY-1485, and S3I-201, were diluted to appropriate concentrations with the cell culture medium. All the drugs were purchased from Selleck Chemicals (TX, USA).
All of the lentiviral vectors were obtained from GeneChem (Shanghai, China), including the GV112 lentiviral shRNA expression vector targeting Raptor, Rictor, STAT3, MBNL1, and the control scrambled shRNẠ (shSc); GV209 and GV234 lentiviral expression plasmids that were used to increase and decrease miR-130b-3p, respectively; and GV341 lentiviral plasmid expressing mouse MBNL1 and the empty plasmid. The detailed information on the recombinant plasmids is presented in Supplementary Table S2. Lentiviruses were generated by transfecting with either the recombinant vectors or control vectors together with packaging plasmids (psPAX2 and pVSVG) into HEK 293 T cells. Culture supernatants were collected and filtered after 48 h of transfection and then used to infect target cells at a multiplicity of infection of 10 to 20. Two days after infection, the cells were selected with 2 μg/mL of puromycin for 1 week following the manufacturer’s instructions.
Immunoblotting analysis was performed as described previously [23]. In brief, cell or tissue lysates were resolved by NuPAGE 4–12% Bis–Tris gels (Life Technologies, CA, USA), transferred to PVDF membrane (Millipore, MA, USA), and then incubated with the primary and secondary antibodies. The specific protein bands in the membrane were visualized using Pierce™ ECL Western Blotting Substrate (Thermo Scientific, MA, USA) and ChemiScope 6100 (Clinx, Shanghai, China). All information regarding antibodies used in this study is provided in Supplementary Table S3.
Total RNA from cells and tissues were isolated using TRIzol reagent (Life Technologies) according to the protocol provided by the manufacturer. For analysis of mRNA expression levels, first-strand cDNA synthesis was performed using the RevertAid™ First Stand cDNA Synthesis Kit (Thermo Scientific). Quantitative real-time PCR (qRT-PCR) detection of mRNA expression of MMP13, VEGF-C, BCL2, IL18, and MBNL1 was performed using SYBR Premix Ex Taq™ II (TaKaRa, Dalian, China). The expression of miR-130b-3p was detected using the Hairpin-itTM microRNAs qPCR Quantitation Kit (GenePharma, Shanghai, China) according to the producer’s instructions. qRT-PCR was performed on the LightCycler96 (Roche, Basel, Switzerland). β-actin or U6 served as an internal control. The primers used are listed in Supplementary Table S4.
Cells were seeded into 12-well plates and allowed to reach 70% confluence before transfection. Transient transfection of mouse miR-130b-3p mimics, inhibitors, and the negative control (GenePharma) was conducted with Lipofectamine RNAiMax (Thermo Fisher Scientific) according to the protocol provided by the manufacturer. The sequences are listed as follows: miR-130b-3p mimics, 5'-CAGUGCAAUGAUGAAAGGGCAU-3'; mimics negative control (NC), 5'-UUCUCCGAACGUGUCACGUTT-3'; miR-130b-3p inhibitor, 5'-AUGCCCUUUCAUCAUUGCACUG-3'; and inhibitor negative control, 5'-CAGUACUUUUGUGUAGUACAA-3'.
A 299-bp fragment of the mouse miR-130b promoter region (− 678/ − 976) embodying the wild-type STAT3 binding site was obtained by polymerase chain reaction (PCR) using mouse genomic DNA extracted from Tsc2 − / − MEFs and cloned into a pTAL-Luc vector (Clontech, CA, USA) for constructing miR-130b promoter luciferase reporter. A fragment of 330-bp MBNL1 3´-untranslated region (3´-UTR) containing the putative binding site for miR-130b-3p was generated by PCR and cloned into the p-miRGLO firefly luciferase vector (GenePharma). The potential STAT3 binding site on the promoter of the mouse miR-130b gene and the predicted miR-130b-3p target binding site in 3´-UTR of MBNL1 were mutated using the Q5 site-directed mutagenesis kit (NEB, MA, USA). The primers used to construct the recombinant plasmids are listed in Supplementary Table S5. To investigate the effect of STAT3 activation on the miR-130b-3p promoter activity, HEK 293 T cells were cultured in triplicate to 80% confluence in 24-well plates and the promoter constructs (200 ng) were co-transfected with pBabe-STAT3C or the empty vector pBabe (200 ng) and the internal control plasmid pRL-TK (10 ng). Luciferase activity was detected with the Dual-Luciferase Reporter assay system (Promega, WI, USA) according to the manufacturer’s procedures. To examine the effect of miR-130b-3p on the MBNL1 3´-UTR, HEK 293 T cells were transfected with 50 nM of miR-130b-3p mimics or NC-mimics, together with 100 ng of luciferase reporter plasmids (MBNL1-WT or MBNL1-Mut) using Lipofectamine 3000 (Invitrogen, CA, USA). Forty-eight hours after transfection, luciferase activities were measured as mentioned above.
MBNL1-overexpressing and control cells were seeded on fibronectin-coated glass coverslips in 24-well culture plates. After 24 h, the cells were fixed with 4% formaldehyde, treated with 1% Triton X-100 (Sigma-Aldrich, MO, USA) for permeabilization, and then blocked with 2% bovine serum albumin. The coverslips were incubated in a primary antibody overnight and followed with a CY3-conjugated secondary antibody (Cell Signaling Technology, MA, USA) for 1 h. An LSM880 + Airyscan confocal laser scanning microscope (Carl Zeiss, Oberkochen, Germany) was used to capture images.
Chromatin immunoprecipitation (ChIP) assay was performed using a SimpleChIP® Plus Enzymatic Chromatin IP kit (Cell Signaling Technology) as described previously [22]. In brief, cells were cross-linked by 1% formaldehyde for 10 min, cracked with the sodium dodecyl sulfate lysis buffer, followed by ultrasonication for 50 min, and then incubated with an anti-phosphor-STAT3 Tyr705 (p-STAT3) antibody or an anti-H3K4me3 antibody (#ab213224, Abcam, Cambridge, UK) overnight. The immunoprecipitated DNA was purified and analyzed using PCR or qRT-PCR with specific primers. The primer sequences are listed in Supplementary Table S6.
Cell-derived conditioned medium (CM) was prepared as described previously [23]. Briefly, stably transfected cells were seeded in a 10-cm dish and incubated for 48 h, after which the medium was removed and replaced by a fresh serum-deprived medium. After 24 h of incubation, the CM was collected, filtered, and then concentrated by ultrafiltration using Amicon Ultra 10 K centrifugal filters (Millipore). The CM was stored at − 80 °C until use. For the tube formation assay, a total of 150 µL of Matrigel (Corning, NY, USA) was added to a 48-well plate and incubated at 37 °C for 30 min. Then, HUVECs (3.5 × 104) in 300 µL of prepared CM were added to each well and incubated at 37 °C in 5% CO2. After incubation for 12 h, bright-field images were recorded using a microscope and analyzed using WimTube (https://www.wimasis.com/en/WimTube, Wimasis GmbH, Munich, Germany).
Pathogen-free fertilized chicken eggs were purchased from Jinan SAIS Poultry Company (Shandong, China) and handled as described previously [23]. Briefly, on embryonic developmental days 8, sterile gelatin sponges mixed with 20 μL of cell suspension containing 5 × 106 cells were deposited on chicken chorioallantoic Membrane (CAM). On embryonic developmental days 14–17, the CAM was separated, fixated, and photographed. The number of blood vessels that converged toward the implant was counted by two blind observers.
The levels of secreted VEGF-C in cell-free supernatant of MBNL1-overexpressing cells and the control cells were quantified using a mouse VEGF-C ELISA Kit (Novus Biologicals, CO, USA) according to the manufacturer’s instructions.
The RNA immunoprecipitation assay experiments were performed with a BersinBio™ RIP Kit (BersinBio, Guangdong, China) according to the manufacturer’s instructions. Briefly, cells were collected and lysed with RIP lysis buffer and then incubated with magnetic protein A beads coupled with anti-Argonaute protein 2 (AGO2) antibody (#186,733, Abcam) for 6 h at 4 °C. Thereafter, the RNA was purified, and the levels of miR-130b-3p and MBNL1 were analyzed using qRT-PCR. IgG served as a negative control. The primers used are listed in Supplementary Table S4.
BALB/c-Nude mice and NOD/SCID mice were purchased from GemPharmatech (Nanjing, China). All animals were maintained in strict accordance with the guidelines of the Animal Center of Anhui Medical University, and all animal experimental procedures were approved by the Experimental Animal Ethical Committee of Anhui Medical University. For in vivo xenograft assay, Nude mice were randomly assigned into groups (five mice per group) to receive respective treatments. In the right anterior armpit of the mice, 4 × 106 genetically engineered cells in 0.2 mL of DMEM were inoculated subcutaneously. Tumor growth was detected every 3 days, and tumor volume was calculated using the following equation: Volume = (length × width2)/2(mm3). To establish the patient-derived xenograft (PDX) models, tumor tissues from an HNSCC patient were processed after tumor resection. The tumor samples were cleaned, then cut into small pieces with diameters of approximately 3–5 mm, and subcutaneously implanted into the flanks of NOD/SCID mice. The successfully established PDX model was referred to as passage 1 (P1). When the tumor volume reached approximately 1,000 mm3, mice were sacrificed, and the tumors were passaged and expanded for two more generations (named P2 and P3) using the same previously described procedure as with Nude mice. The P3 xenografts were treated intratumorally with either antagomiR-130b-3p (a 2´-OMe + 5´-chol–modified miR-130b-3p inhibitor) or the scramble control antagomiR-NC (GenePharma) at a concentration of 10 nmol/50 μL once every three days when tumors reached a volume of 70–100 mm3. On day 28 after treatment, animals were sacrificed, and tumors were collected for further analysis.
Paraffin-embedded tumor tissues were cut into 4-μm slices. The histological sections were stained with antibodies against p-S6, CD31, p-STAT3, and MBNL1, according to the manufacturer’s protocols. For the determination of p-S6 immunoreactivity in HNSCC samples, immunohistochemistry analysis (IHC) staining was scored on the basis of the intensity of staining and the proportion of positive cells. The blinded review was performed by two pathologists.
RNA sequencing data from HNSCC (n = 569), breast invasive carcinoma (BRCA; n = 1,207), esophageal carcinoma (ESCA; n = 200), liver hepatocellular carcinoma (LIHC; n = 425), lung adenocarcinoma (LUAD; n = 567), and skin cutaneous melanoma (SKCM; n = 452) patients were obtained from The Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov/). Gene set enrichment analysis (GSEA) was performed to examine the enrichment of mTORC1 positively regulated gene sets in miR-130b-3p-high and miR-130b-3p-low HNSCC, BRCA, ESCA, LIHC, LUAD, and SKCM cancer tissues, according to methods described previously [22].
Data were analyzed using Student’s t-test (two-tailed) or one-way analysis of variance (ANOVA) as appropriate, with GraphPad Prism 6.0 software. The association of miR-130b-3p and p-S6 was analyzed using Pearson’s correlation analysis. P < 0.05 is considered statistically significant.
Because the TSC1/TSC2 complex is the principal suppressor of mTORC1 signaling and hyperactivated mTORC1 is the main reason for tumor formation in TSC disease [24], Tsc1 − / − or Tsc2 − / − MEFs and TSC samples are excellent models for the study of mTORC1 signaling. In our previous study, 51 differentially expressed miRNAs (13 upregulated and 38 downregulated) in Tsc2 − / − MEFs as compared with Tsc2 + / + MEFs (fold change > 2) were identified [25]. To examine effectively functional miRNAs downstream of mTORC1, a Venn analysis was performed using the aforementioned 51 miRNAs and miRNAs that are abnormally expressed in the serum of patients with TSC [26]. Two miRNAs were screened, including miR-130b-3p and miR-199a-5p (Fig. 1A). The qRT-PCR analysis confirmed that miR-130b-3p levels were significantly increased and the miR-199a-5p level was downregulated in Tsc1- or Tsc2-null MEFs as compared with their corresponding control cells, and their levels were reversed by mTORC1 inhibition with rapamycin treatment (Fig. 1B). MiR-130b-3p was chosen for further study because the degree of its expression change is larger than that of miR-199a-5p. To further confirm that it is indeed mTORC1 that mediates the positive regulation of miR-130b-3p downstream of the TSC1/TSC2 complex, miR-130b-3p levels in Raptor (a specific component of mTORC1) or Rictor (a specific component of mTORC2)-knockdown Tsc2 − / − MEFs were examined. As indicated in the left panels of Fig. 1C, cells infected with Raptor shRNAs exhibited decreased miR-130b-3p levels, whereas Rictor shRNAs had little effect on miR-130b-3p expression. A consistent result was obtained in Tsc1 − / − MEFs after either Raptor or Rictor depletion (Fig. 1C, right panels). In addition, mTORC1 activation by treatment of MHY-1485 led to the upregulation of miR-130b-3p in Tsc2 + / + or Tsc1 + / + MEFs (Fig. 1D). Together, these data suggest that hyperactivated mTORC1 upregulates miR-130b-3p expression.
Because miR-130b-3p has been linked to tumor angiogenesis in various types of cancer, and mTORC1 is a critical activator of angiogenesis [15, 16, 27, 28], we were greatly interested in investigating whether miR-130b-3p plays a vital role in mTORC1-mediated angiogenesis and tumor progression. First, Tsc2 − / − and Tsc1 − / − MEFs were stably transfected with antisense of miR-130b-3p (anti-miR-130b) (Fig. 2A and Supplementary Fig. S1A). Subsequently, in vitro capillary tube formation assay was performed. It was observed that HUVECs cultured with the CM derived from the miR-130b-3p suppressed cell lines developed less capillary-like structures and branch points, implying the pro-angiogenesis function of miR-130b-3p (Fig. 2B and Supplementary Fig. S1B). Moreover, the CAM assay also revealed that miR-130b-3p suppression strongly attenuated the formation of new microvessels (Fig. 2C). Conversely, miR-130b-3p overexpression enhanced the angiogenic capacity of Tsc2 + / + MEFs (Fig. 2D − F). Consistently, the angiogenesis-related genes, including MMP13, VEGF-C, BCL2, and IL18, were found to be upregulated in miR-130b-3p-overexpressing Tsc2 + / + MEFs (Fig. 2G). In summary, these findings suggest that miR-130b-3p could enhance the pro-angiogenic capacity of mTORC1-activated cells. To further investigate the in vivo role of miR-130b-3p, NTC/T2 null cells transfected with a lentiviral vector encoding anti-miR-130b-3p or a scrambled sequence were subcutaneously injected into the right anterior armpit of Nude mice (Supplementary Fig. S1C − D), and then tumor growth was monitored. As depicted in Fig. 2H − J, the anti-miR-130b-3p group, compared with the control group, showed a significant reduction in tumor volume and weight. Furthermore, IHC analysis demonstrated that tumor tissues derived from anti-miR-130b-3p-expressing cells exhibited much weaker staining for the angiogenic marker CD31 than those in the control counterpart (Fig. 2K). Decreased miR-130b-3p expression in the tumor samples derived from animals bearing anti-miR-130b-3p-expressing cell xenografts was confirmed by qRT-PCR (Fig. 2L). Therefore, miR-130b-3p positively regulates angiogenesis and tumor growth driven by mTORC1 activation.
Because the transcription factor STAT3 is one of the most vital downstream effectors of mTORC1 and is a vital driver of angiogenesis [20, 29], we investigated whether STAT3 participates in the regulation of miR-130b-3p expression downstream of mTORC1. We first evaluated the effect of S3I-201, a specific STAT3 inhibitor, on miR-130b-3p expression. As indicated in Fig. 3A, S3I-201 treatment led to a marked reduction of miR-130b-3p in Tsc2 − / − and Tsc1 − / − MEFs. Similarly, knockdown of STAT3 with lentivirus mediated STAT3 shRNA led to significantly decreased miR-130b-3p expression in both Tsc2 − / − and Tsc1 − / − MEFs (Fig. 3B). In contrast, overexpression of a constitutively activated STAT3 (STAT3C) resulted in dramatically upregulated miR-130b-3p expression in Tsc2 + / + MEFs (Fig. 3C). Therefore, mTORC1 upregulates miR-130b-3p through STAT3 activation. Next, we further analyzed whether STAT3 binds to the miR-130b promoter region to activate its expression. H3K4me3 is a highly conserved histone modification and a hallmark of active genes distributed along with promoter regions [30, 31]. By retrieving the UCSC Genome Browser (http://genoime.ucsc.edu/), a genomic region located from approximately − 3074 to − 475 bp ahead of miR-130b stem-loop was determined to have enrichment of the H3K4me3 histone modification (Fig. 3D). Further analysis via the JASPAR database (http://jaspar.genereg.net/) predicted two conserved STAT3-binding sites in this H3K4me3-enriched region (Fig. 3E). ChIP assay indicated that STAT3 was only enriched in site #1 (Fig. 3F), suggesting that this site may have critical importance for the transcription of miR-130b. Furthermore, miR-130b promoter luciferase reporters containing a region around site #1 were constructed (Fig. 3G). STAT3C overexpression significantly increased the luciferase activity of the reporter, whereas the enhanced transcriptional activity was attenuated when the putative STAT3 binding site was mutated (Fig. 3G and H). Moreover, the ChIP assay displayed that the recruitment of the STAT3 protein to site #1 was significantly enhanced in Tsc2 − / − MEFs in comparison with Tsc2 + / + MEFs, and the enrichment was attenuated with the addition of rapamycin (Fig. 3I). On the basis of these results, we conclude that STAT3 transcriptionally elevates miR-130b-3p through direct binding with its promoter.
The putative target genes of miR-130b-3p were predicted by the following bioinformatics tools: TargetScan, picTar, RNA22, miRDB, and miRWalk. The intersections were retrieved by starBase V2.0, and 49 genes were found to be potential targets (Fig. 4A and Supplementary Table S7). To further screen target genes, the Venn analysis of these predicted target genes with downregulated differentially expressed genes in Tsc2 − / − MEFs as compared with Tsc2 + / + MEFs and decreased differentially expressed genes in angiofibroma (AF) of TSC patients vs. normal skin obtained only one candidate, MBNL1 [32, 33] (Fig. 4B, Supplementary Tables S8 and S9). qRT-PCR and western blot analyses confirmed that loss of TSC1 or TSC2 led a significantly downregulated MBNL1 expression, whereas MBNL1 expression was upregulated in response to mTORC1 inhibition (Fig. 4C and D). Furthermore, transfection of miR-130b-3p inhibitor led to upregulated MBNL1 expression in Tsc2 − / − or Tsc1 − / − MEFs (Fig. 4E). In contrast, transfection of miR-130b-3p mimics had the opposite effect in Tsc2 + / + or Tsc1 + / + MEFs (Fig. 4F). Therefore, mTORC1 downregulates MBNL1 through the upregulation of miR-130b-3p. To further assess whether MBNL1 is a direct target of miR-130b-3p, a luciferase activity assay was performed. A fragment of the wild-type 3´-UTR (MBNL1-WT) and a fragment of the mutant 3´-UTR (MBNL1-Mut) were cloned into the p-miRGLO firefly luciferase vector (Fig. 4G). HEK 293 T cells were co-transfected with MBNL1-WT or MBNL1-Mut, miR-130b-3p mimics, or NC-mimics. As indicated in Fig. 4H, the relative luciferase activity of the reporter containing the WT 3´-UTR was significantly decreased when co-transfected with miR-130b-3p mimics. Conversely, the luciferase activity of the mutant 3´-UTR was similar between the miR-130b-3p mimics and NC-mimics. Because miRNAs exert their roles mainly through binding with AGO2 to form an RNA-induced silencing complex [34], anti-AGO2 RIP assays were performed to further confirm our findings. RIP demonstrated that AGO2, compared with IgG, was able to enrich both miR-130b-3p and MBNL1 as compared with IgG (Fig. 4I). Moreover, it was observed that there was a dramatic increase in the levels of MBNL1 3´-UTR in anti-AGO2 RIP compared with anti-IgG RIP in response to miR-130b-3p overexpression (Fig. 4J). Collectively, the aforementioned data suggested that MBNL1 is a direct downstream target of miR-130b-3p.
To examine the potential significance of MBNL1 in angiogenesis, we ectopically expressed MBNL1 with lentivirus in Tsc2 − / − and Tsc1 − / − MEFs (Fig. 5A and Supplementary Fig. S2A). Enzyme-linked immunosorbent assay (ELISA) revealed that the VEGF-C levels were significantly lower in the MBNL1-overexpressing groups (Fig. 5B and Supplementary Fig. S2B). In vitro tube formation assays demonstrated that the HUVECs treated with CM derived from the MBNL1 transfectants developed less capillary-like structures than did cells treated with CM derived from empty vector transfectants (Fig. 5C and Supplementary Fig. S2C). Moreover, the CAM assay also revealed that MBNL1 overexpression dramatically suppressed the formation of new microvessels (Fig. 5D and Supplementary Fig. S2D). The in vivo function of MBNL1 was further evaluated using a subcutaneous xenograft tumor model. As indicated in Supplementary Fig. S2E − I, MBNL1 overexpression attenuated tumor angiogenesis (as assessed by CD31 index) and xenograft growth. Together, these data revealed that MBNL1 exerts an anti-angiogenic activity. To investigate whether the pro-angiogenic effect of miR-130b-3p is dependent on MBNL1, a lentiviral vector expressing shRNAs for MBNL1 was transduced to anti-miR-130b-3p-expressing Tsc2 − / − MEFs or NTC/T2 null cells. The knockdown efficiencies in the transformed cell lines were detected by western blot (Fig. 5E and Supplementary Fig. S3A). MBNL1 knockdown partially rescued the inhibitory effect of miR-130b-3p suppression on angiogenesis (Fig. 5F, G and Supplementary Fig. S3B). In contrast, ectopically expressed MBNL1 in miR-130b-3p-overexpressing Tsc2 + / + MEFs partially attenuated the pro-angiogenic effect of miR-130b-3p (Supplementary Fig. S3C and D). The mediation effect of MBNL1 on the miR-130b-3p-regulated angiogenesis and tumor growth was further confirmed using a subcutaneous xenograft tumor model. Consistent with the forementioned results, MBNL1 depletion rescued the suppressive effects of miR-130b-3p inhibition on xenograft growth and tumor angiogenesis (Fig. 5H − K). Taken together, these data revealed that miR-130b-3p promotes angiogenesis and tumor growth at least partially through suppression of MBNL1 expression.
TCGA database was used to evaluate the clinical relevance of this newly discovered mTORC1 regulation of miR-130b-3p in human cancers. As indicated in Fig. 6A, the analysis of TCGA dataset showed that miR-130b-3p was remarkably upregulated in HNSCC tissues compared with ANM tissues. GSEA further demonstrated that the genes positively regulated by mTORC1 signaling were enriched in miR-130b-3p-high expression groups in HNSCC (Fig. 6B). Similarly, miR-130b-3p was also significantly upregulated and positively correlated with mTORC1 signaling in multiple human cancers, such as SKCM, LIHC, LUAD, BRCA, and ESCA (Supplementary Fig. S4A and B). Furthermore, through analysis of 60 paired human HNSCC lesions and the corresponding ANM tissues, it was confirmed that both miR-130b-3p and p-S6 were upregulated in tumor tissues, and the expression level of miR-130b-3p was positively correlated with mTORC1 activity (Fig. 6C − E). Therefore, miR-130b-3p expression positively correlated with mTORC1 activity in human cancer tissues, and it may play a critical role in mTORC1-mediated tumorigenesis. Next, miR-130b-3p and p-S6 levels were detected in various HNSCC cell lines. As compared with NOK cells, HNSCC cells (FaDu and TU686) exhibited high levels of mTORC1 activity and miR-130b-3p (Fig. 6F). FaDu cells were chosen for further study. As indicated in Fig. 6G and H, mTORC1 inhibition by either pharmacological or genetic strategies led to the downregulation of p-STAT3 and miR-130b-3p. As expected, MBNL1 was substantially upregulated in response to mTORC1 suppression. Consistent with Tsc1- or Tsc2-null MEFs, miR-130b-3p inhibition through expressing sponge sequences targeting miR-130b-3p upregulated the MBNL1 expression and suppressed angiogenesis as evaluated by tube formation and CAM assays (Fig. 6I − K). Inhibition of the mTORC1/miR-130b-3p axis in TU686 cells, similar to FaDu cells, upregulated MBNL1 and impaired angiogenesis (Supplementary Fig. S5A − D). The pro-oncogenic role of human miR-130b-3p was further evaluated using a xenograft tumor model. As depicted in Fig. 6L − N, miR-130b-3p suppression markedly retarded tumor progression. IHC analysis of CD31 in the xenograft tumors confirmed that miR-130b-3p is a positive regulator of angiogenesis in vivo (Fig. 6O). Taken together, these data revealed that the mTORC1/STAT3/miR-130b-3p/MBNL1 signaling cascade is also present in human cancer cells.
PDX tumor models can highly preserve the histological characteristics and heterogeneity of the original tumors [35, 36]. Therefore, to further validate the role of miR-130b-3p in the tumorigenesis of human cancers, a PDX model of HNSCC was constructed. As indicated in Fig. 7A − D, one fresh HNSCC tumor with activated mTORC1 and a high level of miR-130b-3p was chosen to establish the PDX model. The PDX model mice were intratumorally injected with antagomiR-130b-3p or antagomiR-NC once every 3 days. As indicated in Fig. 7E − G, antagomiR-130b-3p significantly delayed the growth of PDX tumors. The qRT-PCR analysis confirmed that miR-130b-3p was substantially decreased in the antagomiR-130b-3p-treated groups than in the antagomiR-NC-treated groups (Fig. 7H). Furthermore, the IHC staining of xenograft tissues indicated a marked increase in MBNL1 expression and a reduction in CD31 and p-STAT3 in the antagomiR-130b-3p-treated group as compared with the control group (Fig. 7I). Taken together, these results confirmed that miR-130b-3p inhibition could effectively inhibit the growth of HNSCC PDX models.
Next, we investigated whether decreased MBNL1 contributes to the enhancement of STAT3 activity caused by hyperactivation of mTORC1 signaling was investigated. As indicted in Fig. 8A, MBNL1 overexpression markedly attenuated STAT3 activity in Tsc2 − / − or Tsc1 − / − MEFs. Immunofluorescence analysis also confirmed that the nuclear level of STAT3 was dramatically reduced in response to MBNL1 overexpression (Fig. 8B). In contrast, knockdown of MBNL1 led to STAT3 activation in both Tsc2 + / + and Tsc1 + / + MEFs (Fig. 8C). Decreased p-STAT3 expression was observed in tumor tissues derived from MBNL1-overexpressing NTC/T2 null cells compared with the control cells (Fig. 8D). Moreover, decreased p-STAT3 expression in tumor tissues derived from anti-miR-130b-3p-expressing NTC/T2 null was partially rescued by knockdown of MBNL1 (Fig. 8E). Taken together, these data revealed that MBNL1 is a negative regulator of STAT3 and that miR-130b-3p-mediated downregulation of MBNL1 is, at least partially, responsible for the STAT3 activation in mTORC1-activated cells.
Hyperactivated mTORC1 promotes tumor angiogenesis, but its underlying mechanisms remain partially understood. In this study, mainly on the basis of Tsc2- or Tsc1-null MEFs, HNSCC cell lines, and HNSCC tissues, we identified miR-130b-3p as a novel downstream target of mTORC1. The positive correlation between mTORC1 and miR-130b-3p was also observed in multiple human cancer tissues. In addition, we illustrated that elevated miR-130b-3p contributed to angiogenesis and that tumor growth is driven by mTORC1. The vital role of miR-130b-3p in tumor angiogenesis has been illustrated recently in some human cancers. For example, Liao reported that miR-130b-3p was significantly upregulated and promoted angiogenesis in hepatocellular carcinoma [37]. Yan et al. demonstrated that exosomal miR-130b-3p derived from oral squamous cell carcinoma cells enhanced angiogenesis and tumor growth [38]. Our findings not only showed consistent results with these previous studies that miR-130b-3p is critical for angiogenesis but also revealed a new molecular link between mTORC1 activation and tumor angiogenesis. Because mTORC1 is frequently activated in hepatocellular carcinoma and oral squamous cell carcinoma owing to mutations in the RTK/PI3K/AKT pathway [39, 40], it may be that deregulated mTORC1 signaling in these cancers promotes miR-130b-3p expression and subsequent acceleration of angiogenesis and tumor progression. Therefore, miR-130b-3p is a potential therapeutic target for some mTORC1-related cancers. In addition to angiogenesis, miR-130b-3p has been demonstrated to take part in various cellular processes involved in cancer progression, including cell proliferation, cell migration, apoptosis, and drug resistance [27, 41, 42]. Therefore, it is critical to examine how miR-130b-3p expression is controlled. Various transcription factors have been demonstrated to regulate the miR-130b gene expression. For example, Cannistraci and colleagues reported that c-Met activation increases miR-130b levels, which then promote prostate cancer metastasis and resistance to hormone ablation therapy [43]. Tong et al. demonstrated that metadherin, acting as a coactivator of NF-κB, promotes epithelial-mesenchymal transition (EMT) -like change and invasion of glioma cells through the upregulation of miR-130b transcription [44]. In addition, other transcription factors, such as TAp63, NF-YC, FOXM1, and p53, have also been reported to be involved in the transcriptional regulation of miR-130b in virous types of cells [45–48]. Here, we illustrated that STAT3, a well-known downstream effector of mTORC1, upregulates miR-130b-3p at the transcriptional level by directly binding the promoter of the miR-130b gene. We not only determined a novel transcription factor of miR-130b but also revealed that the upregulation of miR-130b-3p represents a new mechanism of angiogenesis driven by the over-activated mTORC1/STAT3 signaling pathway. In addition to transcriptional regulation, emerging evidence recently indicated that some lncRNAs and circular RNAs, such as H19 lncRNA and circSLC8A1, are also involved in the post-transcriptional regulation of miR-130b-3p [49, 50]. In the future, it will be interesting to investigate whether these noncoding RNAs are also involved in mTORC1-mediated regulation of miR-130b-3p. MiRNAs are evolutionarily conserved small noncoding RNAs and are involved in tumorigenesis by targeting mRNAs for cleavage or translational repression [51, 52]. MiR-130b-3p has been determined to target multiple tumor suppressors, such as PTEN, HOXA5, and SASH1, in various types of cancer, resulting in cancer progression and treatment resistance [37, 38, 53]. In the current study, through the integration of bioinformatics and experimental strategies, we found that MBNL1 is an unreported target of miR-130b-3p. Furthermore, we confirmed that elevated miR-130b-3p driven by aberrantly activated mTORC1 signaling promotes angiogenesis and tumor growth through downregulation of MBNL1. The splicing regulator MBNL1 is a ubiquitously expressed RNA-binding protein [54]. MBNL1 was found to be downregulated in various common cancers, such as breast, lung, and stomach adenocarcinomas, and downregulation of MBNL1 predicted poor overall survival in patients with these cancers [55]. Although the specific role of MBNL1 in tumor angiogenesis has not been elucidated yet, several MBNL1-regulated genes are involved in angiogenesis [56]. Our findings not only confirmed that MBNL1 is a novel anti-angiogenic factor but also explained the regulatory molecular mechanism of MBNL1 expression. We propose that elevated miR-130b-3p resulting from hyperactivated mTORC1 signaling inhibits MBNL1 expression and then facilitates tumor angiogenesis and progression in some mTORC1-related cancers. STAT3 is constitutively activated in various of cancer types and plays a vital role in tumor angiogenesis and expansion [57]. It is widely perceived that STAT3 acts as a key regulator of angiogenesis downstream of mTORC1 signaling [20, 58]. For example, Yang and colleagues demonstrated that blocking the mTORC1/STAT3 signaling pathway suppresses tumor angiogenesis [29]. Our previous study revealed that STAT3-mediated upregulation of brain expressed X-linked 2 is critical for angiogenesis induced by hyperactivated mTORC1 [19]. In addition, we have proposed that mTORC1 promotes glucose metabolism and suppresses cell differentiation via STAT3 activation [20, 21, 59]. However, the underlying mechanisms by which mTORC1 activates STAT3 are less elucidated. In the current study, we found that activated mTORC1 decreased MBNL1 expression through STAT3/miR-130b-3p pathway activation. Interestingly, ectopic expression of MBNL1 attenuates the phosphorylation and activation of STAT3 in Tsc1- or Tsc2-deficient cells, whereas MBNL1 depletion facilitates STAT3 activation. Thus, our study illustrated a feedback loop between STAT3 and MBNL1 downstream of mTORC1 signaling and provided the first evidence that mTORC1 activates STAT3, at least in part, by MBNL1 inhibition. Together with our previous findings that mTORC1 upregulates STAT3 protein levels through miR-125b-5p suppression and mTORC1 activates STAT3 under the promotion of EGFR expression [25, 32], our results open a possibility that multiple molecular mechanisms are involved in mTORC1-dependent regulation of STAT3. However, it remains to be verified how MBNL1 regulates the activity of STAT3. A previous study has demonstrated that knockdown of MBNL1 led to c-Jun N-terminal kinase (JNK) activation [55]. Because JNK is a well-known positive regulator of STAT3 [60, 61], decreased MBNL1 may contribute to the enhancement of STAT3 activity via JNK activation in mTORC1-activated cells. Future work, however, is required to examine this possibility.
We demonstrate that aberrantly activated mTORC1 contributes to angiogenesis and tumor growth by regulating of the STAT3/miR-130b-3p/MBNL1 feedback loop (Fig. 8F). Our findings help in the elucidation of the molecular mechanism by which dysregulated mTORC1 signaling drives tumor angiogenesis, indicating that the components in the STAT3/miR-130b-3p/MBNL1 loop signaling pathway may be targeted for the treatment of mTORC1-related tumors.
Additional file 1: Fig. S1. Inhibition of miR-130b-3p suppresses angiogenesis. Fig. S2. Overexpression of MBNL1 inhibits angiogenesis. Fig. S3. miR-130b-3p promotes angiogenesis through downregulation of MBNL1. Fig. S4. miR-130b-3p was upregulated and positively correlated with mTORC1 signaling in multiple human cancers. Fig. S5. Inhibition of mTORC1/miR-130b-3p axis impairs angiogenesis.Additional file 2: Supplementary Table 1. Clinical features of 60 HNSCC patients. Supplementary Table 2. Oligonucleotide sequences used in this study. Supplementary Table 3. Antibodies used in this study. Supplementary Table 4. Primer sequences used for qRT-PCR in this study. Supplementary Table 5. Primers used for luciferase reporter in this study. Supplementary Table 6. Primers used for ChIP Assays in this study.Additional file 3: Supplementary Table S7. List of the predict target genes of miR-130b-3p from prediction softwares TargetScan, RNA22, PicTar, miRDB and miRWalk.Additional file 4: Supplementary Table S8. List of the downregulated differentially expressed genes from RNA sequencing results in Tsc2-/- MEFs and Tsc2+/+ MEFs. All genes were identified with FDR-adjusted p-value<0.05 and absolute value of log2(FC)>1.Additional file 5: Supplementary Table 9. List of the downregulated differentially expressed genes from DEGs in angiofibroma(AF) of TSC patients vs. normal skin. All genes were identified with FDR-adjusted p-value < 0.05 and absolute value of log2(FC) > 1. | true | true | true |
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PMC9552503 | Lihua Ren,Xin Fang,Sachin Mulmi Shrestha,Qinghua Ji,Hui Ye,Yan Liang,Yang Liu,Yadong Feng,Jingwu Dong,Ruihua Shi | LncRNA SNHG16 promotes development of oesophageal squamous cell carcinoma by interacting with EIF4A3 and modulating RhoU mRNA stability | 11-10-2022 | SNHG16,Oesophageal squamous cell carcinoma,mRNA stability,EIF4A3,RhoU | Background Numerous studies have revealed that long noncoding RNAs (lncRNAs) are closely related to the development of many diseases and carcinogenesis. However, their specific biological function and molecular mechanism in oesophageal squamous cell carcinoma (ESCC) remains unclear. Methods RNA-Seq was performed to determine the differential expressions of lncRNAs in ESCC, and the level of SNHG16 expression was detected in ESCC and intraepithelial neoplasia (IEN) samples. In vitro and in vivo experiments were performed to explore the role of SNHG16 and the interaction of EIF4A3 and Ras homologue family member U (RhoU) signalling. Results One hundred and seventy-five upregulated and 134 downregulated lncRNAs were identified by RNA-Seq. SNHG16 was highly expressed in ESCC and intraepithelial neoplasia (IEN) samples, and its expression level was correlated with tumour differentiation and T stage. Overexpression of SNHG16 can facilitate ESCC cell proliferation and metastasis. Mechanistically, we noticed that SNHG16 could bind RNA binding protein (RBP)-eukaryotic translation initiation factor (EIF4A3) and interact with it to form a complex. Importantly, the coalition of SNHG16 and EIF4A3 ultimately regulated Ras homologue family member U (RhoU). SNHG16 modulated RhoU expression by recruiting EIF4A3 to regulate the stability of RhoU mRNA. Knockdown of RhoU further alleviated the effect of the SNHG16 oncogene in ESCC cells. Conclusions The newly identified SNHG16–EIF4A3–RhoU signalling pathway directly coordinates the response in ESCC pathogenesis and suggests that SNHG16 is a promising target for potential ESCC treatment. Supplementary Information The online version contains supplementary material available at 10.1186/s11658-022-00386-w. | LncRNA SNHG16 promotes development of oesophageal squamous cell carcinoma by interacting with EIF4A3 and modulating RhoU mRNA stability
Numerous studies have revealed that long noncoding RNAs (lncRNAs) are closely related to the development of many diseases and carcinogenesis. However, their specific biological function and molecular mechanism in oesophageal squamous cell carcinoma (ESCC) remains unclear.
RNA-Seq was performed to determine the differential expressions of lncRNAs in ESCC, and the level of SNHG16 expression was detected in ESCC and intraepithelial neoplasia (IEN) samples. In vitro and in vivo experiments were performed to explore the role of SNHG16 and the interaction of EIF4A3 and Ras homologue family member U (RhoU) signalling.
One hundred and seventy-five upregulated and 134 downregulated lncRNAs were identified by RNA-Seq. SNHG16 was highly expressed in ESCC and intraepithelial neoplasia (IEN) samples, and its expression level was correlated with tumour differentiation and T stage. Overexpression of SNHG16 can facilitate ESCC cell proliferation and metastasis. Mechanistically, we noticed that SNHG16 could bind RNA binding protein (RBP)-eukaryotic translation initiation factor (EIF4A3) and interact with it to form a complex. Importantly, the coalition of SNHG16 and EIF4A3 ultimately regulated Ras homologue family member U (RhoU). SNHG16 modulated RhoU expression by recruiting EIF4A3 to regulate the stability of RhoU mRNA. Knockdown of RhoU further alleviated the effect of the SNHG16 oncogene in ESCC cells.
The newly identified SNHG16–EIF4A3–RhoU signalling pathway directly coordinates the response in ESCC pathogenesis and suggests that SNHG16 is a promising target for potential ESCC treatment.
The online version contains supplementary material available at 10.1186/s11658-022-00386-w.
Oesophageal cancer (EC) is the third highest incidence cancer and the fourth highest cause of cancer-related mortality according to Cancer Statistics in China [1–3]. Approximately 90% of EC in China are oesophageal squamous cell carcinoma (ESCC) [2, 4], which shows aetiological and pathological characteristics distinct from oesophageal adenocarcinoma (EA) [5, 6]. Although the development of multimodality therapy has improved ESCC patient prognosis [7], the 5-year overall survival (OS) rate still remains unsatisfactory [8]. It is believed that late diagnosis and tumour metastasis propensity are associated with poor outcomes [3]. Genetic susceptibility, environmental factors and gene–environment interactions contribute to the development and progression of ESCC [9, 10]. An in-depth study of the molecular mechanisms of ESCC carcinogenesis and screening specific biomarkers are of particular significance for ESCC therapy and early diagnosis. Long noncoding RNAs (lncRNAs), a recognized class of noncoding RNAs (ncRNAs) with lengths longer than 200 nucleotides (nt), have limited or no protein-coding capacity [11]. Although previous researchers regarded many lncRNAs as transcriptional noise, a growing number have been shown to have authentic biological functions such as chromatin modification, transcription, post-transcriptional regulation and nuclear transport [12–14]. As lncRNAs are more tissue specific or cell-type specific than protein-coding genes, they have distinct biological roles in physiological and pathological settings, especially in cancers [15]. Studies on and understanding of lncRNAs in ESCC carcinogenesis have gradually increased in recent years [16, 17]. Previous studies have discovered the expression profile of aberrant lncRNAs in ESCC, and identified varieties of ESCC-associated lncRNAs, some of which could be used as biomarkers for cancer diagnosis or prognosis [17–20]. Nevertheless, compared with the number of other cancer-associated lncRNAs, only very few ESCC-associated lncRNAs have been studied, and their functions and mechanisms have yet to be fully elucidated [20, 21]. Therefore, the vast majority of ESCC-associated lncRNAs need to be further investigated in detail. In this study, we performed a next-generation RNA sequencing assay from four pairs of ESCC and normal oesophagus tissues to identify novel ESCC-associated lncRNAs. We then focused on a small nucleolar RNA host gene 16 (SNHG16) and detected its expression in a cohort of precancerous, cancerous and normal oesophageal tissues. In vitro and in vivo experiments were used to investigate the biological function of SNHG16. Finally, a mechanistic investigation was performed to determine how SNHG16 regulates ESCC cells, and explored its underlying targets.
Oesophageal intraepithelial neoplasia (IEN) tissues, ESCC tissues and paired normal oesophagus tissues were obtained from inpatients who had previously received endoscopic submucosal dissection (ESD) or oesophagectomy with no chemoradiotherapy in the Department of Gastroenterology and the Department of Cardiothoracic Surgery at Zhongda Hospital Affiliated of Southeast University from February 2019 to November 2021. Staging of superficial neoplastic lesions of the oesophagus was done according to the Paris classification of gastrointestinal neoplasms. The protocol of this study complied with the ethical guidelines of Declaration of Helsinki principles and was authorized by the Ethics Committee of Zhongda Hospital (2019ZDSYLL022-P01). Four pairs of ESCC tissues and normal oesophagus tissues were used to obtain a genome sequence screen (Kangchen Biotech, Shanghai, China). Detailed information is provided in Additional file 1: Table S1. Fold change (FC)/P-value/false discovery rate (FDR) filtration (multiple ≥ 1.5, P < 0.05 and FDR < 0.05) were determined to identify differentially expressed ESCC-related lncRNAs. Raw data are available on the Gene Expression Omnibus (GEO) website (GSE189830).
Four human ESCC cell lines (Eca109, KYSE30, KYSE140 and KYSE410) were purchased from the Institute of Biochemistry and Cell Biology of the Chinese Academy of Sciences (Shanghai, China). The normal human oesophageal epithelial cell line HET-1A was kindly provided by Professor Lin. L (The First Affiliated Hospital of Nanjing Medical University). Cells were cultured in RPMI 1640 medium (Gibco, Carlsbad, CA, USA) containing 10% fetal bovine serum (FBS, Gibco) at 37 °C in a humidified incubator supplemented with 5% CO2.
Short hairpin RNA targeting SNHG16 (sh-SNHG16 #1/2/3) and small interfering RNA (siRNA) against EIF4A3 (si-EIF4A3 #1/2/3) and RhoU (si-RhoU #1/2/3) were synthesized by GenePharma (Shanghai, China) to knock down the respective gene expression. Cell transfection was conducted by Lipofectamine RNAiMAX (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocol. Stable cell lines were established by infection with the indicated lentiviruses and selected for puromycin (1–2 μg/ml, Sigma, MO, USA) resistance. Sequences of the the shRNA and siRNA used in this study are listed in Additional file 1: Table S2.
Total RNA from tissues and cells were extracted by an Omega Total RNA kit (Bio-Tek, USA). Reverse transcription was conducted based on the protocol of the Reverse Transcription kit (Takara, Tokyo, Japan). GAPDH and U6 were employed as normalization controls. The primers used in this study for qRT-PCR are listed in Additional file 1: Table S2. To block transcription, 2 μg/ml actinomycin D (APExBIO, USA) was added to the cell culture medium after transfection. After actinomycin D co-culture for various time points, the remaining mRNA was detected by qRT-PCR.
Western blotting was performed to analyse protein expression. The antibodies used were specific for EIF4A3 (1:1000; Abcam) and RhoU (1:500; Origene). GAPDH (1:6000, GeneTex) and β-actin (1:3000, GeneTex) were used as the controls. Protein bands were visualized using an enhanced chemiluminescence (ECL) chromogenic substrate (Beyotime, Shanghai, China) and assessed by Image-Lab analysis software (San Leandro, CA, USA). Paraffin-block tissues of subcutaneous xenografts in mice were stained with haematoxylin and eosin (HE) and IHC, and subsequently evaluated by a pathologist blindly.
Cell viability was measured with a Cell Counting Kit-8 (CCK8) (Beyotime, Shanghai, China) at 24, 48, 72 and 96 h. Colony formation was performed by seeding 300–500 cells in a six-well plate. Two weeks later, the plates were washed and stained with crystal violet. Cell migration was determined by a Transwell assay and wound healing scratch assay according to standard protocols.
Cells were fixed with 4% paraformaldehyde and subsequently treated with 0.5% Triton X-100. For the FISH assay, a digoxigenin (DIG)-labelled SNHG16 probe (Service Bio, Wuhan, China) was used. Hybridization was conducted by utilizing a fluorescent using an in situ hybridization kit (RIBO Bio, Guangzhou, China) in a dark humidifying box at 37 °C overnight. The nuclei of cells were stained by 4′,6-diamidino-2-phenylindole (DAPI). Images were obtained by an Olympus confocal laser scanning microscope (Olympus Optical, Tokyo, Japan).
The separation of nuclear and cytosolic fractions was performed based on the protocol of the PARIS Kit (Life Technologies, Carlsbad, CA, USA). qRT-PCR was then used to determine the expression of SNHG16. U6 and GAPDH were used as internal controls for nuclear and cytoplasmic RNA.
Sense and antisense of SNHG16 were transcribed in vitro with a T7 Quick High Yield RNA Synthesis Kit (Thermo Fisher Scientific, USA). Transcribed RNA was purified by RNA Clean & Concentrator-25 (Zymo Research, Beijing, China). A Pierce Magnetic RNA–Protein Pull-down kit (Thermo Fisher Scientific, MA, USA) was used according to the manufacturer’s instructions. After RNA pull-down, equal amounts of samples pulled down by sense and antisense SNHG16 were loaded on SDS–PAGE gels. Then, the gel was stained with a Protein Fast Silver Stain Kit (Leagene, Beijing, China) according to the protocol. Bands were cut and analysed by liquid chromatography–mass spectrometry (LC–MS/MS) (Oebiotech Company, Shanghai, China). Protein identifications were retrieved from the human RefSeq protein database (National Center for Biotechnology Information) using Mascot version 2.4.01 (Matrix Science, London, UK).
RIP was implemented with the Imprint RNA Immunoprecipitation (RIP) Kit (Sigma, Aldrich, US). Cell extracts were obtained by RIPA lysis buffer and then incubated with a mixture of magnetic beads and antibodies against EIF4A3. Anti-IgG antibody was utilized as a control. The final co-precipitated RNAs were purified and subjected to RT-PCR or qPCR.
Female BALB/c nude mice (4–6 weeks of age, GemPharmatech Co. Ltd, Nanjing, China) received humane care according to the Guide for the Care and Use of Laboratory Animals, and were raised under specific pathogen-free conditions. A total of 5 × 106 SNHG16 stable knockdown or overexpressed cells and control cells were subcutaneously injected into the back of each mouse. Tumour size was calculated as (length × width2)/2 and recorded every 3 days. Mice were sacrificed 30–40 days after injection, and subcutaneous tumours were obtained and imaged. The animal study was approved by the institutional review board of Southeast University (20210709006) and was performed in compliance with the Basel Declaration.
Experiments in our study were carried out in triplicate, and the values are expressed as the mean ± standard deviation (SD). Statistical significance was determined by the nonparametric Mann–Whitney U test or two-tailed paired Student’s t-test. The findings were considered to be significant at P < 0.05. Statistical analyses were performed using SPSS 22.0 software (IBM, NY, USA) and GraphPad Prism v5.01 (GraphPad, La Jolla, CA, USA).
RNA sequences detected 2145 different lncRNAs, including 175 upregulated (fold change > 1.5, P < 0.05) and 134 downregulated (fold change < 0.5, P < 0.05). Here, we focus on SNHG16, for which no function in ESCC has been previously ascribed. Among all the differentially expressed lncRNAs, SNHG16 was one of the upregulated lncRNAs in ESCC tissues (Fig. 1A). Two publicly accessible microarray datasets, including 301 oesophageal carcinoma samples and 405 normal samples, also verified the higher level of SNHG16 expression (GSE53624, 53,622) (Fig. 1B). Furthermore, we examined SNHG16 expression in 25 primary ESCC tissues and matched normal oesophageal tissues, and found that SNHG16 was significantly upregulated in ESCC tissues (Fig. 1C). We further detected SNHG16 in samples resected by ESD therapy. To our surprise, SNHG16 expression was high in 19 and low in 11 of 30 ESD samples (Fig. 1D), and its expression was correlated with tumour differentiation (P = 0.037) and T stage (P = 0.098), suggesting that SNHG16 upregulation was an early event in ESCC development. The correlation between SNHG16 expression and detailed clinical baseline characteristics of the patients in our study are presented in Table 1.
To explore the biological role of SNHG16 in ESCC, we detected SNHG16 expression in diverse human ESCC cell lines. As shown in Fig. 2A, the level of SNHG16 was increased in ESCC cell lines (Eca109, KYSE30, KYSE140 and KYSE410) compared with the normal oesophageal cell line (HET-1A). Three independent shRNAs, #1, #2 and #3, were transfected into ESCC cell lines to knockdown SNHG16 expression. It was satisfactory that SNHG16 was more efficiently diminished by shRNA #2, which was selected for the primer sequence of the lentivirus package (Fig. 2B). As endogenous SNHG16 levels in KYSE30 and KYSE410 cells were higher than those in Eca109 and KYSE140 cells, they became stable cell lines packaged with lentivirus to stably knockdown SNHG16. Additionally, SNHG16 was ectopically overexpressed with a lenti-SNHG16 vector in Eca109 and KYSE140 cells. Cell proliferative vitality was analysed by CCK-8 and colony formation assays, which showed that knockdown of SNHG16 decreased cell proliferation and colony formation compared with scrambled control cells (Fig. 2C, D). To estimate whether SNHG16 could affect ESCC cell migration, Transwell and scratch wound healing assays were performed. Interestingly, the number of migrating KYSE30 and KYSE410 cells was strongly reduced after SNHG16 knockdown (Fig. 2E). Scratch wound healing assays also showed that SNHG16 knockdown significantly suppressed migration ability (Fig. 2F). shRNA depletion experiments may suffer from off-target effects, therefore, we subsequently investigated the effect of SNHG16 overexpression. As shown in Fig. 2C–F, Eca109 and KYSE140 cells overexpressing SNHG16 displayed more cell proliferation and migration ability than controls. Altogether, gain- and loss-of-function experiments showed that SNHG16 promotes ESCC cell proliferation and migration in vitro.
To further clarify if SNHG16 exerts ESCC cell carcinogenesis effects in vivo, Eca109 cells stably overexpressing SNHG16 or control empty vector were subcutaneously injected into nude mice. As displayed in Fig. 3A, tumour volumes and tumour growth in the LV-SNHG16 group was obviously faster than in the control group in the whole process of feeding. After 35 days, ultimate xenograft tumours were obtained. The xenograft tumours were photographed and showed that tumours formed in the control group were generally smaller than those in the LV-SNHG16 group (Fig. 3A). In contrast, the tumour weight and tumour growth after injection with KD-SNHG16 were smaller than those of the negative control groups (Fig. 3B). We further detected the staining of Ki-67 and CD34 through immunohistochemistry (IHC) analysis, which showed higher Ki-67 and CD34 intensity in the LV-SNHG16 group than in the control group, while crosscurrent results were observed in the KD-SNHG16 group (Fig. 3C).
To further demonstrate the potential molecular mechanisms of SNHG16 in ESCC, subcellular fractionation and FISH staining were used. As displayed in Fig. 4A, B, SNHG16 was mostly located in the cytoplasm against the nucleus, which suggested that SNHG16 may play a regulatory role at the post-transcriptional level. Pull-down assays were carried out to identify the probable RNA binding proteins (RBPs) binding to SNHG16. Intriguingly, Fig. 4C showed specific bands in the 40–55 kDa, 35 kDa and 15 kDa regions by silver staining, which implies that some RBPs bind to SNHG16. Considering that the range of 40–55 kDa can pull down more proteins, we performed LC–MS from this band to look for specific RBPs interacting with SNHG16. Subsequently, we discovered 341 differential RBPs binding to SNHG16 and 164 RBPs binding to antisense SNHG16, according to LC–MS (Fig. 4D). We stripped away the overlapping proteins and focused on EIF4A3, which specifically binds to SNHG16 (Fig. 4E). As shown in Fig. 4F, the abundance of SNHG16 was detected in the precipitates of EIF4A3 antibody, and the enrichment of EIF4A3 protein in the products pulled down by SNHG16 (Fig. 4G) further confirmed the results of LC–MS. Dramatically, we noticed that the level of EIF4A3 remained unaltered after SNHG16 knockdown or overexpression (Fig. 4H), and SNHG16 exhibited no significant change with EIF4A3 depletion (Fig. 4I), which suggests that SNHG16 and EIF4A3 are not downstream regulators of each other but may form a complex. Altogether, SNHG16 may recruit EIF4A3 to regulate its downstream genes.
The online GEPIA database (http://gepia.cancer-pku.cn/) shows that EIF4A3 is highly upregulated in oesophageal cancer, and its expression is positively correlated with SNHG16 (Additional file 1: Fig. S1A). To verify its role in ESCC, we synthesized siRNAs target EIF4A3 to knock down its expression. As shown in Additional file 1: Fig. 1B, si-EIF4A3 #1 exhibited ~ 50% knockdown efficiencies and was selected for subsequent functional experiments. CCK-8 and colony formation assays showed that EIF4A3 downregulation significantly reduced ESCC cell viability (Additional file 1: Fig. S1C-D). In addition, cell migration ability was also weakened due to EIF4A3 knockdown according to the transwell and scratch wound healing assays (Additional file 1: Fig. S1E–F). These findings indicated that EIF4A3 promoted ESCC cell malignant proliferation and migration, corresponding with the oncogenic role of SNHG16 in ESCC.
To investigate the associated signal pathways and potential target genes involved in SNHG16–EIF4A3 regulation in ESCC, a high-resolution transcriptome microarray (Shengyin Biotech, Shanghai, China) after SNHG16 or EIF4A3 knockdown in ESCC cells was performed. Microarray analysis identified 20,456 differentially expressed genes after SNHG16 knockdown, and 22,602 altered genes after EIF4A3 knock down (fold change > 1.5, P < 0.05). Notably, we found 204 genes at the overlap of these two gene sets, which were indicated to be the co-targets regulated by SNHG16 and EIF4A3 (Fig. 5A). The mRNA levels of RhoU, FOXO6, WNT4, ST6GALNAC1, AGR2, P4HTM, NELL2 and ALPP were significantly downregulated due to SNHG16 or EIF4A3 knockdown in ESCC cells according to RNA-Seq (Fig. 5B). To further validate the screen common target mRNAs, we performed qRT-PCR to explore the regulation of the eight mRNA by SNHG16 and EIF4A3. As displayed in Fig. 5C, only RhoU mRNA was significantly diminished in both KYSE30 and KYSE140 cells when SNHG16 or EIF4A3 was knocked down. In addition, the protein level of RhoU was significantly reduced after SNHG16 or EIF4A3 silencing (Fig. 5D). Furthermore, the results of RIP assay showed that EIF4A3 could interact with RhoU, and the enrichment of RhoU in anti-EIF4A3 precipitates was strengthened due to SNHG16 overexpression (Fig. 5E). Previous studies have reported that lncRNAs and RBPs can regulate mRNA stability, so we treated KYSE30 and KYSE140 cells with actinomycin D, which measures the decay of pre-existing mRNA. As shown in Fig. 5F, downregulation of SNHG16 or EIF4A3 decreased the RhoU mRNA half-life. Co-silencing SNHG16 and EIF4A3 in ESCC cells further decreased RhoU mRNA stability. However, the upregulation of SNHG16 did not strengthen RhoU mRNA stability (Fig. 5G). To illustrate whether the function of SNHG16 was dependent on EIF4A3, we further transfected LV-SNHG16 cells with si-EIF4A3. As expected, EIF4A3 knockdown decreased RhoU mRNA stability in LV-SNHG16 cells, which implied a more dominant role in regulating mRNA stability (Fig. 5G). Altogether, these results implied that SNHG16 modulated RhoU expression by recruiting EIF4A3 to enhance RhoU mRNA stability.
To explore whether RhoU was involved in SNHG16-induced ESCC cell proliferation and migration, we carried out rescue experiments. Figure 6A shows that siRNA #1, #2 and #3 could not adequately inhibit inhibition individually, so we used siRNA #1, #2 and #3 by using the smart pool method to transfect ESCC cells in the following functional assays to achieve more effective RhoU inhibition. Fortunately, CCK-8 and colony formation assays showed that cell proliferation was increased by SNHG16 overexpression and was repressed when RhoU was knocked down (Fig. 6B, C). Similarly, cell migration ability was impaired after RhoU suppression (Fig. 6D, E). Rescue experiments showed that SNHG16 partially affected the tumourigenesis and development of ESCC through RhoU.
Long noncoding RNAs (lncRNAs) have been recently identified as key participators in cancer-related biological processes, and indicate novel molecular targets in cancer. Herein, we performed a high-throughput analysis of ESCC tissues and normal oesophageal tissues and discovered 2145 aberrantly expressed lncRNAs, which updates the current ESCC lncRNA profile. We first reported high SNHG16 expression in high-grade intraepithelial neoplasia (HG-IEN) and showed that its expression was correlated with tumour differentiation and T stage, which indicates that it may play an oncogenic role in early ESCC. Mechanistically, we acknowledge that SNHG16 could bind to some RBPs. Furthermore, we targeted eukaryotic translation initiation factor (EIF4A3), a core component of exon junction complex, and demonstrated that the SNHG16–EIF4A3 coalition ultimately regulated the expression of the Ras homolog family member U (RhoU). SNHG16 modulated RhoU expression by recruiting EIF4A3 to enhance the mRNA stability of RhoU. In conclusion, our data suggest that the SNHG16–EIF4A3–RhoU axis might provide new insight into the mechanism underlying ESCC development. Small nucleolar RNA host gene 16 (SNHG16), located on 17q25.1, was first reported in aggressive neuroblastoma [22]. Subsequent studies identified its oncogenic role in other cancers, such as lung [23], cervical [24], breast [25] and colorectal cancers [26]. However, its role in hepatocellular cancer is controversial [27, 28], which may be attributed to tissue-specific or cell type-specific properties. Recently, SNHG16 expression was shown to be upregulated in ESCC tissues compared with normal tissues [29, 30], indicating its oncogenic effect in ESCC. In this study, we noticed that SNHG16 was upregulated in ESCC tissues, according to our microarray analysis. We further explored its expression in a large cohort of ESCC tissues and confirmed its upregulation in ESCC tissues and ESCC cell lines. Currently, ESCC tends to be detected at an early stage because of the prevalence of upper gastrointestinal endoscopy screening [31]. Endoscopic submucosal dissection (ESD) has become an alternative, minimally invasive strategy to oesophagectomy, especially for oesophageal intraepithelial neoplasia (IEN) [32]. The detection of SNHG16 in IEN can help us to better understand its role in the tumourigenesis of ESCC. Here, we collected 30 pairs of oesophageal neoplasia samples (obtained by ESD therapy) and first found that the level of SNHG16 was high in 19 T1N0M0 patients, which indicates that SNHG16 is an ESCC-related biomarker. Furthermore, in vitro and in vivo assays showed that ectopic expression of SNHG16 prompted ESCC cell proliferation and migration ability. These findings imply an oncogenic role of SNHG16 in the development and progression of ESCC. Accumulating evidence suggests that lncRNAs promote or suppress cancer by sponging miRNAs. It was originally reported that SNHG16 has 27 AGO/miRNA binding sites along its full length, indicating that SNHG16 might function as a competing endogenous RNA (ceRNA), “sponging” miRNA off its cognate targets [26]. Subsequent studies have revealed that SNHG16 competitively binds with miR-4518 [33], miR-140-5p [34], miR-4500 [35] and miR-302a-3p [36] in various cancer types. Other confirmed mechanisms for lncRNAs in the cytoplasm involve post-transcriptional regulating mRNA stability or accessibility to the translational machinery [37], which is part of the interaction with RNA-binding proteins (RBPs) [38, 39]. For instance, lncRNA MEG3 induced Shp mRNA decay by interacting with PTBP1 to facilitate cholestatic liver injury [40]. Linc01093 triggered the mRNA decay of GLI1 through interaction with IGF2BP1 to suppress hepatocellular carcinoma (HCC progression [41]. In this study, we found that SNHG16 was mostly located in the cytoplasm in ESCC cell lines, which suggests its vital role in post-transcriptional regulation. We explored whether some RBPs interact with SNHG16 by RNA protein pull down and LC–MS analysis. According to the literature, EIF4A3 is one of the three core components of the exon junction complex (EJC), which causes mRNA decay and regulates protein expression at the translational and post-translational levels [42, 43]. We initially noticed that EIF4A3 was one of the RBPs interacting with SNHG16 and further confirmed the abundant binding relationship between them through RNA pull-down and RIP assays. Therefore, we hypothesized that SNHG16–EIF4A3 could regulate target mRNA stability. According to RNA-Seq, we found that RhoU was the common target of SNHG16 and EIF4A3. As expected, knocking down the expression of SNHG16 or EIF4A3 separately decreased the RhoU mRNA stability, and co-reduction of SNHG16 and EIF4A3 further decreased the half-life of RhoU. However, overexpression of SNHG16 failed to increase the mRNA stability of RhoU, which suggests that the mRNA stability regulation of SNHG16 was more dependent on EIF4A3. Rho GTPases are class of small G proteins belonging to the Ras superfamily that regulate number of cell functions, including cell migration, cell proliferation, cell junction and cell polarity. The atypical Rho GTPase RhoU was originally isolated as a gene transcriptionally upregulated in wnt-1-transformed mouse mammary epithelial cells that shares distinct homology with Cdc42, as well as some biological functions [44]. For example, RhoU binds and activates p21-activated kinase (PAK1), induces filopodia and regulates cell tight junctions [45]. Impaired RhoU activity in fatty acid synthase-depleted cells leads to reduced adhesion turnover downstream of paxillin serine phosphorylation, which is rescued by the addition of exogenous palmitate [46]. Previous studies reported that knockout of RhoU led to increased peripheral adhesions and reduced paxillin S272 phosphorylation, which is required for adhesion disassembly [45]. Upregulated RhoU in prostate cancer correlated with disease progression, and silencing of RhoU was shown to reduce the migratory ability of MDA-MB-231 and PC3 breast cancer cells [45, 47]. In our study, we found that EIF4A3 could interact with RhoU, and the enrichment of RhoU in anti-EIF4A3 precipitates was strengthened by SNHG16 overexpression. In conclusion, we deemed that SNHG16 modulates RhoU expression by recruiting EIF4A3 to enhance the mRNA stability of RhoU. To determine whether RhoU participates in the oncogenic role of SNHG16, we restrained the level of RhoU in SNHG16-overexpressing cells. Excitingly, we noticed that RhoU knockdown repressed SNHG16 carcinogenesis in ESCC cells. As we did not find an effective specific siRNA targeting RhoU, we were unable to perform in vivo experiments to confirm the SNHG16–RhoU axis. Despite this, we perceived the involvement of RhoU in SNHG16-induced ESCC cell proliferation and metastasis on the basis of in vitro studies.
Our work demonstrates that upregulation of SNHG16 could promote ESCC growth and metastasis associated with tumour differentiation and T stage, which might be recognized as a potential therapeutic target for ESCC. Mechanistically, SNHG16 could interact with EIF4A3 and regulate RhoU mRNA stability. Targeting SNHG16–EIF4A3–RhoU signalling may provide new insights into ESCC treatment strategies. Our findings may provide new insight into how SNHG16 regulates mRNA stability and promote our comprehension of lncRNA regulatory characteristics in ESCC malignant development and progression.
Additional file 1: Figure S1. EIF4A3 was upregulated in ESCC and promoted ESCC cell proliferation and migration. (A) Relative expression of EIF4A3 in human oesophageal cancer tissues (n = 162) compared with noncancerous tissues (n = 11) and a positive correlation with SNHG16 via the GEPIA database. (B) Western blot analysis of EIF4A3 after si-NC or si-EIF4A3 transfection in ESCC cells. Mock was the blank control group. GAPDH was used as an internal control. CCK-8 assays (C) and colony formation assays (D) were used to determine the proliferation ability of si-EIF4A3-transfected KYSE30 and KYSE410 cells. Transwell assays (E) and wound healing assays (F) were performed to investigate the migratory abilities of si-EIF4A3-transfected KYSE30 and KYSE410 cells. *P < 0.05, **P < 0.01, ***P < 0.001. | true | true | true |
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PMC9552847 | Changze Song,Jianong Zhang,Xiao Liu,Meilu Li,Dejie Wang,Zhijian Kang,Jiaao Yu,Jiuwei Chen,Hongxin Pan,Honglei Wang,Guangbin Li,Haojie Huang | PTEN loss promotes Warburg effect and prostate cancer cell growth by inducing FBP1 degradation | 27-09-2022 | PTEN,SKP2,ubiquitination,PCa,FBP1 | Rationale Fructose-1,6-bisphosphatase (FBP1) is a tumor suppressor and a key enzyme negatively regulating Warburg effect in cancer. However, regulation of FBP1 protein expression and its exact role in prostate cancer (PCa) is largely unclear. Phosphatase and tensin homolog (PTEN) is one of the most frequently deleted tumor suppressor genes in human PCa. However, the role of PTEN loss in aberrant Warburg effect in cancer remains poorly understood. Methods Expression of PTEN and FBP1 was analyzed in several PCa cell lines and prostate tumor tissues in mice. Western blot (WB) and RT-PCR approaches were used to examine how PTEN regulates FBP1 expression. Co-immunoprecipitation (co-IP) and in vivo ubiquitination assays were used to define the regulatory mechanisms. A PCa xenograft model was employed to determine the impact of PTEN regulation of FBP1 on PCa growth in vivo. Result We demonstrated that in a manner dependent of PI3K/AKT signal pathway PTEN regulated FBP1 expression in various PCa cell lines and tumors in mice. We confirmed that this regulation took place at the protein level and was mediated by SKP2 E3 ubiquitin ligase. Mechanistically, we showed that serine 271 phosphorylation of FBP1 by cyclin-dependent kinases (CDKs) was essential for SKP2-mediated degradation of FBP1 protein induced by PTEN loss. Most importantly, we further showed that loss of PTEN expression enhanced Warburg effect and PCa growth in mice in a manner dependent, at least partially on FBP1 protein degradation. Conclusions Our results reveal a novel tumor-suppressive feature of PTEN in restraining FBP1 degradation and the Warburg effect. These results also suggest that prohibiting FBP1 protein degradation could be a viable therapeutic strategy for PTEN-deficient PCa. | PTEN loss promotes Warburg effect and prostate cancer cell growth by inducing FBP1 degradation
Fructose-1,6-bisphosphatase (FBP1) is a tumor suppressor and a key enzyme negatively regulating Warburg effect in cancer. However, regulation of FBP1 protein expression and its exact role in prostate cancer (PCa) is largely unclear. Phosphatase and tensin homolog (PTEN) is one of the most frequently deleted tumor suppressor genes in human PCa. However, the role of PTEN loss in aberrant Warburg effect in cancer remains poorly understood.
Expression of PTEN and FBP1 was analyzed in several PCa cell lines and prostate tumor tissues in mice. Western blot (WB) and RT-PCR approaches were used to examine how PTEN regulates FBP1 expression. Co-immunoprecipitation (co-IP) and in vivo ubiquitination assays were used to define the regulatory mechanisms. A PCa xenograft model was employed to determine the impact of PTEN regulation of FBP1 on PCa growth in vivo.
We demonstrated that in a manner dependent of PI3K/AKT signal pathway PTEN regulated FBP1 expression in various PCa cell lines and tumors in mice. We confirmed that this regulation took place at the protein level and was mediated by SKP2 E3 ubiquitin ligase. Mechanistically, we showed that serine 271 phosphorylation of FBP1 by cyclin-dependent kinases (CDKs) was essential for SKP2-mediated degradation of FBP1 protein induced by PTEN loss. Most importantly, we further showed that loss of PTEN expression enhanced Warburg effect and PCa growth in mice in a manner dependent, at least partially on FBP1 protein degradation.
Our results reveal a novel tumor-suppressive feature of PTEN in restraining FBP1 degradation and the Warburg effect. These results also suggest that prohibiting FBP1 protein degradation could be a viable therapeutic strategy for PTEN-deficient PCa.
Non-malignant cells primarily rely on mitochondrial oxidative phosphorylation to produce the energy needed in the processes of life. In contrast, one of the common characteristics of tumor cells is that they metabolize glucose into lactic acid even if there is sufficient oxygen, which is called aerobic glycolysis or “Warburg effect” (1). Indeed, mounting evidence suggests that this effect is closely associated with tumor carcinogenesis and progression (2). Furthermore, current research has suggested that this metabolic change can be accomplished by a variety of mechanisms (3), including the abnormal regulation of related enzymes in glucose metabolism (4). Gluconeogenesis plays important roles in glucose homeostasis in normal cells. It is also essential in regulating aerobic glycolysis in cancerous cells (5, 6). Fructose-1,6-bisphosphatase (FBP1) is the rate-limiting enzyme in gluconeogenesis (7) and plays a key function in Warburg effect (4, 8–10). The loss of FBP1 may be an essential tumorigenic event that promotes the development of basal-like breast cancer cells in epithelial mesenchymal transformation (4). In gastric cancer, colon cancer and hepatocellular carcinoma, the expression of FBP1 is downregulated (8, 9, 11), and its deletion is related to the poor prognosis of clear cell renal cell carcinoma and hepatocellular carcinoma (10, 11). These studies have shown that FBP1 exerts a necessary function in regulating tumor glucose metabolism and cancer progression. Prostate cancer (PCa) is the most commonly diagnosed malignancy and the second leading causes of death in American men (12). Despite the high morbidity and mortality of PCa, the understanding of molecular mechanisms related to the occurrence and evolution of this malignant disease is incomplete. PTEN functions as a lipid phosphatase to dephosphorylate phosphatidylinositol (3–5) trisphosphate (PtdIns (3–5) P3 or PIP3) (13). It is a multi-functional tumor suppressor and is often lost in human cancer, including PCa (14–17). Elevated activation of the signaling networks through the phosphoinositide 3-kinase (PI3K) group of lipid kinases by loss of PTEN is a characteristic of most cancers such as PCa (18–21). Additionally, PTEN, as the main negative regulator of the PI3K/AKT pathway, is a key regulator controlling lipid and glucose metabolism and mitochondrial functions in cell (22). Previous studies have shown that the serine/threonine kinase AKT, as a downstream target of PI3K/PTEN, can phosphorylate a variety of metabolic related proteins, such as AS160, GSK3, FOXO and PGC-1a (23–26). In this study, we found that PTEN inhibited the degradation of FBP1 protein, which was mediated via phosphorylation-dependent ubiquitination. Our results also suggest that the deregulation of FBP1 may be the key mechanism of tumor progression driven by Warburg effect in PTEN-deficient PCa.
22Rv1, DU145 and 293T cell lines were purchased from ATCC (Manassas, VA). PTEN WT and -null MEFs were originally generated from Pten knockout mice and kindly provided by Dr. Zhenbang Chen (Meharry Medical College, Nashville, TN). 22Rv1 and DU145 cells were cultured in RPMI 1640 medium (Corning Cellgro) with 10% fetal bovine serum (FBS) (Thermo Fisher Scientific). 293T cells and MEFs were cultured in Dulbecco’s modified Eagle’s medium (Corning Cellgro) supplied with 10% FBS. All cell lines were routinely cultured in 37°C, 5% CO2 incubator.
The expression plasmids for Flag-FBP1, HA-FBP1, HA-Ub and HA-SKP2 had been generated in our lab. The Flag-FBP1 mutant S271A was generated by using the KOD-Plus Mutagenesis Kit (Toyobo). The antibodies used in this study include: FBP1 (Abcam); PTEN, AKT and pS473 AKT (Cell Signaling Technology); SKP2, ERK2 and p27Kip1 (Santa Cruz Biotechnology); Ser/Thr-p (BD Scientific); HA tag (Covance); β-Tubulin and Flag tag (Sigma). The chemicals used include: LY294002 (Invitrogen), MG132 (Millipore), CHX (Sigma) and Roscovitine (MedChemExpress).
The cells were harvested and lysed in RIPA buffer for more than 15 min on ice, and the lysate was centrifuged at 15,600 xg at 4°C for 10 min. After the supernatant was quantified using the BCA protein quantitative kit (Thermo Fisher Scientific), 4x DTT containing loading buffer (Thermo Fisher Scientific) was added to protein samples and the mixed samples were heated in 100°C for 5 min. The samples were separated on SDS-PAGE and transferred to nitrocellulose membrane (Thermo Fisher Scientific). The membrane was pre-blocked with 5% skim milk for 1 h at room temperature and incubated with primary antibody at 4°C overnight. Membranes were washed in 1x TBST for 3 times, 5 min each and then incubated with horseradish peroxidase-conjugated secondary antibody at room temperature for 1 h. Blots were finally visualized using SuperSignal West Pico Stable Peroxide Solution (Thermo Fisher Scientific).
Total RNA was isolated from cells by directly adding Trizol reagent (Thermo Fisher Scientific) into cultured cells. The first strand cDNA was synthesized from 1 µg of total RNA with GoScript kit (Promega). Real-time polymerase chain reaction (PCR) was carried by using SYBR green mix (Bio-Rad), C1000 Touch Thermal Cycler and CFX96 real-time system (Bio-Rad). All PCR signals were normalized to the internal control GAPDH cDNA, and the fold change was calculated using the 2-△Ct method. The DNA sequence information of primers used for RT-qPCR is provided in Table S1 .
Co-IP was performed using the method reported previously (27). Cells transfected with expression plasmids were harvested and cells were lysed in IP buffer (Sigma-Aldrich, St. Louis, MO) on ice for 15 min or longer, and the cell lysate was centrifuged at 15,600 xg for 10 min at 4°C. The supernatant was transferred to a fresh tube. The supernatant was then incubated with protein A/G agarose beads (Thermo Fisher Scientific) and primary antibodies at 4°C overnight. The IP beads were washed extensively (six times) on ice with IP buffer, and then re-suspended in 1 × SDS loading buffer followed by SDS-PAGE and Western blot analysis.
293T cells were transfected with plasmids for HA–ubiquitin and related genes. After 36 h of transfection, the cells were treated with 30 μM of MG132 for 6 h, and then lysed in 1% SDS buffer and boiled for 10 min. The cell lysate was incubated with anti-FLAG M2 agarose beads (Sigma) at 4°C for 4 h. The beads was washed for 4 times using BC100 buffer containing 0.2% of Triton X-100. The pulldown proteins were eluted with 3X FLAG polypeptide at 4°C. Ubiquitinated proteins were analyzed by SDS-PAGE and Western blot.
The procedure for colony formation assay was carried out as previously described (28, 29). In short, 1×103 cells were plated into each well in 6-well plates. The next day, the cells were treated with vehicle or Roscovitine (10 μM, Cat# HY-30237, MedChemExpress). After about 16 days of treatment, the cells were fixed with 4% paraformaldehyde for 15 min, stained with (0.5% w/v) crystal violet for 1 h, and then gently rinsed with running water. The cell colonies with more than 50 cells were counted, and the survival curve was generated using linear regression.
Cell viability was measured using an MTS kit (Promega) in accordance with the instruction from the manufacturer. Briefly, the cells were seeded into 96-well plates with about 1,000 cells per well. After the cells attached to the bottom of the well, the designated drugs were added to each well at the indicated concentration. At the specified time points, CellTiter 96R Aqueous One Solution Reagent with a final concentration of 10% (V/V) was added into the wells to measure cell viability. Absorbance was measured after incubating the cell culture plates in the cell incubator at 37°C for 60 min. The absorbance of 490 nm was read in a microplate reader.
Lentivirus-based control and gene-specific shRNAs were purchased from Sigma-Aldrich. 293T cells were transfected using Lipofectamine 2000 with shRNA plasmids and virus package plasmids (PMD2.G and pSPAX2). Twelve hours after transfection, the spent medium was replaced with fresh DMEM containing 10% fetal bovine serum (FBS) and 1 mM sodium pyruvate. After 36 hours of transfection, the culture medium containing packaged virus was filtered using 0.45 μm filters and added to target cells by supplying 8 µg/mL polybrene. shRNA sequences are provided in Table S2 .
Cells (4.0 × 105/well) were seeded into each well of 6-well plates and cultured in phenol red-free RPMI 1640 medium (Thermo Fisher Scientific) for 24 h. The spent medium was collected and the glucose concentration of the spent medium was measured using the Glucose (GO) Assay Kit in accordance with the manufacturer’s instructions (Sigma-Aldrich). Glucose consumption was calculated based on the difference of glucose concentration between the spent and fresh medium. Lactate concentration of the spent medium was quantitatively measured using a L-Lactate Assay kit according to the manufacturer’s instructions (Eton Bioscience). Lactate production was calculated according to the difference of lactate concentration between the spent and fresh medium. The optical densities were measured at 570 nm wave-length in a plate reader.
All animal studies were approved by the Mayo Clinic Institutional Animal Care and Use Committee (IACUC). Mice were housed with a 12 h light/12 h dark cycle and free to eat and drink. Probasin (Pb)-driven Cre4 recombinase transgenic mice (C57BL/DBA2) were originally generated in the laboratory of Dr. Pradip Roy-Burnam at the University of Southern California, Los Angeles, CA (17) and acquired from the National Cancer Institute (NCI) Mouse Repository. Pten Loxp/Loxp conditioned knockout mice (129/Balb/c) were originally generated in the laboratory of Dr. Hong Wu at the University of California, Los Angeles, CA (18), and purchased from Jackson Laboratory (004597). Littermate mice were used for control and target mice to ensure comparable genetic backgrounds. The sequence information of all the PCR primers used is listed in Table S1 .
SCID mice, at 6 weeks of age, were bred in house and randomly divided into different groups. The animal study was approved by the IACUC at Mayo Clinic. All mice were housed in standard conditions with a 12 h light/dark cycle and access to food and water ad libitum. DU145 cells (5×106 in 100 μl 1×PBS) infected with lentivirus expressing empty vector (EV) or PTEN-specific shRNAs in combination with Flag-tagged FBP1-WT or S271A mutant were first mixed with Matrigel (BD Biosciences, 100 μl) on ice and then the mixed cells were injected s.c. into the right flank of mice. Xenograft growth was measured in a blinded fashion using a digital caliper and the volume of xenografts was estimated using the formula (L×W2)/2, where L is the length of tumor and W is the width. After the completion of measurement, mice were euthanized with CO2 and xenograft tumors were isolated and weighed. Tumor tissues were divided, and a portion was formalin-fixed and paraffin-embedded (FFPE) and the rest was frozen for protein and RNA extraction.
Unless otherwise specified, all experiments were repeated three or more times. One-sided or two-sided paired Student’s t test was used for single comparison, and multi comparisons were carried out using one-way ANOVA test. The P < 0.05 is considered statistically significant.
Previous studies have shown that the loss of PTEN tumor suppressor leads to the abnormal activation of PI3K signaling pathway, which is considered to be one of the most common oncogenic events in the pathogenesis of PCa (21). FBP1 is a key rate-limiting enzyme in gluconeogenesis (30). Increasing evidence shows that FBP1 is a key enzyme in regulating tumor glucose metabolism, and the deletion of FBP1 gene is related to cancer progression (4, 8–10). We were interested in investigating whether the expression of PTEN affected cancer metabolism by regulating the level of FBP1 in PCa cells. Therefore, we knocked down endogenous PTEN by the usage of two independent gene-specific small hairpin RNAs (shRNAs) in 22Rv1 and DU145 PCa cell lines. WB and RT-PCR showed that PTEN knockdown (KD) reduced the expression of FBP1 at the protein level, but had little impact on the level of FBP1 mRNA ( Figures 1A, B ). Restoring PTEN in PTEN-negative PC-3 and C4-2 PCa cell lines induced FBP1 protein expression, but exerted little impact on FBP1 mRNA expression ( Figures 1C, D ). Furthermore, we showed that deletion of Pten gene in MEFs induced downregulation of Fbp1 protein, but not Fbp1 mRNA expression ( Figures 1E, F ). IHC analyses further showed that knockout of Pten gene in the murine prostate downregulated Fbp1 protein level in mice ( Figure 1G ). These results suggest that PTEN positively regulates FBP1 expression in different human PCa cell lines and mouse prostate tumors. PTEN is an established negative regulator of PI3K/AKT signaling pathway (31). To determine how inhibition of this pathway affected FBP1 expression, PTEN-negative LNCaP PCa cells were treated with different doses of the PI3K inhibitor LY294002. We demonstrated that inhibition of AKT phosphorylation by LY294002 correlated with upregulation of FBP1 protein dose-dependently ( Figure 1H ). Collectively, these data suggest that PTEN regulates FBP1 protein expression via the PI3K/AKT signaling pathway.
It has been reported that FBP1 can be degraded by ubiquitination (32). We sought to determine whether loss of PTEN regulated this process. To this end, we treated control and PTEN knockdown cells with the protein de novo synthesis inhibitor cycloheximide (CHX) and examined FBP1 protein expression level at different time points. We demonstrated that PTEN depletion largely decreased the half-life of FBP1 protein in 22Rv1 and DU145 cells ( Figures 2A, B ), suggesting that PTEN might negatively influence FBP1 protein degradation via proteasome pathway. To test this hypothesis, PTEN small hairpin RNAs (shPTENs) were transferred to 22Rv1 and DU145 cells and then treated with MG132. We found that PTEN loss-induced downregulation of FBP1 protein was blocked by MG132 treatment in both 22Rv1 and DU145 cells, but little or no effect was observed at the mRNA level ( Figures 2C–F ). In agreement with these results, the ubiquitin assays showed that PTEN depletion largely augmented FBP1 protein polyubiquitination ( Figure 2G ). Thus, these data suggest that loss of PTEN promotes the ubiquitination and proteasomal degradation of FBP1 protein in PCa cells.
Consistent with the previous reports that inhibition of the PI3K/AKT signaling decreases expression of SKP2, an adaptor protein of the SKIP1-CULLIN1-F-Box protein (SCF) E3 ligase complex (33, 34), we found that depletion of PTEN increased mRNA and protein expression of SKP2 in 22Rv1 and DU145, which co-occurred with downregulation of FBP1 protein ( Figures 3A, B ). We, therefore, sought to determine whether SKP2 mediates FBP1 degradation induced by PTEN loss in PCa cells. To this end, shSKP2 was transfected into 22Rv1 and DU145 cells and protein expression was determined by WB. We showed that knockdown of SKP2 increased FBP1 expression at protein, but not mRNA level ( Figures 3C, D ). Moreover, we found that ectopic expression of SKP2 decreased FBP1 expression in a dose-dependent manner at the protein level, but had no drastic impact on FBP1 mRNA expression ( Figures 3E, F ). Furthermore, we showed that knockdown of endogenous SKP2 caused stabilization of FBP1 protein in both 22Rv1 and DU145 cell lines ( Figures 3G, H ). Next, we sought to determine whether SKP2 mediates FBP1 degradation induced by PTEN loss. To this end, we knocked down PTEN and/or SKP2 in 22Rv1 and DU145 cells and we found that PTEN loss-induced downregulation of FBP1 protein was completed blocked by knocking down SKP2 in these two cell lines ( Figures 3I, J ). These data indicate that SKP2 mediates FBP1 degradation induced by PTEN loss in PCa cells.
It has been known that SKP2 induces K48-linked polyubiquitination and proteasomal degradation of p27Kip1 protein in a manner dependent on cyclin-dependent kinase-2 (CDK2)-mediated phosphorylation of p27Kip1 (35–40). Also, a study has shown that the deletion of PTEN leads to the activation of CDK2 by down-regulating p27Kip1 (41). As expected, we found that PTEN knockdown decreased p27Kip1 expression but most importantly, PTEN loss increased FBP1 phosphorylation ( Figure 4A ). To determine whether CDKs play any role in PTEN loss-induced downregulation of FBP1 protein, we knocked down PTEN in 22Rv1 and DU145 cells and treated cells with or without Roscovitine, a broad inhibitor of CDKs including CDK2 ( Figure 4B ). We demonstrated that Roscovitine treatment blocked the down-regulation of FBP1 protein caused by PTEN deletion in both cell lines, but without obvious impact on mRNA expression ( Figures 4B, C ). Similar results were obtained in wild-type (WT) and Pten knockout MEF cells ( Figures 4D, E ). We further showed that CDK inhibition diminished FBP1 protein decay in 22Rv1 and DU145 cells ( Figures 4F, G ). Together, these data indicate that CDKs mediate FBP1 degradation induced by PTEN loss and this process is blocked by CDK inhibitor.
It is known that CDKs regulate the protein level and function of their downstream substrates through protein phosphorylation (42). We noticed that akin to known CDK substrates such as RB, H1B, FOXO1, EZH2, ATM and p27Kip1, there is a putative CDK phosphorylation site (270KSPNG274) which is similar to the CDK phosphorylation consensus motif K/R-T/S-P-X-K/R (X, any amino acid) ( Figure 5A ). To determine whether the serine 271 (S271) residue plays any role in PTEN loss-induced FBP1 degradation, we generated an FBP1 S271A phosphorylation-resistant mutant. We demonstrated that knockdown of PTEN largely increased phosphorylation of Flag-FBP1-WT, but not the Flag-FBP1-S271A mutant in 293T cells ( Figure 5B ), suggesting that PTEN loss results in S271 phosphorylation on FBP1. We further showed that PTEN knockdown-induced downregulation of FBP1 was blocked by S271A mutation, but this mutant had no obvious effect on the mRNA expression of FBP1 ( Figures 5C, D ). In agreement with these observations, in vivo ubiquitination assays showed that loss of PTEN robustly enhanced polyubiquitination of FBP1-WT, but not the FBP1-S271A phosphorylation-resistant mutant ( Figure 5E ). Thus, these data indicate that the serine 271 phosphorylation on FBP1 is necessary for FBP1 protein degradation induced by PTEN loss.
Given that FBP1 is a major negative regulator of glycolysis, and cancer cells rely heavily on aerobic glycolysis (Warburg effect) for growth, we were very interested to determine whether restored expression of FBP1 inhibited the growth of PCa cells by blocking Warburg effect. As expected, we found that knockdown of PTEN increased glucose metabolism and lactate production in both 22Rv1 and DU145 cells ( Figures 6A, B ). This impact was largely inhibited by ectopic expression of the phosphorylation/degradation-resistant mutant Flag-tagged FBP1-S271A, but only modestly diminished by ectopic expression of Flag-tagged degradable FBP1-WT ( Figures 6A, B ). Similar results were seen in the cell proliferation assays in the two cell lines ( Figures 6C, D ). Next, we evaluated the impact of restored expression of FBP1 on tumor growth in mice. We infected DU145 cells with lentivirus expressing shControl or shPTEN in combination with or without Flag-tagged FBP1-WT or FBP1-S271A and inoculated these groups of cells into SCID mice. We discovered that FBP1-S271A expression, but not FBP1-WT inhibited PTEN knockdown-enhanced tumor growth in vivo ( Figures 6E, F ). Therefore, our data suggest that degradation of FBP1 plays a significant role in contributing to PTEN deletion-induced PCa growth in vitro and in vivo.
The major finding of the current study is the identification of a previously unrecognized molecular mechanism that promotes Warburg effect and cancer progression. FBP1, a recognized tumor suppressor, is known to inhibit cancer development via inhibition of aerobic glycolysis and suppression of the Warburg effect in different cancer types (4, 10, 43). In this study, we have revealed that PTEN plays a key function in regulating FBP1 expression and tumor progression through FBP1 phosphorylation-dependent ubiquitin degradation in PCa, thus defining a new role of PTEN in metabolism and tumor progression. We have found that the loss of PTEN promotes the degradation of FBP1 protein by activating the PI3K/AKT pathway via two mechanisms. On the one hand, activated AKT down-regulates p27, thus increasing the activity of its substrate proteins such as CDKs and promoting the CDK-dependent phosphorylation of FBP1. On the other hand, activated AKT upregulates SKP2 mRNA and then increases the expression of SKP2 protein, which can ubiquitinate CDK-phosphorylated FBP1, and lead to CDK phosphorylation-dependent degradation of FBP1 ( Figure 7 ). Our observation further support the notion that mutation in the CDK-phosphorylation site on FBP1 can hinder the degradation of FBP1 and increases FBP1 expression, thereby restraining Warburg effect and PCa growth. These findings not only provide an mechanistic explanation for the observed PTEN loss-induced downregulation of FBP1 protein in PCa, but also provide mechanistic insight into the tumor growth augmented by the Warburg effect. FBP1 is the rate-limiting enzyme in the process of gluconeogenesis, which converts fructose-1,6-biphosphate to fructose-6-phophate and inorganic phosphate (44). Previous studies have shown that FBP1 is frequently downregulated in a variety of solid tumors (4, 10, 45). Its down-regulation mechanism may be related to DNA hypermethylation of gene promoter or loss of the copy number of the gene (4, 46), histone deacetylation caused by deregulation of HDACs (11) or degradation of FBP1 in tumor cells caused by the E3 ligase TRIM28. It is important that FBP1 downregulation is tightly related to the Warburg effect, which is a key metabolic feature of many cancers. In this study, we have demonstrated that FBP1 protein is destructed after phosphorylation in PTEN-deficient PCa. Consistent with the finding that FBP1 is often downregulated in human cancers, we provide evidence that loss of FBP1 contributes to tumor growth through the Warburg effect in PTEN-deficient PCa. Thus, our findings define a new role of FBP1 in regulating cancer progression. PTEN plays an important role in cancer development and progression. Previous studies have reported that loss of PTEN plays a role in tumor metabolism. In our study, we have demonstrated that PTEN loss leads to phosphorylation of FBP1 at the CDK site and promotes its degradation. This effect is attenuated by mutation of CDK phosphorylation site on FBP1. Our findings reveal PTEN as an upstream protector of FBP1 and uncover a new mechanism by which PTEN regulates metabolism in cancer. The significance of these findings is further accentuated by our observations that expression of PTEN and FBP1 is positively corrected in multiple PCa cell lines and a PCa mouse model. In summary, we have discovered a new role of PTEN in antagonizing Warburg effect by regulating expression of FBP1 and its effect on cell metabolism and tumor growth. Mechanistically, we show that PTEN inhibits phosphorylation-dependent ubiquitination-mediated degradation of FBP1. This finding highlights the importance of FBP1 protein destruction in augmented Warburg effect and growth of PTEN-deficient PCa. Our findings also suggest that targeting PTEN loss-induced FBP1 protein degradation could be a viable strategy for effective treatment of cancers such as PCa with aberrant activation of PI3K/AKT.
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
All animal study was approved by the Mayo Clinic Institutional Animal Care and Use Committee (IACUC).
HH conceived the study. CS, JZ, XL, ML, ZK, JY, and JC performed experiments and collected and analyzed the data. HH and DW supervised the study. CS, JZ, ML and HH wrote the manuscript. All authors contributed to the article and approved the submitted version. CS, JZ and XL have contributed equally to this work.
We thank Lan Shen for the technical assistance. The work was supported by funding from the Mayo Clinic Foundation (to HH).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9552866 | Pooja Singh,Krishna Kumar Choudhary,Nivedita Chaudhary,Shweta Gupta,Mamatamayee Sahu,Boddu Tejaswini,Subrata Sarkar | Salt stress resilience in plants mediated through osmolyte accumulation and its crosstalk mechanism with phytohormones | 26-09-2022 | Brassinosteroids,ethylene,abscisic acid,cytokinins,Jasmonates,salicylic acids,osmolytes,salt stress | Salinity stress is one of the significant abiotic stresses that influence critical metabolic processes in the plant. Salinity stress limits plant growth and development by adversely affecting various physiological and biochemical processes. Enhanced generation of reactive oxygen species (ROS) induced via salinity stress subsequently alters macromolecules such as lipids, proteins, and nucleic acids, and thus constrains crop productivity. Due to which, a decreasing trend in cultivable land and a rising world population raises a question of global food security. In response to salt stress signals, plants adapt defensive mechanisms by orchestrating the synthesis, signaling, and regulation of various osmolytes and phytohormones. Under salinity stress, osmolytes have been investigated to stabilize the osmotic differences between the surrounding of cells and cytosol. They also help in the regulation of protein folding to facilitate protein functioning and stress signaling. Phytohormones play critical roles in eliciting a salinity stress adaptation response in plants. These responses enable the plants to acclimatize to adverse soil conditions. Phytohormones and osmolytes are helpful in minimizing salinity stress-related detrimental effects on plants. These phytohormones modulate the level of osmolytes through alteration in the gene expression pattern of key biosynthetic enzymes and antioxidative enzymes along with their role as signaling molecules. Thus, it becomes vital to understand the roles of these phytohormones on osmolyte accumulation and regulation to conclude the adaptive roles played by plants to avoid salinity stress. | Salt stress resilience in plants mediated through osmolyte accumulation and its crosstalk mechanism with phytohormones
Salinity stress is one of the significant abiotic stresses that influence critical metabolic processes in the plant. Salinity stress limits plant growth and development by adversely affecting various physiological and biochemical processes. Enhanced generation of reactive oxygen species (ROS) induced via salinity stress subsequently alters macromolecules such as lipids, proteins, and nucleic acids, and thus constrains crop productivity. Due to which, a decreasing trend in cultivable land and a rising world population raises a question of global food security. In response to salt stress signals, plants adapt defensive mechanisms by orchestrating the synthesis, signaling, and regulation of various osmolytes and phytohormones. Under salinity stress, osmolytes have been investigated to stabilize the osmotic differences between the surrounding of cells and cytosol. They also help in the regulation of protein folding to facilitate protein functioning and stress signaling. Phytohormones play critical roles in eliciting a salinity stress adaptation response in plants. These responses enable the plants to acclimatize to adverse soil conditions. Phytohormones and osmolytes are helpful in minimizing salinity stress-related detrimental effects on plants. These phytohormones modulate the level of osmolytes through alteration in the gene expression pattern of key biosynthetic enzymes and antioxidative enzymes along with their role as signaling molecules. Thus, it becomes vital to understand the roles of these phytohormones on osmolyte accumulation and regulation to conclude the adaptive roles played by plants to avoid salinity stress.
Soil is a complicated system in which physical and biological processes interact. Various natural and anthropogenic activities influences climate change that leads to disturbed physical and chemical characteristics of soil (Pandey and Choudhary, 2019; Ahirwal et al., 2021). Among environmental changes, soil salinization has been known as a severe threat to agricultural fields (Mukhopadhyay et al., 2021). Approximately 20% of the world’s irrigated land [about 60 million (Mha)] has been globally affected due to salinity (FAO and ITPS, 2015), and with continuous climate change, it is projected to increase to 50% by 2050 (Machado and Serralheiro, 2017; Abdelrahman et al., 2018). In addition to this, FAO has reported that increasing soil salinity could pull 0.3–1.5 million hectares agricultural land out of production each year, reducing yield potential by 20–46 million hectares (FAO and ITPS, 2015). Therefore, crops cannot be cultivated if soil salinity is not controlled and rises above specified salinity thresholds (FAO, 2017). Among abiotic stresses, salinity affects plant growth by hampering photosynthesis, CO2 assimilation and excessive ROS production (Chaudhary and Choudhary, 2021; ElSayed et al., 2021; Selem et al., 2022). The detrimental effects of salinity begin with osmotic or water stress (a reduction in the root’s ability to absorb water), followed by ionic toxicity (nutritional imbalance, formation of ROS species), hormonal imbalance and susceptibility to infection by the pathogen (Choudhary et al., 2017; Talbi et al., 2018). Plants respond to salinity by adapting diverse strategies such as phytohormonal regulation, redox change in potential, osmolyte biosynthesis, and epigenetic control of stress-related genes during stressful conditions. Similarly, salt stress tolerance is a complex trait that includes various signaling pathways, transcription factors, stress-responsive genes (Mansour and Hassan, 2022). However, tolerance to salinity levels varies between plant species, and such plants can be categorized as halophytes or glycophytes. Halophytes are the plants that are endowed with the ability to tolerate salinity up to 200 mM over glycophytes that are salt sensitive under adverse effects of salinity (Flowers and Colmer, 2008; Santos et al., 2016; Song et al., 2016). This salt tolerance mechanism in halophytes involves the reduction of Na+ influx, Na+ compartmentalization, and efflux of Na+ ions (Flowers and Colmer, 2008). In addition to this, ROS scavenging via antioxidant enzymes or quenching them with non-enzymatic molecules such as carotenoids, flavonoids, reduced glutathione, ascorbic acid and compatible osmolytes such as proline, glycine betaine (GB), trehalose sugar (Khan et al., 2015; Per et al., 2018) provide tolerance against salinity stress in the plant (Anjum et al., 2017). Osmolytes majorly contribute to maintaining cellular osmotic adjustment through cell turgidity, protects internal cell components and reduced ionic toxicity. However, multiple pathways have been explored in the biosynthesis of osmolytes in bacteria as well as in plants. In addition to this, phytohormones undoubtedly regulate osmolyte production and accumulation (Per et al., 2017). Phytohormones interact synergistically with osmolytes and bring tolerance to stress (Iqbal et al., 2014). However, the comprehensive role of phytohormones by modulating the biosynthesis of osmolytes has not been explored properly. Therefore, it becomes imperative to understand the underlying mechanism of phytohormones regulating the biosynthesis of osmolytes. Thus, in this present review, we have focused on the synthesis and role of osmolytes in plants and further their modulation via phytohormones under salinity stress.
The term “Salinity” refers to the presence of an excessive amount of soluble salts in the soil that hinders plant growth (Etikala et al., 2021). High salinity is one of the major abiotic stress that is most widely distributed around the globe (Chaudhry and Sidhu, 2021). Since salinity is one of the stringent problems, it can be categorized as Primary and Secondary salinity. Primary salinity occurs in arid and semi-arid climatic zones due to natural, anthropogenic activities and Secondary salinity occur directly as a consequence of man-made activities (Safdar et al., 2019). The detrimental effect of salinity on crop growth is due to changes in physiological, morphological, biochemical and molecular responses in plant growth (Arif et al., 2020; Figure 1). Inhibitory effects of salt stress is influenced by number of factors including salt content, duration of exposure, plant species and varieties, photochemical quenching capability, plant growth stages, stress type, gas exchange characteristics, photosynthetic pigments, and ambient conditions (Shahverdi et al., 2018). At low levels of soil salinity, it enhances the plant length as concluded in various studies on various crops such as Zea mays (Hamada, 1995), Oryza sativa L. (Lee et al., 2011), Vigna unguiculata L. (Ibrahim, 2016), Brassica campestris L. (Memon et al., 2010) and Vicia faba L. (Hanafy et al., 2013). Higher sodium chloride salt concentrations, on the other hand, lowered the height of Vigna mungo L. (Kapoor and Srivastava, 2010), and Tanacetum parthenium L. (Mallahi et al., 2018) plants. Salt stress affects root and stem growth, and hinders nutrient uptake and translocation (Shrivastava and Kumar, 2015). Reduction in the plant growth is mainly due to decreased chlorophyll content which leads to the reduction in photosynthetic capacity of the plants under salinity stress (Netondo et al., 2004). In the context of plant growth, a recent detailed study on tomato with different salt concentrations (75,150 and 300 mM) exhibited a reduction in fresh and dry weight of roots (86.5% and 78.6%), shoot (71% and 72%), chlorophyll and carotenoid contents (22, 18.6%), and anthocyanin (41.1%), respectively (Alzahib et al., 2021). However, at a relatively higher concentration, 300 mM NaCl, reported an increase in proline content (67.37 mg g-1 fresh weight), antioxidant enzymes such as Superoxide dismutase (SOD), and Catalase (CAT), while reduction in malondialdehyde (MDA) content. An increased salt concentration alters the morphology, physiology and metabolism in these landraces in response to salt stress (Alzahib et al., 2021). Similarly, in Medicago truncatula, the effect of salinity on photosynthesis and chlorophyll fluorescence was studied, and total chlorophyll content was significantly reduced by 43% in TN6.18 and only 6% in TN.8.20 compared to control plants. The same effect was reported with carotenoid content, reduced by 51% in the sensitive TN6.18 line but only 13% in the resistant line (Najar et al., 2019). These recent studies indicate that salinity drastically affects the growth and development of plants. Nutritive imbalance another factor of salt stress that disrupts the osmotic equilibrium and further prevails drought conditions (Riaz et al., 2019). Additional effects include hampering reproductive processes such as inhibiting microsporogenesis, promotion of rapid programmed cell death and senescence of fertilized embryos (Suo et al., 2017). TEM micrographs of Solanum melongena treated with 75, 100, and 150 mM NaCl exhibited bulging chloroplasts and an absence of integrated thylakoid membranes associated with big starch grains (Alkhatib et al., 2021). Salinity influences the antioxidant activity of enzymes. For example, in Andrographis paniculata alteration in the activity of antioxidant enzymes, viz. catalase (CAT) and peroxidase (POD) was observed that further reveals the extent of induced changes modulated by salinity stress (Kumar and Srivastava, 2018). In short, the impact of salinity stress has been illustrated in Figure 1.
To comprehend the physiological process of salinity tolerance in plants, one must first understand the cause of growth restriction, which can be due to salt’s osmotic impact on the soil or the toxic effect of salt within the plant body. As a result, plants respond to salinity in two ways: an initial rapid increase in external osmotic pressure at first followed by a gradual response as Na+ accumulates in leaves. In the first phase, plant roots sense the salt concentration above the threshold level, mainly 40 mM NaCl in many plants or less for sensitive plants like rice and Arabidopsis, and significantly decreases the rate of shoot growth. In the second ionic phase, the salt concentration increases excessively in the older leaves due to continuous transport to transpiring leaves over a longer period of time eventually results in higher salt concentration and then leaves die. As a result, if new leaves die faster than they are being produced, the plant’s photosynthetic capacity will no longer meet the carbohydrate requirements of young leaves, declining growth even more (Munns and Tester, 2008). Salinity tolerance is a physiological feature that is linked to a number of mechanisms that influences stress (Roy et al., 2014). However, based on the differential responses of plants, tolerance to salinity can be categorized into three types, viz. osmotic tolerance, ionic tolerance, and tissue tolerance (Chaudhary and Choudhary, 2021).
Osmotic stress tolerance initiates a rapid response by diminishing cell expansion of root tips and young leaves and decreasing stomatal conductance to preserve water. It uses quick, long-distance (root to shoot) signaling pathways (Roy et al., 2014; Isayenkov and Maathuis, 2019), which essentially ignores the osmotic effects of NaCl, KCl, mannitol, and polyethylene glycol (Hassini et al., 2017; Darko et al., 2019; Prodjinoto et al., 2021; Gul et al., 2022). In osmotic tolerance, both organic solutes and inorganic ions are essential. These low molecular weight organic solutes, such as sugar and sugar derivatives including sucrose, polyols, and heterosides, GB and homarine (tertiary nitrogen compounds), amino acids such as proline, glutamate are commonly found in higher plants. Although it was thought that crop species had a wide range of osmotic tolerance, this was difficult to evaluate until recently. The measurements of growth parameters such as leaf growth and stomatal conductance methods are usually time-consuming and destructive. Digital images of plants allow measurements of the plant’s relative growth rate immediately after exposure to salinity and, hence, measure osmotic tolerance. Rice (Al-Tamimi et al., 2016), barley (Tilbrook et al., 2017), durum wheat (James et al., 2008; Sirault et al., 2009), bread wheat (Asif et al., 2018), and wild relatives of wheat, such as T. monococcum, have shown variations in osmotic tolerance based on relative plant growth rate.
The exclusion of ions, particularly Na+, from the shoot is a long-established mechanism for salinity tolerance in agricultural plants. This mechanism has received the most attention as it becomes easier to perform experimentation. Many crops, such as durum wheat (Forster, 2001; Munns and James, 2003), rice (Zhu et al., 2001; Lee et al., 2003), barley (Wei et al., 2003; Garthwaite et al., 2005) and Medicago (Sibole et al., 2003) have shown a substantial link between exclusion and tolerance of salt. In this mechanism, Na+ and Cl− enter the plant’s roots and are quickly transported to the shoot via transpiration stream. To avoid the buildup of these ions into the shoot system, roots exclude most of the Na+ and Cl− dissolved in the soil solution through which the concentration of salt in the shoot as a whole would never increase over that in soil, and the plant could survive indefinitely in saline soil. In this way, the concentration of Na+ and Cl− ions is relatively higher in shoot than in roots that, improve the plant’s salt tolerance. Lauchli et al. (2008) evaluated the concentration of sodium and other ions in different layers of wheat root. In addition to this, the SOS1 antiporter localized to the root epidermis (particularly at the root tip, where roots are undifferentiated) provides the first line of defense against sodium uptake (Assaha et al., 2017; Figure 2).
Tissue tolerance refers to a tissue’s ability to retain tissue function while accumulating high amounts of intracellular Na+ or Cl− ions (Munns et al., 2016; Negrāo et al., 2017). To avoid the detrimental effect of accumulated Na+ and Cl− ions, compartmentalization into vacuoles or photosynthetically non-active cells avoids the accumulation of Na+ and Cl− ions in the cytoplasm of plant cells where most important metabolic process occurs, i.e., tissue tolerance (Munns and Tester, 2008; Roy et al., 2014; Figure 2) and employing such mechanism will allow a plant to avoid toxicity. There is already a considerable amount of evidence across crop varieties in terms of the rates of accumulation of Na+ and Cl− in the shoots (Munns et al., 2016).
Osmoprotectants are low molecular weight hydrophilic organic compounds that involve a variety of roles connected to plant defense mechanisms under varying environmental conditions. Unlike inorganic compounds, these compounds are non-toxic at higher cellular concentrations (Nahar et al., 2016; Niazian et al., 2021). During stressful conditions, these osmoprotectants accumulates in plants like proline, ectoine, trehalose, polyols, fructan, and quaternary ammonium compounds (QACs) such as glycinebetaine, alanine betaine, proline betaine, choline-O-sulfate, hydroxyproline betaine, and pipecolate betaine (Singh et al., 2015). Transgenic plants overexpressing biosynthetic enzymes for osmoprotectants, such as mannitol, GB, D-ononitol, or sorbitol, have accumulated these compounds in levels too low to give protective benefits solely through osmotic mass action (Huang et al., 2000). The fundamental function of osmoprotectants accumulation in plants under salt stress is to maintain cell turgor pressure via osmoregulation, and protection of cellular components via reduction of ionic toxicity. Furthermore, by scavenging of hazardous ROS generated and preserving important antioxidative enzymes, these osmoprotective chemicals boost the antioxidative defense system in plants (Hasanuzzaman et al., 2014, 2019). In addition to this, osmolytes also function in the activation of defense-related genes under various stresses, which designates its prime importance in plants (Wani et al., 2018b). In the upcoming section, we discuss the role of important osmoprotectants under salinity stress in plants. Table 1 summarizes some of the relevant osmoprotectants in plants exposed to salinity stress.
Amino acids derived osmoprotectants such as proline, arginine, alanine, leucine, glycine, serine, valine and γ-aminobutyric acid (GABA; Suprasanna et al., 2014). These osmoprotectants accumulate under salinity stress conditions and decrease the osmotic potential of cells allowing water absorption. They also stabilize protein structures and membranes (Ashraf and Foolad, 2007); also act as nitrogen storing agents and ROS scavengers (Hayat et al., 2012). In stressed conditions, accumulation of mainly proline in relatively higher amounts as compared to other osmoprotectants is an indication of stress conditions. β-alanine being a non-proteinogenic amino acid is a stress response molecule involved in plant protection from biotic and abiotic stresses. Furthermore, it is converted into β-alanine betaine, an osmoprotective compound in some plant species (Parthasarathy et al., 2019).
Proline can be biosynthesized by two pathways: glutamate and ornithine pathway. Proline is produced from glutamatic acid via the intermediate Δ1-pyrroline-5-carboxylate (P5C), which is catalyzed by Δ1-pyrroline 5-carboxylate synthetase (P5CS) and Δ1-pyrroline5-carboxylate reductase (P5CR) in the glutamate pathway (Dar et al., 2016). However, in an alternate pathway, Proline is synthesized from ornithine (Orn), which is transaminated to Pyrroline-5- carboxylate (P5C) via Orn-δ-aminotransferase (δ-OAT; Verbruggen and Hermans, 2008). It has been claimed that proline buildup aids stress tolerance in various ways. It acts as a molecular chaperone, ensuring the integrity of proteins and enhancing enzyme activity (Ghosh et al., 2022). Recently, engineered plants have high expression of pyrroline-5-carboxylate reductase enzyme, leads to the accumulation of proline. Also, it has been observed that the antioxidant property of proline is helpful as ROS Scavenger (El-Badri et al., 2021). The importance of the Orn pathway in the development of rice seedlings has been explained through the constitutive expression of OsOAT genes. These genes are responsible for enhanced δ-OAT activity, improved antioxidant status, tolerance to drought, and osmotic stress (You et al., 2012). However, under salt stress, the preferential use of the Glu pathway over the Orn pathway is increased due to enhanced expression of P5CS activity. This suggests the pivotal role of Glu pathway in proline accumulation during osmotic adjustment (Zhen and Ma, 2009). Delauney et al. (1993) reported that P5CS mRNA levels were significantly up-regulated while OAT mRNA levels were down-regulated during salt stress in Vigna aconitifolia L. Later, it was confirmed by Lei et al. (2016) and Mansour and Ali (2017) through evaluation studies related to proline biosynthesis in salt stress. Interestingly, exogenous application of proline produced different results. For instance, Zea mays L. under foliar exposure of proline resulted in decreased P5CS activity and increased PDH activity under salt stress (de Freitas et al., 2018). Similar results were obtained in Sorghum bicolor under saline conditions (de Freitas et al., 2019). Seed primed with exogenous proline has been observed with decreased P5CS response while, on the other hand, PDH expression increased significantly in Triticum aestivum L. (Rady et al., 2019). These increased PDH level protect plants from proline toxicity (Deuschle et al., 2001). Over-expression of P5CS gene expression in Lepidium draba leads to proline accumulation and improved antioxidative responses under salt stress (Pakzad et al., 2021).
Quaternary ammonium compounds like GB, β-alanine betaine, proline-betaine, choline-O-sulfate etc. (Koyro et al., 2012) accumulate under salt stress conditions. Among these compounds, GB generally gets accumulated in a more considerable amount as compared to others, mainly accumulated in the chloroplast. GB helps to maintain intracellular osmotic equilibrium by regulating water flow into the cells (Ranganayakulu et al., 2013). More benefits are reflected in terms of the protection to thylakoids membrane, maintenance of photosynthetic activity and stomatal conductance, and photorespiration reduction etc. Transgenic approaches by overexpressing Betaine aldehyde dehydrogenase (BADH) enzyme provide better tolerance under stressful conditions (Sulpice et al., 2003).
Glycine betaine (GB) is zwitterionic, neutral at physiological pH and a quaternary ammonium compound that is N-methylated derivative of glycine (Ashraf and Foolad, 2007). GB is widely synthesized in chloroplasts of young tissues protecting the membrane enzymes and proteins under stressful environmental conditions. Because GB is not actively destroyed or metabolized in plant tissues, its concentration is determined by synthesis, transport, and dilution of plants (Annunziata et al., 2019). GB is biosynthesized as spatio-temporal under abiotic stress conditions (Annunziata et al., 2019). Usually, it is synthesized at modest levels and gently rises in young tissues /organs when abiotic stress occurs. Furthermore, unlike proline, the GB is swiftly re-translocated to younger leaves even if it is exogenously supplied to older sections. Thus, it can be inferred that GB cannot be metabolized and plays a critical role in the protection of young tissues. Under normal and stressful conditions, some plant species accumulate GB spontaneously (Chen and Murata, 2008) such as major cereals that are completely devoid of the potential to accumulate GB (Kurepin et al., 2015). An attempt to transfer GB biosynthetic genes in these plants via genetic engineering is considered a protective strategy for increasing salinity stress tolerance (Chen and Murata, 2011). Upregulation of the BADH gene has been reported as a potential biomarker in salt-stressed wheat plants (Lv et al., 2016). Similarly, Arabidopsis plants transformed with a novel BADH gene, ScBADH, resulted in the accumulation of SOD, proline and GB under salt stress (Wang et al., 2016). In another study, transgenic maize introduced with BADH gene from Artiplex micrantha L. reported higher GB content that is sufficient to impart tolerance against salt stress. Similarly, japonica and rice cultivars mediate up-regulated expression of the BADH1 gene in salt stress (Fitzgerald et al., 2008). Thus, it could be inferred that BADH act as a positive regulator in the treatment of salt stress via MAPK pathway in plants. Furthermore, the codA gene (choline oxidase) isolated from Arthrobacter globiformis can potentially alleviate phosphate deficiency in tomato plants through GB action (Li et al., 2019). In addition, GB regulates ion channels and transporters by maintaining Na+/K+ levels that are helpful in the transportation of phosphate under salt-stressed conditions (Haruta and Sussman, 2012; Wei et al., 2017; Yuan et al., 2017).
Plant osmolytes, besides enhancing osmotic homeostasis and stabilization, also act as chaperons in preserving the folding of proteins under stressful conditions and thus providing stability and function (Slama et al., 2015; Rabbani and Choi, 2018). In animals, TMAO is a quintessential osmolyte that act as a chaperone that retains the folding status of protein and protects against denaturants (Yancey, 2005; Strambini and Gonnelli, 2008; Jethva and Udgaonkar, 2018). Interestingly, a recent study demonstrated that the plant also synthesizes TMAO endogenously from FAOs and further illustrates that its level rises under abiotic stress conditions. Thus, TMAO enhances plant tolerance to freezing, drought, temperatures and high salt (Catala et al., 2021).
During salt stress, carbohydrates such as sugars (e.g., glucose, fructose, trehalose) and starch accumulate (Parida et al., 2004). The significant role played by these sugars involves osmoprotectant and scavenging of ROS for mitigating salt stress. It has also been reported that with an increase in the level of salt stress, the level of reducing sugars (sucrose, fructans) also increases significantly (Kerepesi and Galiba, 2000; Gangola and Ramadoss, 2018).
Trehalose (Tre) is a non-reducing sugar that is made up of two glucose residues (D-glucopyranose units) linked together by an extremely stable linkage (Ahluwalia, 2022). It’s a suitable solute or osmoprotectant even at high cellular concentrations because it’s non-reducing in nature and very soluble (Lunn et al., 2014). Plants produce Tre through the trehalose-6-phosphate synthase/phosphatase (OtsA–OtsB) pathway, which is dependent on two essential molecules: uridine-diphospho-glucose (UDP-Glc) and glucose-6-phosphate (Glc-6-P) in a two-reaction process (Paul et al., 2008; Kosar et al., 2018). Tre functions as a protective molecule for cellular, membrane, and proteinaceous structures due to this particular characteristic (López-Gómez and Lluch, 2012; Abdallah et al., 2016). Tre preserves membrane and protein structures under stress by forming an amorphous glass structure and influencing the surrounding polar phospholipid head groups or amino acids via hydrogen bonding (Einfalt et al., 2013; Poonam et al., 2016). The creation of this amorphous glassy structure protects biomolecules from the negative effects of abiotic stresses, particularly dehydration and aids in the recovery of their specific functions when normal non-stress environmental conditions prevail (Kosar et al., 2018). Transgenic plants have conferred enhanced tolerance to various abiotic stresses through the expression of Tre biosynthesis genes (Iordachescu and Imai, 2008). TPP (trehalose-6-phosphate phosphatase) and TSS (trehalose-6-phosphate synthase) genes are commonly present in the genomes of higher plants (Leyman et al., 2001). OsTPP1, a member of the TPP gene family, is involved in circumventing salt tolerance through transient up-regulated expression (Chao et al., 2005). For instance, the overexpressed OsTPP1 gene in rice plants has been found to tolerate salt stress by promoting the expression of stress-responsive genes (Ge et al., 2008). Similarly, Tre accumulation takes place in transgenic rice plants through regulated expression of fusion genes involving E. coli biosynthetic genes (OtsA and OtsB) along with TPS and TPP genes (Garg et al., 2002). These plants exhibited high tolerance levels to salt stress, further necessitating the importance of these genes in the design of transgenic plants. In Arabidopsis, AtTPPD is a chloroplast-localized enzyme that has been speculated to enhance tolerance toward high salinity (Krasensky et al., 2014). Higher accumulation of soluble sugars and starch levels achieved through over-expression of AtTPPD suggested its putative role in the metabolism of sugars under salt stress. The introduction of TPP gene from rice into maize plants resulted in a 20%–31% higher yield than non-transgenic controls (Nuccio et al., 2015).
Sugar alcohols such as pinitol, mannitol, myo-inositol and sorbitol show an influential role in mitigating stress conditions by adjusting osmotic equilibrium. These are also well-known as polyols. Myo-inositol and Pinitol have a cyclic structure, while mannitol and sorbitol have a linear structure. Their accumulation in plants is thought to serve a variety of functions, including osmotic adjustment, ROS regulation and molecular chaperons (Upadhyay et al., 2015; Bhattacharya and Kundu, 2020). Mannitol, a sugar alcohol, formed by the action of enzyme mannose-6-phosphate reductase on the mixture of glucose/fructose transforms into mannitol and gluconic acid. Mannitol aids in osmotic regulation and helps to remove oxygen radicals produced by stress (Kaya et al., 2013). Sorbitol is an osmoprotectant that is produced during photosynthesis (Wu et al., 2010). Zhou et al. (2003) utilized sorbitol-6-phosphate to produce sorbitol by dephosphorylating sorbitol-6-phosphatase. D-Ononitol, on the other hand, is a sugar alcohol that acts as an osmolyte, reducing water loss in plants during drought stress. The myo-inositol O-methyltransferase gene from Mesembryanthemum crystallinum was transferred into tobacco, which resulted in increased D-ononitol production and improved drought and salt resistance (Vinocur and Altman, 2005). Pinitol is generated by the methylation of myo-inositol and has found in many halophytic species. Ononitol epimerization also results in the formation of pinitol (Sengupta et al., 2008; Slama et al., 2015; Dumschott et al., 2019).
Mannitol is an acyclic polyol consisting of six carbon atoms (Slama et al., 2015). It is essential in quenching hydroxyl radicals (Gill and Tuteja, 2010a,b). Mannose-6-P isomerase (phosphomannose isomerase), mannose-6-phosphate reductase, and mannose-1-phosphate phosphatase are among the enzymes that start the production of mannitol in plants from Fructose-6-P (Loescher et al., 1992). As mannitol accumulates spontaneously in all plant species, adding it to non-mannitol accumulators can improve their resistance to adverse environmental conditions. Similarly, the incorporation of mannitol biosynthetic genes from accumulator species to non-accumulator species enhances their resistance to abiotic challenges, which is also a successful strategy for mitigating adverse impact of climate change. Eggplants engineered with mtlD gene have established tolerance against high NaCl stress (200 mM) (Prabhavathi et al., 2002). Populus tomentosa, a transgenic woody plant transformed with the mtlD gene encoding mannitol-1-phosphate dehydrogenase, has survived salt stress as a result of mannitol’s oxidative stress protection (Hu et al., 2005). This E. coli related mtlD gene encodes non-specific phosphatases that convert mannitol-1-phosphate to mannitol in transgenic plants. Further, mannitol-synthesizing transgenic peanut plants resulted in the accumulation of mannitol by over-expression of the mtlD gene from E. coli under salt stress (Bhauso et al., 2014). Moreover, the antioxidant genes might influence the expression of the mtlD gene in maintaining cellular homeostasis through detoxification of ROS species during salt stress (Patel et al., 2016). Recently, an attempt to the production of mannitol synthesis in Arabidopsis thaliana has been reported by expression of two biosynthetic genes, namely, mannitol-1-phosphate dehydrogenase and mannitol-1-phosphatase genes from brown algae Ectocarpus sp. strain Ec32, that results in the production of 42.3–52.7 nmol g−1 fresh weight of mannitol, sufficient to impart salinity stress tolerance (Rathor et al., 2020).
Inositol or more preciously myo-inositol is a sugar-like carbohydrate produced in many plants (Valluru and Van den Ende, 2011; Nisa et al., 2016). Being an osmoprotectant, its derivatives including pinitol, galactinol and ononitol, also perform diverse functions as osmoprotectant (Handa et al., 2018). It also regulates the synthesis of phytohormone such as auxin, phytic acid biosynthesis, and plant defense mechanism (Hazra et al., 2019). Inositol and other related molecules are suggested to prove salt tolerance in two ways: (1) protection of cellular structures from ROS, (2) maintaining cell turgor pressure inside the cell. The production of inositol is a two-step metabolic route that begins with the enzymatic conversion of d-glucose 6-P into myo-inositol-1-P catalyzed by myo-inositol-1-P synthase (Majumder et al., 1997), followed by dephosphorylation of myo-inositol-1-P resulting to form myo-inositol that further produces different inositol-containing compounds such as phospholipids (Dastidar et al., 2006). Introgression of salt tolerant MIPS (L-myo-inositol 1-phospahte synthase) protein encoded by PcINO1 gene of Porteresia coarctata resulted in inositol accumulation in tobacco plants (Majee et al., 2004). Transcriptome analysis studies revealed the potential of over-expression of the IbMIPS1 gene in transgenic sweet potato plants induced via salt stress (Zhai et al., 2016). Another MIPS gene, MdMIPS1 (myo-inositol-1-phosphate synthase1) overexpressed in transgenic apple plants, has promoted the biosynthesis of myo-inositol along with the accumulation of other osmoprotectants to alleviate salinity-induced osmotic stress (Hu et al., 2020).
Polyamines (PAs) are nitrogen-containing compounds having a low molecular weight that are present in cellular compartments. The most common PAs found in plants are spermidine (Spd), putrescine (Put), and spermine (Spm), classified as plant growth substances (Bano et al., 2020). Several other PAs such as cadaverine, homospermidine, canavalamine, and 1, 3-diamino propane are synthesized from amino acids. PAs generally occur in free or conjugated form with macromolecules or phenolic compounds. Put, Spd, and Spm are the most abundant PA that can be formed from arginine with the help of N-carbamoyl putrescine and agmatine (Urano et al., 2003). This putrescine is also converted into spermine and spermidine by synthase enzyme. In saline conditions, out of these polyamines, putrescine is mainly accumulated. They interact with the membrane surface and with the help of their polyanionic nature, stabilize the membrane structure (Gill and Tuteja, 2010a,b). PAs also increase the membrane fluidity and act as nitrogen reserve so that plants use them after stress conditions are over. They also support in maintaining cellular pH and ionic balance. The main functions of polyamines are osmotic adjustment, scavenging hydroxyl radicals via modulating enzyme activities and ammonia detoxification (Kuznetsov et al., 2007; Mustafavi et al., 2018; Chen et al., 2019). It has been suggested that Spd level is a salt tolerance indicator (Li and He, 2012). Exogenously application of Spd, improved plant development via increased reactive oxygen metabolism and photosynthesis under salinity stress (Meng et al., 2015; Baniasadi et al., 2018). Various transgenic approaches are used to improve stress tolerance by expressing polyamine biosynthesis enzymes such as arginine decarboxylase (ADC), ornithine decarboxylase (ODC), spermidine synthase (SPDS) and S-adenosyl methionine decarboxylase (SAMDC; Gill and Tuteja, 2010a,b). Regulation of PAs becomes important in salt-stressed plants after confirmation of poor performance of transgenic plants mutated with PA synthesis genes (Urano et al., 2004; Marco et al., 2015). Up-regulated expression of Calvin-cycle-related genes mediated by PAs is responsible for the mitigation of detrimental effects of salinity in Brassica napus L. (ElSayed et al., 2022). The key enzymes involved in the Calvin cycle consist of FBPase, PRKase, SBPase, and Rubisco, which are important for CO2 fixation (Raines, 2003). Limitation in Rubisco activity has been deduced as one of the major constraints in the down-regulation of photosynthesis in salinity stress (Lu et al., 2009). However, exogenous application of Spd has altered the expression of RbcL and RbcS genes, which subsequently influences the Rubisco structure and function (Spreitzer, 2003). Polyamine oxidases (PAOs) are catabolic enzymes of PAs that are flavin adenine dinucleotide- dependent (Wu et al., 2022). Different PAOs, such as AtPAOS and ZmPAO, have been identified in Arabidopsis and tobacco plants (Cona et al., 2006; Moschou et al., 2008). For instance, atpao5 in Arabidopsis stimulated the metabolic and transcriptional activities induced via salt stress (Zarza et al., 2017). Rice and wheat plants are identified with genes encoding proteins having PAO activity, suggesting an important function in salinity tolerance (Liu et al., 2014a,b; Xiong et al., 2017). Plant Polyamine oxidase (PAO) enzyme is responsible for H2O2 production during Put and Spd catabolism in plant tissues (Wang et al., 2019). Contrary to this, the OsPAO3 gene has exhibited a positive effect in rice plants through the enhanced accumulation of polyamines, which is sufficient to eliminate overproduction of H2O2 and exclude Na+ (Liu et al., 2022).
In terms of metabolic energy, plants use ions to balance water potential in tissues, unlike the use of carbohydrates or amino acids, which requires a significantly larger amount of energy. On the other hand, concentrations of ions should be maintained at an optimum level otherwise, it could be toxic to many cytosolic enzymes; therefore, compartmentalization of ions in the vacuoles becomes necessary (Binzel et al., 1998). As NaCl is the most common salt encountered by the plants during salinity stress, the salt overlay sensitive pathway is one of the main strategic approaches adopted by the plants. Plants perceive high Na+ concentration through downstream signaling of stress responses (Gong, 2021). The activation of Ca2+ channels always accompanies changes in ion concentrations and osmotic pressure. A putative osmosensor, OSCA1, is responsible for downstream Ca2+ signaling induced via osmotic stress (Yuan et al., 2014; Zhang et al., 2020). Similarly, the Arabidopsis mutant moca1 (monocation-induced Ca2+) delivered a hypersensitive response to salt stress. These are identified as Na+-gated Ca2+ channels involved in the enhancement of Ca2+ concentration. GIPs (glycosyl inositol phosphorylceramide) are Na+ sensors encoded by MOCA1 to increase the influx of Ca2+ ions (Jiang et al., 2019). Cell-wall integrity is maintained by plasma membrane-positioned receptors-like kinases, FERONIA (FER), under salt stress (Feng et al., 2018). FER, along with BAK1 phosphorylate CNGCS (cyclic nucleotide-gated ion channels) involved in Ca2+ signaling (Pan et al., 2019; Tian et al., 2019). Since salt stress triggers an overproduction of ROS, i.e., H2O2, a HPCA1 sensor located in the plasma membrane senses an increase in H2O2 concentration (Wu et al., 2020). In a salt overlay sensitive pathway, SOS1, SOS2 and SOS3 are three genes commonly involved (Wu et al., 1996). During salinity stress, elevated Na+ stimulates a rise in cytosolic Ca2+ concentration, which interacts with Ca2+ binding protein SOS3, and further interaction with Serine/threonine kinase protein SOS2 mediates the efflux of Na+ from the cells through Na+/H+ antiporter (SOS1; Shi et al., 2003; Kim et al., 2007). SOS3 and SOS2 kinase complex directly phosphorylates SOS1. Furthermore, SOS1, SOS2 and SOS3 work together to provide resistance to salinity stress (Mahajan and Tuteja, 2005; Park et al., 2016). Furthermore, another member of SOS3 family, Calcineurin B-like (CBL10), forms a complex with SOS2, which is thought to regulate both the exclusion of Na+ ion through SOS1 and the compartmentalization of Na+ ion into the vacuole by activating Na+/H+ antiporter (NHX). A schematic representation of salt overlay sensitive signaling has been depicted in Figure 2.
Plants perceive abiotic stress by activating signal-transduction pathways that allow them to adapt to even minor environmental changes. A wide array of complex transduction pathways are involved in sensing salt stress and generating a response during salinity stress. Pathways such as Salt overlay sensitive (SOS) pathway, phytohormone signaling, Calcium signaling, and Mitogen-Activated Protein Kinase (MAPK) network are involved in production and accumulation of osmolytes in regulating osmotic homeostasis during salinity stress (Roychoudhury and Banerjee, 2017). The biosynthesis and accumulation of osmolytes is one of the important events in the activation of stress signaling pathways in plants during exposure to abiotic stress such as salt, heavy metals, cold, drought etc., that enables the plants to adapt quickly to changing environmental conditions. The SOS pathway is reported to be regulated by MAP Kinase pathways and the level of osmoprotectant GB also affects this pathway (Ashraf and Foolad, 2007). Similarly, abscisic acid signaling regulates proline accumulation in response to salinity stress as well as drought (Verslues and Bray, 2005). In order to withstand constant stressful conditions, phytohormone mediating stress tolerance has been found to be crucial in plant response to salinity stress. Since phytohormones makes a great contribution is sensing salinity stress and adaption, nine plant hormones are commonly involved, which are divided into two groups: growth promoting hormones and stress response hormones (Yu et al., 2020). Auxins, gibberellins (GAs), cytokinins (CKs), brassinosteroids (BRs) and strigolactones (SLs) are growth-promoting hormones, while abscisic acid (ABA), ethylene, salicylic acid (SA) and jasmonic acid (JA) are stress response hormones. Among all, abscisic acid is most important in regulating salinity stress responses. Under stressful conditions, ABA accumulation takes place, which further activates kinase cascades and initiates stress defense reactions (Zhu, 2016). The Sucrose-nonfermenting-1-protein kinases 2 s (SnRK2s) are the main components in abscisic acid signaling pathways.
The plant responds to salinity stress by the accumulation of compatible solutes as already discussed above. In order to alleviate osmotic stress, osmolytes further modulate the enhanced expression of genes involved in synthesis of plant hormones such as abscisic acid (ABA), cytokinins (CK), salicylic acid (SA), jasmonic acid (JA), auxins, polyamines, brassinosteroids (BRs) and gibberellins (GRs) (Fahad et al., 2015; Rao et al., 2016). These hormones has diverse role in modulating the signaling pathways during the emergence of salinity stress (Ali et al., 2020). Since, osmolytes and phytohormones have been elucidated to have a significant role under demanding environmental conditions; it is therefore becoming crucial to understand the regulation of osmolytes and phytohormones and further correlate the roles of the same. The interaction of phytohormones with osmoprotectants has been explained in Figure 3.
Many physiological processes in plants are controlled by brassinosteroid signaling during salt stress. BRL3, a member of the brassinosteroid (BR) receptor family, regulates biosynthesis of many key osmoprotectants (Fabregas et al., 2018). Soluble osmolytes sugars maintain osmotic homeostasis and helps in ROS scavenging (Parvaiz and Satyawati, 2008). Proline acts as a molecular chaperone by scavenging free radicals and also stabilizes redox reactions inside cytosol (Kumar et al., 2013). Applications of proline in addition to brassinosteroid (24-epibrassinolide) to cultivars of Brassica juncea that grow in saline environment minimize harmful effects of salinity and improves yield (Wani et al., 2019). GB is a type of compatible osmoprotectant, which never changes at neutral pH; hence highly water soluble but in the hydration sphere of proteins, is insoluble. So these sugar osmolytes withhold water and preserve the protein structure (Kurepin et al., 2017). Artificial supply of brassinosteroids provides salt stress tolerance to plants by enhancing GB secretion as illustrated in Figure 3. Exogenous application of 24-epibrassinolide to tolerant and sensitive varieties of Pisum sativum plants was reported in enhancing the GB content and further helps in mitigation of salinity stress (Shahid et al., 2014). In another study, Cd stressed Pisum sativum plants when subjected to 24-epibrassinolide it causes an additional increase in the level of GB, providing a stress tolerance ability to plants (Ahmad et al., 2018). Treatment of Zea mays L. seedlings with HBL (28-homobrassionolide) and EBL (epibrassinolide) resulted in the modulation of antioxidative enzyme activities and compatible osmolytes that accounts for osmotic adjustment during salt stress (Rattan et al., 2020). Hence, brassinosteroid has stress defending capacity by increasing osmolyte.
Ethylene performs various physiological processes in the plant involving seed germination, plant development, senescence, fruit ripening, it has also been known to have a significant role in stress tolerance. It regulates abiotic stress by accumulating osmoprotectants (Iqbal et al., 2015). S-adenosyl methionine (SAM), the precursor for ethylene biosynthesis, is also a precursor for GB biosynthesis (Figure 3). Increasing GB and lower ethylene content (by inhibiting the activity of ACC synthase enzyme) in salinity stress enhances glutathione concentration (GSH) hence reducing oxidative stress (Khan et al., 2014). Proline along with ethylene gives salt tolerance capacity to Brassica juncea (Iqbal et al., 2015). Exogenous application of ethephon (ethylene source) with both doses of N and S on salt-stressed mustard plants increased the metabolism of proline, which is responsible for reducing oxidative stress (Jahan et al., 2021). The reason behind this fact is that increased nitrogen levels subsequently enhanced proline accumulation to provide salt tolerance (Iqbal et al., 2015). The biosynthesis of polyamines is also linked to ethylene production in terms of presence of precursor (S-adenosylmethionine, SAM; Petruzzelli et al., 2000). According to reports, ethylene and PAs are highly correlated in response to (ROS) production in the leaves of spring wheat seedlings under osmotic stress (Li et al., 2004). Increased PAs content, reduced ROS production, and ethylene synthesis were found in plants in response to stressful conditions.
Cytokinins are growth-promoting phytohormones and regulate plant growth and development (Pavlu et al., 2018). It promotes cell division in plant tissue culture and also regulates the cell cycle (Schaller et al., 2014). For osmolytes synthesis and accumulation in stress, ethylene cell signaling, MAPK plays a crucial function in plants (Shen et al., 2014). In abiotic stress, Cytokinin Oxidase/Dehydrogenase (CKX1) gene encodes for the enzyme that deactivates active cytokinins and increases the accumulation of GB content (Kathuria et al., 2009). Similarly, in Physcomitrella patens, overexpression of PpCKX1 lowers cytokinin levels and increases salt tolerance (Hyoung et al., 2019). These CKX-induced cytokinin-deficient plants are more valuable for researching the role of cytokinin than ipt mutants (Werner et al., 2003). The supply of cytokinin with NaCl gives signals that stimulate PEP carboxylase accumulation along with proline. Cytokinin activates PEP carboxylase that is responsible for increased proline levels in M. crystallinum (Thomas et al., 1992) and improved salinity stress tolerance (Figure 3). Cytokinins also regulate GB biosynthesis by modulating the GB pathway. In Solanum lycopersicum, the potential of Kinetin (Kn) and epibrassinolide (EML), either separately or in combination, was investigated under salinity stress. Results suggest that by enhancing the other physiological process, also leads to accumulation of GB through a crosstalk mechanism (Ahanger et al., 2020). Interestingly, several studies demonstrate that cytokinins and PAs govern various physiological and biochemical processes in plants, with a strong link between their levels, and operate as inter and intracellular messengers, regulating biotic and abiotic stresses (Galston, 1983; Wimalasekera and Scherer, 2009). However, the mechanism by which cytokinins influence the accumulation of PAs in plants is still unknown.
Abscisic acid (ABA) maintains osmotic adjustment in salt-stressed plants by regulating physiological processes for osmolyte regulation (Karimi and Ershadi, 2015). At a molecular level, ABA controls synthetic pathways of osmolytes by acting as signaling molecules (Pal et al., 2018). It also increases proline synthesis and accumulation to protect plant cells from damaging effects (Karimi and Ershadi, 2015). This increased proline accumulation is due to an increase in the transcription of genes encoding essential enzymes in proline biosynthesis. In Medicago truncatula, it was reported that proline accumulation occurs under water deficit stress conditions controlled by ABA levels (Planchet et al., 2014). ABA increases the biosynthesis route of GB, resulting in increased accumulation of this osmolyte in plant cells, which aids in abiotic stress resistance (Zhang et al., 2012). Under abiotic stress after adding ABA to plant synthesis of GB level enhanced due to increased activity of GB biosynthetic enzyme betaine-aldehyde dehydrogenase (BADH; Yang et al., 2015; Figure 3). By analyzing drought-stressed plants after fluridone treatment, these researchers were able to confirm the significance of ABA in betaine-aldehyde dehydrogenase upregulation. In PAs production, ABA regulates critical transcriptional processes. For instance, gene transcript of arginine decarboxylase 2 (ADC2), spermidine synthase1 (SPDS1), and spermine synthase (SPMS) were found to be up-regulated under drought conditions (Alcázar et al., 2006). Similar trends were also reported in arginine decarboxylase (ADC) expression patterns in response to salinity stress (Urano et al., 2004). In plants, such as Atriplex halimus, Oryza sativa, Phaseolus vulgaris and Zea mays, the impact of ABA levels in response to salinity stress has also been reported (Liu et al., 2005; Ben Hassine et al., 2009; Shevyakova et al., 2013). ABA priming has been used to provide tolerance to abiotic stress such as drought, cold, or salt stress (Savvides et al., 2016). In addition, one-time ABA priming in Vicia faba grown under 50 mM salinity has been found to alleviate salt stress through alteration in gene expression patterns over time, maintaining the ionic and osmotic balance and increasing photosynthesis and growth (Sagervanshi et al., 2021).
In abiotic stress, jasmonic acid (JA) includes several plant reactions such as gene regulation, synthesis of particular proteins, and secondary metabolism. JA regulates the detrimental effects of environmental stress through a cascade of plant responses (Choudhary and Agrawal, 2014a,b; Choudhary et al., 2021). For example, JA increased the levels of non-enzymatic antioxidants such as proline, which has been reported in several studies (Anjum et al., 2011; Shan et al., 2015). Under salinity stress, methyl jasmonate greatly mitigated the adverse effects of salinity on soybean growth (Yoon et al., 2009). Exogenous jasmonates (JAs) supplement enhances plant growth because of their effect on metabolites. Application of JAs increases the accumulation of constituents of Krebs cycle and finally gives resistance to stressed plants (Sharma et al., 2016). In Solanum lycopersicum, the application of JAs increases the production of GB and thus enhance plant growth and development under salinity stress conditions (Ahmad et al., 2017, 2018; Figure 3). Salinity-induced peroxidation have been observed under exogenous application of methyl jasmonate in Brassica napus due to enhanced soluble sugar levels in leaves (Ahmadi et al., 2018). Furthermore, JA signaling have also been implicated in the production of PAs in fruit ripening, insect-pathogen tolerance, low-temperature injuries. Due to their primary role in activating essential antioxidant enzymes, Spd levels increased in barley genotypes and protected membranes from peroxidation (Bandurska et al., 2003). Similarly, under any form of stress, sugar level rises, JA has been demonstrated to enhance sugar content in a variety of crop plants, including Triticum aestivum, Brassica napus, and Ipomea batata, as well as improve overall plant performance under abiotic conditions (El-Khallal, 2001; Harpreet et al., 2013).
Salicylic acid (SA), as a vital phytohormone, has multifaceted role in plant growth and developmental processes such as photosynthesis, mineral ion absorption and assimilation, antioxidant, and tolerance to stress (Choudhary and Agrawal, 2014a,b; Moravcová et al., 2018; Choudhary et al., 2021). The importance of SA in increasing resilience to environmental challenges has been well documented (Ahmad et al., 2011; Khan et al., 2015). During abiotic stress, the synthesis of osmolytes like GB, proline and sugar are influenced by SA (Misra and Misra, 2012; Jangra et al., 2022). The elevation in proline accumulation in salt-stress plants attributed to a stress tolerance mechanism (Misra and Saxena, 2009). In Rauvolfia serpentina, SA involves in enhancing proline production under salt stress and regulating cell turgor. It also mitigates salt stress in the seedling of Torreya grandis by accumulating proline. More proline concentration enhances the synthesis of stress protective proteins increasing stress tolerance (Li et al., 2014). SA enhances the accumulation of proline by regulating proline biosynthesis gene expression pattern. For instance, the exogenous application of SA mediates upregulation of important genes like P5CSA and P5CSB (encodes pyrroline-5-carboxylate synthase) and downregulation of PDH (encoding proline dehydrogenase; Lee et al., 2019). SA improves the overall growth of the plant by influencing the concentration of GB (Misra and Misra, 2012; Farhadi and Ghassemi-Golezani, 2020). On the other hand, by applying exogenous SA and its analogs, scientists have determined its imperative role in ameliorating salt stress on various plants (Gharbi et al., 2017; Shaki et al., 2018). Recently, in Vigna radiata plants, supply of 0.5 mM SA enhanced the accumulation of GB by more than 40% with respect to control and thus minimizing the adverse of salinity (Syeed et al., 2021; Figure 3). On application of exogenous SA to salinity stressed Zea mays, SA increases the level of soluble sugars in this plant (Khodary, 2004). On the other hand, SA, prevents the accumulation of PAs under salt stress conditions (Palma et al., 2013).
Salt stress in crop plants is a potential threat for agricultural crop productivity and ultimately to food security under the current and futuristic Climate-changing scenarios, worldwide. The mechanism of salinity tolerance in plants is complex involving osmotic stress and ion toxicity causing a major loss of yield and quality. The role of phytohormones in regulating responses to adverse effects of salinity has been well documented however the studies related to phytohormone mediating osmolyte biosynthesis require more research insight to get a clear mechanism of crops tolerance. Therefore, in the present article we have summarized the roles of phytohormones in regulating osmolytes and further enhance our knowledge by explaining the cross talk at the physiological level on exposure to salinity. Apart from this, still, molecular dissection studies are required to unravel the mechanism behind the modulation of osmolytes. Among all phytohormones, the role of cytokinin remains contradictory, which needs to be focused. Various transgenic approaches have been elucidated in salt-sensitive plants that successfully impart salinity tolerance in plants. However, the deployment of novel approaches involving phytohormone engineering metabolism could be considered a method of choice to produce salt-resilient crops with higher yields.
PS, SG, MS, BT, and SS: conceptualization, writing original draft, and writing—review and editing. NC: visualization and writing—review and editing. KC: conceptualization, visualization, supervision, and writing—review, and editing. All authors contributed to the article and approved the submitted version.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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PMC9553336 | Jilai Shi,Li Li | circKMT2E Protect Retina from Early Diabetic Retinopathy through SIRT1 Signaling Pathway via Sponging miR-204-5p | 30-09-2022 | Objective To explore the changes of circRNAs in the retina of diabetic patients without diabetic retinopathy (DR) to screen latent protective factor. Methods The sequencing data of the retina from three diabetic donors that possess no noticeable pathological feature of the retina at ultimate eye inspection and three healthy donative samples were involved in this study. Herein, we carried out bioinformatics analysis to disclose the expression pattern and characteristics of circRNAs on the basis of Gene Ontology as well as KEGG pathway analyses. Then, sequencing data were applied to infer the interaction between selected circRNAs and miR-204-5p. The potential miRNA response elements for the annotated circRNAs and their target gene were speculated using TargetScan as well as miRanda. Results RNA sequencing detected 28,978 alternative circRNAs. Thereinto, 1063 were expressed with significant difference. circKMT2E was upregulated more than two folds in alloxan-induced diabetic retinal tissues compared with normal retinal tissues, exhibiting an expression trend opposite to miR-204-5p. Bioinformatics analysis showed that circKMT2E have four seed sequences on hsa-miR-204-5p. Thus, circKMT2E was speculated to have function on the basis of sponging miR-204-5p in order to participate in the pathogenetic process of DR. Besides, miR-204-5p was speculated to be able to bind SIRT1, which can interact with its target proteins, and adjusts various cell functions including cellular inflammatory responses, proliferation, as well as apoptosis. Conclusion The upregulation of circKMT2E in the early stage of DR may be involved in its pathogenesis and may activate the SIRT1 signaling pathway to protect the retina by the sponge function to miR-204-5p. | circKMT2E Protect Retina from Early Diabetic Retinopathy through SIRT1 Signaling Pathway via Sponging miR-204-5p
To explore the changes of circRNAs in the retina of diabetic patients without diabetic retinopathy (DR) to screen latent protective factor.
The sequencing data of the retina from three diabetic donors that possess no noticeable pathological feature of the retina at ultimate eye inspection and three healthy donative samples were involved in this study. Herein, we carried out bioinformatics analysis to disclose the expression pattern and characteristics of circRNAs on the basis of Gene Ontology as well as KEGG pathway analyses. Then, sequencing data were applied to infer the interaction between selected circRNAs and miR-204-5p. The potential miRNA response elements for the annotated circRNAs and their target gene were speculated using TargetScan as well as miRanda.
RNA sequencing detected 28,978 alternative circRNAs. Thereinto, 1063 were expressed with significant difference. circKMT2E was upregulated more than two folds in alloxan-induced diabetic retinal tissues compared with normal retinal tissues, exhibiting an expression trend opposite to miR-204-5p. Bioinformatics analysis showed that circKMT2E have four seed sequences on hsa-miR-204-5p. Thus, circKMT2E was speculated to have function on the basis of sponging miR-204-5p in order to participate in the pathogenetic process of DR. Besides, miR-204-5p was speculated to be able to bind SIRT1, which can interact with its target proteins, and adjusts various cell functions including cellular inflammatory responses, proliferation, as well as apoptosis.
The upregulation of circKMT2E in the early stage of DR may be involved in its pathogenesis and may activate the SIRT1 signaling pathway to protect the retina by the sponge function to miR-204-5p.
Diabetes mellitus (DM) as a kind of noncommunicable chronic metabolic disease has prevailed worldwide [1, 2]. The complications of DM affect nearly every tissue of the human body; among all affected tissue, diabetic retinopathy (DR) refers to the frequent microvascular complication that accompanies DM. DR currently is deemed as one of the most common causes of blindness especially in working-aged people [2, 3]. Most studies organized for western populations have found a DR prevalence of more than 30% in individuals of similar age and duration of disease [1]. In the wake of the quick progress of high-throughput sequencing approaches, the function of circular RNAs (circRNAs), which take part in significant processes in diverse diseases, has been increasingly focused on [4–7]. circRNAs, dissimilar to linear RNAs, could take shape in a closed annulus structure presenting better steadiness as well as more specific peculiarities [8–11]. circRNAs, which are normally expressed according to the stage-specific manner as well as tissue-specific pattern, can participate in a series of physiological as well as pathological processes [12–14]. circRNAs contain microRNA (miRNA) response elements, by which circRNAs could adjust the expression of their target genes [15]. circRNAs, as a type of noncoding RNAs with modulatory capacity, can weaken the impact of miRNAs on the basis of silencing miRNA via sponge function, which is related to the posttranscriptional management of genes [15, 16]. On basis of the combination of bioinformatics analysis and basic experiment, the networks of gene modulatory among mRNAs, circRNAs, and miRNAs reported by a few previous studies have offered us more profound knowledge of the process of pathology and development for the retina. Therein, miR-204, a miRNA widely expressed in the lung, kidney, eye, mammary gland, skin, as well as melanocytes, executes significant functions during both functional maintenance and retinal development [17]. miR-204, a type of enriched miRNAs in eyes, owns the most prominent expression in the ocular tissue, such as the retina, lens, and ciliary body. Therefore, the extensive expression of miR-204 implies that it could adjust several vital cellular activities for ocular tissue [18–20]. Mao et al. found that the expression levels of miR-204-5p were significantly augmented in the retina from diabetic rats; besides, miR-204-5p additionally endorses the development process of DR on the basis of downregulating the microtubule-linked protein 1 light chain 3 to inhibit autophagy [21]. However, Yang et al. found that high glucose can downregulate miR-204 in ARPE19 cells [22]. During the initial progress of DR, vascular pathology, for instance, areas of vascular nonperfusion, microaneurysms, and decreased retinal blood flow, appears [3, 23]. Reduced blood flow of the retina, to some extent, manifests inchoately, not only in humans with DM but also in animal models with DM [23, 24]. Altered accommodation of inner retinal vascular is normally deemed as an accommodation forerunner to the occurrence of grievous vascular pathology in DR [25]. The controversial capacity of miR-204 in the pathogenetic process of DR may suggest that miR-204 participates in the early protective effect but terminal disablement. In this study, to ascertain the function of miR-204 in early diabetic retina as well as to reveal the early latent pathogenetic process of DR, in-depth sequencing data from postmortem human retinal tissue including three diabetic donors without DR and three healthy donors were enrolled. Mainly based on bioinformatics analysis, we found that the upregulation of circKMT2E in the early stage of diabetic retinal feedback may be involved in the pathogenesis of DM that activates the SIRT1 signaling pathway to protect the retina by the sponge function to miR-204-5p.
The in-depth transcriptomic data of both healthy and diabetic donors (with no evident visual injury or obvious pathology of the retina at the ultimate ocular inspection) were downloaded from the NCBI BioProject database with accession numbers PRJNA672929 and PRJEB10043 using “prefetch” order in Linux with the NCBI SRA Toolkit. After stratified sampling, three healthy subjects and three diabetic subjects were signed up in this investigation. The retinal samples from a postmortem human were acquired via the Iowa Lions Eye Bank (Coralville, Iowa, USA) in which samples were safeguarded within 6 h postmortem [26]. For the option of donors, Becker et al. [26] did not enlist donors who possess a confirmed medical history of Hepatitis B or C and HIV. Besides, donated ocular samples that were provided with neurodegenerative diseases were also excluded.
Sequencing reads with satisfying quality were matched to the online reference genome or transcriptome with the aid of STAR software (v2.5.1b) [27]. All identified circRNAs on the basis of DCC software were then annotated with the aid of the circBase database as well as Circ2Traits. circRNAs that possess significant differential appearance between the above-mentioned two groups were recognized based on t-test. The p value was corrected using the Benjamini and Hochberg method [28]. Fold change ≥ 2.0 as well as p value ≤ 0.05 were used for filtering circRNAs with differential expression.
Enrichment analyses on the basis of GO (http://www.geneontology.org) as well as KEGG (http://www.genome.jp/kegg) were implemented on the host genes of circRNAs with differential expression. GO is a methodic and organized database in order to depict both genes and its product. It not only covered molecular function but also revealed biological processes as well as cell component. With the help of the pathway analysis from KEGG, the signaling pathways that contain circRNAs as well as their biological functions can be inferred. The relevant p value was computed on the basis of Fisher's exact test, with a suggested threshold value at 0.05.
The abundance of circRNAs was calculated by Ballgown and computed by Fragments Per Kilobase of exon model per Million mapped fragments (FPKM). The threshold value of FPKM in each group was 0.5, which mean the circRNA would be deemed as expressing in this group if FPKM > 0.5. For the circRNA expression, Student's t-test was applied on the basis of GraphPad Prism 8.0 to compute the significance for differences.
The underlying miRNA reaction elements for the annotated circRNAs and target gene were predicted using custom-written software on the basis of both TargetScan and miRanda (Cloud-seq Biotech, Shanghai, China). CircPrimer1.2 (http://www.bioinf.com.cn/) and UCSC genome browser were used to annotate the arrangement of circKMT2E and its positions on parental genes, respectively. circMir1.0 software, on the basis of miRanda 2010 (http://www.microRNA.org/microRNA/getDownloads.do) and RNAhybrid-2.1.2 (https://bibiserv.cebitec.uni-bielefeld.de/rnahybrid/), was applied to annotate putative bundling situations of miR-204-5p on circKMT2E transcripts.
We identified the expression level of numerous circRNAs existing in retinal tissues on the basis of the samples donated from the diabetic subjects with no conspicuous visual damage or observable pathology at ultimate ocular detection as well as the retinal tissues from control healthy donors using the high-throughput sequencing. Under the sequencing, a total of 28,978 circRNAs were perceived in human retinal tissues, of which 10,970 circRNAs were observed for the first time as newfound circRNAs, while 18,008 circRNAs were already included in the circBase. (Figure 1(b)). According to the functional explanation in this study, which refers to the genome of these annotated circRNAs, 75.09% of these circRNAs were situated in protein-coding exons, while 0.69%, 1.24%, 6.11%, and 16.87% of them belonged to introns, intergenic, antisense, and sense overlapping regions, respectively (Figure 1(a)). The median size of exonic circRNAs was distributed at 556 nt (Figure 1(c)).
Differentially expressed circRNAs between above-mentioned two groups are exhibited on the basis of a scatter plot (Figure 2(a)). As shown in the volcano plot (p ≤ 0.05 as well as fold change ≥ 2.0), the number of 1063 circRNAs was disclosed to present significant differential expression between the above-mentioned two groups, of which 142 circRNAs were increased and 921 circRNAs were decreased in the DM group in contrast with the control group (Figure 2(b)). Among screened circRNAs with differential expression, 198 circRNAs were detected as novel circRNAs, and 865 circRNAs were already included in the circBase (Figure 2(c)). Besides, a total of 14 circRNAs were revealed to present more than 5-fold differential expression, including circMET, circITCH, circDNMT3B, circPAG1, circADAM9, circFTO, circ001209, circKMT2E, circCOL1A2, circ0001953, circHIPK3, circ0084043, circZNF532, and circEhmt1 (Figure 2(d)).
Among 1063 differentially expressed circRNAs, 1056 were derived from 805 unique genes, while the host genes of 7 circRNAs cannot be ascertained. 81.49% of the 805 genes generated only one circRNA, 11.80% of these genes generated two different circRNAs, and 6.71% of these genes generated more than two circRNAs (Figure 3(a)). In addition, these circRNAs differentially distributed throughout all of human chromosomes (Figures 3(b) and 3(c)).
In the process of bioinformatics analysis, to annotate the capacity of the target genes of all circRNAs that were differentially expressed, Gene Ontology analysis was applied. The top ten enriched functional entries of cellular components, biological processes, and molecular functions are shown in Figure 4. The most enriched biological process was intracellular metabolic, organelle organization as well as cell protein metabolic process (Figure 4(a)). Of the cellular components, the genes were closely related to the intracellular part, intracellular organelle, cytoplasm, and catalytic complex (Figure 4(b)). For the molecular functions, the largest proportion of top genes was referred to as binding and protein binding (Figure 4(c)). To further understand the correlation between these top genes and the pathogenesis of the early DR, we employed pathway analysis based on KEGG. The top ten strikingly enriched KEGG pathways are shown in Figure 4(d).
Due to the specific significance of miR-204 in the biology of the retina [17, 22], in this study, what circRNAs the predicted miRNA targets were identified on the basis of miRNA target prediction software—TargetScan. A total of 240 circRNAs were inferred to possess miR-204-5p response elements. By comparing these circRNAs with the differentially expressed genes in DM retina, our research team discovered that 206 (85.83%, 206/240) circRNAs were expressed with significant difference in the DM group, including 18 (7.5%, 18/240) upregulated and 188 (78.33%, 188/240) downregulated circRNAs (Figure 5(a)). That is, the alteration of the miR-204-5p-related circRNAs seems to be associated with the pathogenesis of DM. The predicted mutual combination of miRNA and circRNA was ranked according to pairing structure scores computed by miRanda algorithms, with the result revealing that hsa-miR-204-5p had a high score for upregulating circRNA circKMT2E and downregulating circRNA circPAG1. Hence, circKMT2E and circPAG1 were further used for the FPKM analysis. These two circRNAs both showed the same expression patterns with the sequencing results (Figure 5(b)). circKMT2E is upregulated significantly (FC = 4.449, p = 0.047), while circPAG1 is downregulated significantly (FC = 0.413, p = 0.021), in the DM group in contrast to the healthy control. Besides, circKMT2E, derived from Exon4-Exon15 of transcript KMT2E of Chromosome 7 (q22.3) (Figures 6(a) and 6(b)), was significantly upregulated in DM retina and exhibiting an opposite expression pattern to miR-204-5p. Bioinformatics prediction revealed that circKMT2E having four matched sequences could combine with miR-204-5p (Figures 6(c) and 6(d)). Further analysis of TargetScan revealed that miR-204-5p could combine with SIRT1. Briefly, circKMT2E seems can activate the SIRT1 signaling pathway by the sponge function to miR-204-5p.
circRNAs and miRNAs, which have dynamic and tissue- and cell-type-specific expression patterns, attract many researches to focus on their potential function, especially on their roles in the pathogenesis of diseases and the possibility to serve as fresh therapeutic targets for DR treatment [29]. Currently, most general studies show that circRNA can frequently act as the “sponges” of correlative miRNA and decrease the inhibiting effect of miRNAs toward target gene expression [28, 30]. In this study, compared with the control group, 14 different circRNAs in retinal samples from diabetic donors who do not possess conspicuous ocular impairment or obvious pathology of the retina at the last eye exam were revealed to present significant alteration and may participate in the early pathological feedback of DR. Some of this circRNAs have been confirmed by systematic research; for example, Zhu et al. [31] found that downregulation of circDMNT3B was conducive to the vascular dysfunction of DR on basis of targeting miR-20b-5p and BAMBI (a type 1 TGFβ receptor antagonist), and Shan et al. [32] found that circZNF532 adjusts diabetes-induced retinal pericyte deterioration as well as vascular dysfunction. It was reported by Qi et al. [21] as well as Yang et al. [22] that miR-204 may be significative in the pathogenesis of DR; however, both the capacity of miR-204 in the early phase of DR and its upstream mechanism are remain sealed. Thus, we launched this study by focusing on miR-204. Based on RNA-seq and FPKM analysis as well as a previous study of miR-204-5p, we further focused on circKMT2E, which is derived from the fourth to fifteenth exons of the annotated KMT2E gene region. circKMT2E was significantly upregulated in diabetic donors without DR and showed a conflicting expression pattern to miR-204-5p. Bioinformatics analysis further revealed that circKMT2E possesses four seed sequences that can be matched with hsa-miR-204-5p. Thus, we deduced that circKMT2E, to some extent, may be a potential controller in the early pathological process of diabetic retina and be associated with the miR-204-5p sponge function. Same as the previous study conducted by Lv et al. [33] that focused on islet β-cells, our bioinformatics analysis showed that human miR-204-5p can bind SIRT1. KMT2E is usually related to neurodevelopmental diseases, such as autism spectrum disorder, mental retardation, macrosomia, neurodevelopmental disorders, and epilepsy [34, 35]. Thus, since the retina contains abundant neuronal quantity and separate neuronal types [36], the circKMT2E seems to broadly benefit diabetic retina. Besides, miR-204 was also previously described to have various regulatory functions such as serving as an autophagy- and apoptosis-related controlling factor in various diseases. Besides, Yan et al. reported that the ischemia reperfusion injury of the spinal cord can be protected on the basis of the inhibition of miR-204, which is possible with the aid of promoting autophagy and antiapoptosis [37]. Jian et al. disclosed that miR-204 protected cardiomyocytes by adjusting autophagy through regulating LC3-II protein during hypoxia reoxygenation, and Cheng et al. [38] found that endogenous miR-204 can protect the kidney against chronic injury in hypertension and diabetes. That is, miR-204 can present diverse function for different tissues. In addition, Qi et al. found that miR-204-5p was presented as considerably augmented in the retina tissue collected from diabetic rats and further found that miR-204-5p can promote DR development [21]. However, Yang et al. found that high glucose can downregulate miR-204 in ARPE19 cells, which is a kind of human retinal pigment epithelial cell line [22]. It seems that miR-204-5p has both a stage- and a tissue-specific manner. SIRT1, a constituent of the silent information regulator 2 family, is a Class III histone deacetylase, which interplays with target proteins, and adjusts many cellular progresses, for example, cellular apoptosis, proliferation, and inflammatory responses [33, 39]. Generally, Sirt1 is mainly a histone deacetylase predominately localized in the nucleus, and its activity relies on cellular NAD availability [39]. Functionally, SIRT1 could deacetylate a series of histones, for example, H3 and H4, and more than 50 transcription factors and DNA repair proteins, for example, NF-κB [40]. It is expressed throughout the retina and is currently deemed as a guardian of the development of DR. In addition, the associative ability of miR-204-5p to SIRT1 was confirmed by a previous study [41]. Thus, in the early stage of diabetic retinal feedback, the upregulation of circKMT2E may be involved in the pathogenesis of DM on the basis of activating the SIRT1 signaling pathway to protect the retina by the sponge function to miR-204-5p, just as the augment of Sirt1 is also defensive against diverse ocular diseases such as cataract, retinal degeneration, as well as optic neuritis [39, 42]. Therefore, this study substantially appended to previous studies by finding that, in the early stage of diabetic retinal reaction, circKMT2E can seemingly activate the SIRT1 signaling pathway to defend the retina based on its sponge function to miR-204-5p. Besides, this study illustrated the controversial capacity of miR-204-5p in early diabetic retina. However, this study possesses several limitations. First, the direct binding abilities of circKMT2E and miR-204-5p were not substantiated by dual-luciferase reporter assay. Second, the transfection experiment of the retinal cell was not included in this study. Third, which factor makes miR-204-5p lose efficacy and induce DR was not ascertained. Although our study found that the differentially expressed circRNAs were involved in the pathologic process of DR and offered an innovative target for the therapy of DR, the exact mechanisms need further validation.
In the present study, our research team scrutinized the circRNAs that possess differential expression in the retina from diabetic donors who did not possess ocular damage or retinal alteration of pathology and preliminarily discussed the relation between miR-204-5p and related circRNAs during the early diabetic retina. The upregulation of circKMT2E in the early stage of diabetic retinal feedback may be involved in the pathogenesis of DM that activates the SIRT1 signaling pathway to protect retina by the sponge function to miR-204-5p. | true | true | true |
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PMC9553421 | Jiandong Sun,Yan Liu,Xiaoning Hao,Michel Baudry,Xiaoning Bi | Lack of UBE3A-Mediated Regulation of Synaptic SK2 Channels Contributes to Learning and Memory Impairment in the Female Mouse Model of Angelman Syndrome | 04-10-2022 | Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by severe developmental delay, motor impairment, language and cognition deficits, and often with increased seizure activity. AS is caused by deficiency of UBE3A, which is both an E3 ligase and a cofactor for transcriptional regulation. We previously showed that the small conductance potassium channel protein SK2 is a UBE3A substrate, and that increased synaptic SK2 levels contribute to impairments in synaptic plasticity and fear-conditioning memory, as inhibition of SK2 channels significantly improved both synaptic plasticity and fear memory in male AS mice. In the present study, we investigated UBE3a-mediated regulation of synaptic plasticity and fear-conditioning in female AS mice. Results from both western blot and immunofluorescence analyses showed that synaptic SK2 levels were significantly increased in hippocampus of female AS mice, as compared to wild-type (WT) littermates. Like in male AS mice, long-term potentiation (LTP) was significantly reduced while long-term depression (LTD) was enhanced at hippocampal CA3-CA1 synapses of female AS mice, as compared to female WT mice. Both alterations were significantly reduced by treatment with the SK2 inhibitor, apamin. The shunting effect of SK2 channels on NMDA receptor was significantly larger in female AS mice as compared to female WT mice. Female AS mice also showed impairment in both contextual and tone memory recall, and this impairment was significantly reduced by apamin treatment. Our results indicate that like male AS mice, female AS mice showed significant impairment in both synaptic plasticity and fear-conditioning memory due to increased levels of synaptic SK2 channels. Any therapeutic strategy to reduce SK2-mediated inhibition of NMDAR should be beneficial to both male and female patients. | Lack of UBE3A-Mediated Regulation of Synaptic SK2 Channels Contributes to Learning and Memory Impairment in the Female Mouse Model of Angelman Syndrome
Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by severe developmental delay, motor impairment, language and cognition deficits, and often with increased seizure activity. AS is caused by deficiency of UBE3A, which is both an E3 ligase and a cofactor for transcriptional regulation. We previously showed that the small conductance potassium channel protein SK2 is a UBE3A substrate, and that increased synaptic SK2 levels contribute to impairments in synaptic plasticity and fear-conditioning memory, as inhibition of SK2 channels significantly improved both synaptic plasticity and fear memory in male AS mice. In the present study, we investigated UBE3a-mediated regulation of synaptic plasticity and fear-conditioning in female AS mice. Results from both western blot and immunofluorescence analyses showed that synaptic SK2 levels were significantly increased in hippocampus of female AS mice, as compared to wild-type (WT) littermates. Like in male AS mice, long-term potentiation (LTP) was significantly reduced while long-term depression (LTD) was enhanced at hippocampal CA3-CA1 synapses of female AS mice, as compared to female WT mice. Both alterations were significantly reduced by treatment with the SK2 inhibitor, apamin. The shunting effect of SK2 channels on NMDA receptor was significantly larger in female AS mice as compared to female WT mice. Female AS mice also showed impairment in both contextual and tone memory recall, and this impairment was significantly reduced by apamin treatment. Our results indicate that like male AS mice, female AS mice showed significant impairment in both synaptic plasticity and fear-conditioning memory due to increased levels of synaptic SK2 channels. Any therapeutic strategy to reduce SK2-mediated inhibition of NMDAR should be beneficial to both male and female patients.
Angelman syndrome (AS) is a rare neurodevelopmental disorder with an incidence of approximately 1 in 10,000 to 20,000 live births [1, 2]. AS is characterized by severe developmental delay, language and cognition deficits, motor dysfunction [3, 4], unusually happy demeanor, and in many AS patients, seizure activity and autism-like behavior [3, 5, 6]. AS is caused by the deficient expression of the maternally inherited UBE3A gene in neurons [7–13], because neuronal expression of the paternal allele is silenced by a long noncoding antisense RNA transcript (UBE3A-ATS) [14–19]. Common maternal UBE3A deficiency has been attributed to four genetic etiologies [10, 20]: deletions of the maternal 15q11–q13 region (class I, approximately 70% of cases), paternal uniparental disomy of chromosome 15 (class II, 5%), imprinting defects (class III, 5%), and mutations in UBE3A (class IV, 10%). The UBE3A gene encodes an E ligase, UBE3A, also known as E6-associated protein (E6AP), the founding member of the HECT (homologous to E6AP carboxy terminus) domain-containing E3 ligase family [21]. Although there is no clear sex difference in the incidence of AS, emerging evidence indicates that the clinical presentation and pathogenesis of the disease may differ between male and female patients. For instance, a study of 24 AS patients (11 males and 13 females) reported that a larger proportion of male patients could walk independently, as compared to female patients [22]. A more recent study with 110 adolescents and adults with AS reported that obesity disproportionately affected female AS patients [23]. However, due to the rare prevalence of the disease, sex differences in cognitive function have not been widely studied. A few lines of transgenic mice with maternal UBE3a deficiency (AS mice) have been developed and tremendously contributed to our understanding of AS pathogenesis, as these mice exhibit several features of the human disease, including reduced brain size, abnormal electroencephalogram, learning and memory deficits, motor dysfunction [24–28], as well as impairment in long-term potentiation (LTP) of synaptic transmission [25, 29–33]. The influence of age and background strains on phenotypic syndromes and their severity across these mouse models has been well characterized [26, 34, 35]. While a few studies have also addressed sex differences [26, 34], their results are not conclusive, and clear sex differences were only observed in body weight [26], motor function, and nest building [34]. A more recent study specifically designed to compare male and female AS mice using several behavioral tests identified sex differences in some behavioral features, which were mainly due to differences in sensory perception [36]. We previously reported that the small conductance potassium channel protein SK2 is a UBE3a substrate, and that its synaptic levels are significantly increased in the hippocampus of male AS mice, an effect which contributes to LTP impairment [37, 38], and reduced memory recall in the fear-conditioning paradigm in these mice [37]. The critical roles of SK channels in LTP and in learning and memory in wild-type (WT) mice have been well documented in the literature [39–41]. We also showed that enhanced synaptic SK2 levels in AS mice imposed a stronger inhibition of NMDARs, resulting in impaired LTP and fear memory [37], which is in agreement with the literature [39, 40]. The degree of activation of NMDARs and the efficacy of their downstream signaling pathways have been shown to be different in adult male and female mice [42, 43]. Thus, the present studies were directed at evaluating synaptic SK2 levels, NMDAR regulation by SK2, and contextual and auditory fear memory in female AS mice.
We first determined synaptic SK2 expression in the hippocampus of female mice. Western blot analysis of hippocampal proteins from female AS mice showed that SK2 levels were significantly increased in crude synaptosomal fractions, as compared to those from female WT mice (P2; Figure 1), a finding similar to what we previously reported for male AS mice. UBE3a deficiency was confirmed by western blot analysis (Figure 1). Immunofluorescent staining of brain sections showed prominent SK2 staining in hippocampal CA1 region, especially in cell bodies and dendrites of pyramidal neurons (Figure 2(a)). High-magnification examination revealed that both the intensity and numbers of SK2-immunoreactive puncta distributed along apical dendrites of CA1 pyramidal neurons were significantly increased in female AS mice as compared to female WT mice (Figures 2(a) and 2(b)). SK2-immunopositive puncta were partially colocalized with PSD95-immunopositive puncta in both WT and AS mice. Quantitative analysis showed that the percentage of puncta dually stained with SK2 and PSD95 antibodies was significantly increased in female AS mice, as compared to female WT mice (Figure 2(b)). There was no significant difference in the overall number of PSD95-immunopositive puncta between female AS and WT mice (Figure 2(b)).
Previous experiments showed that theta-burst stimulation (TBS) in field CA1 of hippocampal slices from male AS mice elicited only a transient facilitation of synaptic transmission, which decayed rapidly, and LTP failed to consolidate [29, 37]. In female AS mice, the amplitude of TBS-induced LTP was also significantly reduced as compared to female WT mice (Figures 3(a) and 3(b)). We then determined whether SK2 activity contributed to reduce LTP by using a selective SK2 channel blocker, apamin. Following preincubation of hippocampal slices from female AS mice with apamin (20 nM), the magnitude of TBS-elicited LTP was significantly enhanced and almost reached the level seen in female WT mice (Figures 3(a) and 3(b)). We also analyzed long-term depression (LTD), another type of synaptic plasticity postulated to be involved in learning and memory, in hippocampal slices from female mice. Low-frequency stimulation (LFS; 1 Hz, 15 min) of the Schaffer collaterals in hippocampal slices from 2~3-month-old female WT mice induced a transient synaptic depression, and synaptic responses slowly returned to baseline levels (Figure 3(c)), a result consistent with the literature [37, 44]. However, the same protocol induced sustained LTD in slices from 2~3-month-old female AS mice, which is similar to what we previously reported in male AS mice [37]. Apamin (20 nM) pretreatment also significantly reduced LTD in female AS mice (Figures 3(c) and 3(d)). Both TBS-induced LTP and LFS-induced LTD at Schaffer collateral-CA1 synapses are known to be dependent on NMDARs, and previous studies have demonstrated that SK2-mediated hyperpolarization inhibits NMDAR-channel opening [37]. We previously showed that, in male AS mice, NMDAR-mediated synaptic responses (NfEPSPs) were significantly reduced as compared to male WT mice, and that apamin application normalized NfEPSPs in male AS mice. We thus performed similar experiments in female AS mice. NfEPSPs were isolated by bath application of Mg2+-free aCSF containing 6-cyano-7-nitroquinoxaline-2, 3-dione (CNQX; 10 μM) to block AMPA-receptor-mediated synaptic transmission. The NMDAR antagonist AP5 was used to verify that NfEPSPs were mediated by NMDARs under these conditions (Figures 3(e) and 3(f)). As previously observed in male AS mice, NfEPSP amplitudes were significantly lower in female AS mice as compared to female WT mice, and this decrease was reversed by apamin application (Figures 3(e) and 3(f)), suggesting that SK2 imposes a stronger inhibition of NMDAR in female AS mice than in female WT mice. Interestingly, apamin also significantly increased NfEPSP amplitude in female WT mice (Figures 3(e) and 3(f)), which is different from what we observed in male WT mice, where apamin did not affect NfEPSPs [37].
To determine whether apamin could also reverse impairment in hippocampus-dependent learning in female AS mice, we used the fear-conditioning paradigm. AS and WT female mice were injected with apamin (0.4 mg/kg, i.p.) 30 min before the training session, as previously reported [37, 41]. While there was no difference in freezing time in the preconditioning period, during training or before tone application in the testing period among all experimental groups (Figures 4(a) and 4(b)), female AS mice exhibited much less freezing time in both context-dependent (Figure 4(a)) and tone-dependent (Figure 4(b)) memory recall, as compared to WT female mice. Apamin treatment significantly enhanced memory recall in female AS mice (Figure 4). Under our experimental conditions (three conditioned stimuli (CS) paired with three unconditioned stimuli (US)), apamin treatment did not affect learning in female WT mice (Figure 4).
Abnormal synaptic plasticity, with reduced LTP and enhanced LTD, has been repeatedly reported in hippocampal slices from AS mice [25, 27–29]. We previously showed that UBE3A-mediated ubiquitination and subsequent degradation of synaptic SK2 channels play critical roles in synaptic plasticity and learning and memory. In male AS mice, the lack of UBE3A resulted in increased synaptic SK2 levels, which contributes to abnormal synaptic plasticity and impairment in learning and memory in the fear-conditioning paradigm [37]. These findings are consistent with the literature [39–41]. In the present study, we showed that female mice also exhibited reduced TBS-induced LTP and enhanced LFS-induced LTD, as well as impairment in both contextual and auditory fear memory. Abnormal synaptic plasticity and memory impairment were markedly improved by treatment with apamin, a SK2 channel blocker, suggesting that increased SK2 channel activity is involved in the pathophysiology of AS mice. Indeed, like in male AS mice, electrophysiological studies revealed that increased SK2 levels imposed a tonic inhibition of NMDARs, accounting for the abnormal synaptic plasticity observed in AS mice. Interestingly, there were also subtle differences between the present results and our previous results with male WT and AS mice. First, the reduction in LTP amplitude observed in female AS mice was not as severe as in male AS mice, as synaptic responses did not return to baseline at 40 min post TBS. Second, apamin, used at the same concentration in both studies, did not affect NMDAR fEPSP amplitude in hippocampal slices from male WT mice [37, 38], but significantly increased it in female WT mice. It has been previously reported that LTP in hippocampal CA1 region is more difficult to elicit in female than in male rodents [43, 45]. It is tempting to speculate that SK2 channels impose a stronger inhibition of NMDAR in female than in male WT mice, which could increase the threshold for LTP induction in CA1 region of female mice. To overcome the higher threshold for and facilitate LTP induction in females, an additional mechanism is therefore required. In a study with rodents, Wang et al. [43] showed that activation of ERα through locally produced estrogen is necessary for LTP induction in females but not in males. The molecular signaling downstream of estrogen receptors is not completely clear and may involve metabotropic NMDAR activity and activation of ERK, PKA, mTOR, and other signaling pathways [46, 47]. Of note, we previously showed that although one TBS failed to induce LTP, two TBS applied within 45 min were able to induce LTP in AS mice [37]. We subsequently showed that the effect of two TBS on LTP was due to PKA activation-induced SK2 endocytosis, as it was blocked by a PKA inhibitor and occluded with apamin [38]. Our recent study also showed that although TBS-induced LTP was impaired in male AS mice, high-frequency stimulation-(HFS-) induced LTP was not [48]. We also previously showed that, while TBS-induced LTP was ERK-dependent, HFS-induced LTP relied more on PKA activation [49]. These results imply that PKA activation facilitates LTP in male AS mice. Whether the same mechanism also holds true in female mice remains to be determined, but if it were, estrogen-mediated PKA activation could account for the differences in LTP between male and female AS mice. Along this line, to the best of our knowledge, sex differences in the expression and regulation of SK2 channels in the CNS remain unsettled, although sexual dimorphism has been reported in cardiac SK channel activation and regulation [50]. Additionally, SK2 channels have been shown to influence neuronal intrinsic plasticity through regulation of membrane excitability [51, 52]. Whether these additional roles of SK2 channels also contribute to alterations in synaptic plasticity and memory in AS mice, this remains to be determined. Despite these subtle differences in synaptic plasticity, female AS mice exhibited similar impairment in fear-conditioning learning as male AS mice. A recent study specifically designed to address sex differences in AS mice [36] showed that, during the training/conditioning phase, male AS mice exhibited enhanced responses, and female AS mice showed reduced responses to shocks when compared to their respective WT mice. Both male and female AS mice exhibited impairment in fear memory recall 24 h after conditioning, however, there was no sex difference. This study further showed that the sex differences observed in training responses were due to altered pain sensation, with male AS mice exhibiting enhanced pain sensation while female AS mice had reduced pain sensation, when compared to their respective WT mice. There was no difference between WT and AS when male and female mice were combined. This finding is different from a previous report showing that AS mice had enhanced nociception as compared to WT mice without sex differences. We did not observe any sex or genotype differences in freezing responses during training, which is consistent with previously published data [28, 32]. Additionally, experimental settings, animal age, and genetic background were different between our studies and Koyavski et al.'s report [36]. We used three tone-footshock pairings with a 2 s shock at 0.75 mA in 3-4 month-old 129 mice, while Koyavski et al.'s study used two 2 s foot-shocks at 0.5 mA in 5-8 month-old C57BL/6 J mice. Both age and strain backgrounds have been shown to influence the degree of behavioral deficiency of AS mice [26, 34]. Nevertheless, the general conclusion seems to be that there is no sex difference in fear-conditioning learning and that both male and female AS mice are equally impaired. Another recent study using combined males and females reported that, while AS mice performed poorly in spatial learning in the Morris water maze in massed training, learning was improved in a spaced training paradigm [53]; no sex difference was reported. It is therefore possible that downregulation of SK2 by PKA-mediated phosphorylation of SK2 induced by a second TBS or by HFS [48] contributes to the improved performance observed in spaced learning. Koyavski et al.'s [36] study also compared female and male WT and AS mice in the Morris water maze spatial learning paradigm. While they confirmed that AS mice performed much worse than WT mice, there were no significant sex differences within the genotype. There are a couple of shortcomings in the current study. First, the study used only female WT and AS mice and did not include a direct comparison of male and female mice. Second, we did not identify female mice in the different phases of the estrous cycle (proestrous, estrous, and metestrous). Nevertheless, our results support the general conclusion previously reported in the field that there is no clear sex difference in fear-conditioning learning in AS mice. These results support the observation that there are no marked sex differences regarding major cognitive functions in human AS subjects, while there might be subtle sex differences in other phenotypic traits. Along this line, it has been recently reported that a 6-week environmental enrichment period restored motor coordination, marble burying, and forced swim behavior in male AS mice to the level of WT mice, while having no effect on female AS mice [54]. Results from our study also provided a molecular mechanism for the observed benefit of spaced training as a potential therapeutic strategy for enhancing cognition in AS.
Animal experiments were conducted in accordance with the principles and procedures of the National Institutes of Health Guide for the Care and Use of Laboratory Animals. All protocols were approved by the Institutional Animal Care and Use Committee of Western University of Health Sciences. Original UBE3a mutant (AS) mice were obtained from The Jackson Laboratory, strain B6.129S7-UBE3atm1Alb/J (stock No. 016590), and a breeding colony was established, as previously described 30. In all experiments female AS mice aged between 2–4 months were used. Control mice were age-matched, female, and wild-type littermates. Multiple liters were used. Mice, housed in groups of two to three per cage, were maintained on a 12-h light/dark cycle with food and water ad libitum.
P2/S2 fractionation and western blots were performed according to published protocols [27]. Briefly, hippocampal tissue or slices were homogenized in ice-cold HEPES-buffered sucrose solution (0.32 M sucrose, 4 mM HEPES, pH 7.4) with protease inhibitors. Homogenates were centrifuged at 900 g for 10 min to remove large debris (P1). The supernatant (S1) was then centrifuged at 11,000 g for 20 min to obtain crude membrane (P2) and cytosolic (S2) fractions. P2 pellets were sonicated in RIPA buffer (10 mM Tris, pH 8, 140 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1% NP-40, 0.5% sodium deoxycholate, and 0.1% SDS). Protein concentrations were determined with a BCA protein assay kit (Pierce). The samples were separated by SDS-PAGE and transferred onto a PVDF membrane (Millipore). After blocking with 3% BSA for 1 h, membranes were incubated with specific antibodies (anti-SK2 antibody, Alomone Labs, 1 : 500; anti-b-actin, Sigma-Aldrich, A5441, 1 : 1000; anti-UBE3A, Bethyl, A300-351A, 1 : 2000) overnight at 4°C followed by incubation with secondary antibodies (IRDye secondary antibodies; Li-COR) for 2 h at room temperature. Antibody binding was detected with the Odyssey® family of imaging systems.
Deeply anesthetized animals were perfused, and brains were postfixed in 4% PFA overnight followed by sequential immersion in 15% and 30% sucrose for cryoprotection. Brains were then sectioned (20 μm) and stained as previously described [27]. Briefly, sections were blocked in 0.1 M PBS containing 5% goat serum and 0.3% Triton X-100, and then incubated in primary antibody mixture including rabbit anti-SK2 (1 : 200; APC-028, Alomone Labs) and mouse anti-PSD95 (1 : 200; MA1-045, Invitrogen) in 0.1 M PBS containing 1% BSA and 0.3% Triton X-100 overnight at 4°C. Sections were washed 3 times (10 min each) in PBS and incubated in appropriate Alexa Fluor–conjugated secondary antibodies (Invitrogen) for 2 h at room temperature. Images were acquired using a Zeiss LSM880 AiryScan confocal microscope.
Images for all groups were obtained using identical acquisition parameters and analyzed using Zen (Zeiss) and ImageJ (NIH) software. In all cases the experimenter was blind regarding the identity of the samples during acquisition and analysis. All immunostaining studies were performed in at least three independent experiments. The apical dendrites in the CA1 region of hippocampus were randomly selected for puncta analysis. Four-six mice were used for each genotype; 6-8 regions of interest and over 500 particles were analyzed for each mouse. The intensity and number of SK2- and PSD95-stained puncta were quantified. Colocalization analysis by Mander's coefficients was performed using Zen.
Acute hippocampal transversal slices (400 μm-thick) were prepared from adult female mice (2-4-month-old) as previously described [29], and recording was done in an interface recording chamber; slices were continuously perfused with oxygenated (95% O2/5% CO2) and preheated (33 ± 0.5°C) artificial cerebrospinal fluid (aCSF) (in mM) [110 NaCl, 5 KCl, 2.5 CaCl2, 1.5 MgSO4, 1.24 KH2PO4, 10 D-glucose, 27.4 NaHCO3]. Field EPSPs (fEPSPs) were elicited by stimulation of the Schaffer collateral pathway in CA1 stratum radiatum. Before each experiment, the input/output (I/O) relation was examined by varying the intensity of the stimulation. Long-term potentiation was induced using theta-burst stimulation (10 bursts at 5 Hz, each burst consisting of 4 pulses at 100 Hz). Long-term depression was induced by 900 pulses delivered at 1 Hz. Synaptic NMDA receptor-mediated responses were obtained using Mg2+-free aCSF containing 10 μM CNQX. Data were collected and digitized by Clampex; the slope of fEPSP was analyzed in most of the experiments, except for NMDA receptor-mediated responses in which the amplitude of fEPSP was analyzed.
AS mice and their WT littermates were randomly assigned to either drug or vehicle groups and blinded to the examiner. Mice were injected intraperitoneally (i.p.) with apamin (0.4 mg/kg body weight) 30 min before being placed in the fear-conditioning chamber (H10-11-M-TC, Coulbourn Instruments). The conditioning chamber was cleaned with 10% ethanol to provide a background odor. A ventilation fan provided a background noise at ∼55 dB. After a 2-min exploration period, three tone-footshock pairings separated by 1-min intervals were delivered. The 85 dB 2 kHz tone lasted 30 s and coterminated with a footshock of 0.75 mA and 2 s. Mice remained in the training chamber for another 30 s before being returned to home cages. Context test was performed one day after training in the original conditioning chamber with 5 min recording. On day three, animals were subjected to cue/tone test in a modified chamber with different texture and color, odor, background noise, and lighting. After 5 min recording, mice was exposed to a tone (85 dB, 2 kHz) for 1 min. Mouse behavior was recorded with the FreezeFrame software and data were analyzed using the FreezeView software (Coulbourn Instruments). Motionless bouts lasting more than 1 s were considered as freezing. The percent of time animal froze was calculated, and the group means with SEM and cumulative distribution of % freezing were analyzed.
All data are expressed as means ± SEM. To compute P values, unpaired Student's t-test, one-way and two-way ANOVA with Dunnett's or Tukey's post-test were used (GraphPad Prism 8), as indicated in the figure legends. The level of statistical significance was set at P < 0.05. | true | true | true |
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PMC9553513 | Yawei Liu,Litian Hu,Qinqiang Liu,Jing Ye,Jianping Zhang | miR-3651 Participates in the Growth Cycle of Hepatocellular Carcinoma Cells and Promotes the Malignant Metastasis via the PI3K/AKT/mTOR Signalling Pathway | 19-09-2022 | Objective Hepatocellular carcinoma (HCC) shows a growing incidence over the past few years, and clinical efforts are made to search for more effective novel diagnosis and therapy regimen for it to improve its outcome. This study probed into the association of miR-3651 with the PI3K/AKT/mTOR pathway to offer a more detailed reference to the follow-up exploration of novel diagnosis and therapy methods of HCC. Methods Totally, 83 patients with HCC treated in our hospital between Apr. 2017 and Aug. 2018, 100 patients with simple liver cirrhosis (LC), and 94 normal persons over the same time span were enrolled, and serum miR-3651 in them was quantified to understand the predictive and prognostic significance of miR-3651 for HCC. In addition, with purchased human HCC cell strains (HepG2), the impacts of miR-3651 on the invasion as well as proliferation of HepG2 were determined using the MTT and Transwell assays, and the PI3K/AKT/mTOR pathway and autophagy-associated proteins in HepG2 were quantified via WT. Results Serum miR-3651 was found to be higher in HCC patients than in LC patients and normal persons, and it presented a sensitivity and specificity of 57.14% and 94.00%, respectively, in forecasting the occurrence of HCC in LC patients. The decrease of miR-3651 in HCC patients after therapy was strongly bound up with patients' prognosis, and its increase implied an increased risk of death. In in vitro assays, HepG2 presented higher miR-3651 expression than HL-7702, and upregulated miR-3651 intensified the invasion and proliferation of HepG2, while silencing miR-3651 gave rise to opposite results. Additionally, the PI3K/Akt/mTOR pathway in HepG2 presented an obvious activation state, and its activation was further intensified after increase of miR-3651, while its activation was suppressed after silence of miR-3651. Moreover, HepG2 presented notably downregulated autophagy-associated proteins, and the increase of miR-3651 further suppressed the autophagy process, but with the intervention of BEZ235, the impacts of miR-3651 were completely reversed. Conclusion miR-3651 intensifies the growth and invasion of HCC cells through activating the PI3K/AKT/mTOR signalling pathway, which is probably a breakthrough in the future diagnosis and therapy of HCC. | miR-3651 Participates in the Growth Cycle of Hepatocellular Carcinoma Cells and Promotes the Malignant Metastasis via the PI3K/AKT/mTOR Signalling Pathway
Hepatocellular carcinoma (HCC) shows a growing incidence over the past few years, and clinical efforts are made to search for more effective novel diagnosis and therapy regimen for it to improve its outcome. This study probed into the association of miR-3651 with the PI3K/AKT/mTOR pathway to offer a more detailed reference to the follow-up exploration of novel diagnosis and therapy methods of HCC.
Totally, 83 patients with HCC treated in our hospital between Apr. 2017 and Aug. 2018, 100 patients with simple liver cirrhosis (LC), and 94 normal persons over the same time span were enrolled, and serum miR-3651 in them was quantified to understand the predictive and prognostic significance of miR-3651 for HCC. In addition, with purchased human HCC cell strains (HepG2), the impacts of miR-3651 on the invasion as well as proliferation of HepG2 were determined using the MTT and Transwell assays, and the PI3K/AKT/mTOR pathway and autophagy-associated proteins in HepG2 were quantified via WT.
Serum miR-3651 was found to be higher in HCC patients than in LC patients and normal persons, and it presented a sensitivity and specificity of 57.14% and 94.00%, respectively, in forecasting the occurrence of HCC in LC patients. The decrease of miR-3651 in HCC patients after therapy was strongly bound up with patients' prognosis, and its increase implied an increased risk of death. In in vitro assays, HepG2 presented higher miR-3651 expression than HL-7702, and upregulated miR-3651 intensified the invasion and proliferation of HepG2, while silencing miR-3651 gave rise to opposite results. Additionally, the PI3K/Akt/mTOR pathway in HepG2 presented an obvious activation state, and its activation was further intensified after increase of miR-3651, while its activation was suppressed after silence of miR-3651. Moreover, HepG2 presented notably downregulated autophagy-associated proteins, and the increase of miR-3651 further suppressed the autophagy process, but with the intervention of BEZ235, the impacts of miR-3651 were completely reversed.
miR-3651 intensifies the growth and invasion of HCC cells through activating the PI3K/AKT/mTOR signalling pathway, which is probably a breakthrough in the future diagnosis and therapy of HCC.
Hepatocellular carcinoma (HCC) is one frequently seen malignant tumor worldwide, with a mean annual increase of over 800,000 patients [1]. Its specific pathogenic mechanism is still under investigation, and its primary cause is clinically considered to be bound up with hepatitis B virus infection, liver cirrhosis (LC), fatty liver (and other liver diseases), heredity, and so on [2]. HCC is featured with no symptoms or with only slight atypical symptoms in the early stage usually, and it has reached the middle or late stage, accompanied by different degrees of intrahepatic and extrahepatic metastasis once it shows notable clinical symptoms [3, 4]. According to the survey, HCC in over 70% of HCC patients was in CNLC IIa or above, which is one primary cause for the unfavourable outcome of HCC patients [5]. At the current stage, many feasible clinical therapy approaches are available for HCC, but the 5-year survival rate of HCC patients is still only appropriate 30%-50% [6]. Over the past few years, as a focus of medical research, microRNA has been verified to be a part in many processes such as epigenetics, organ and tissue changes, cell differentiation, and disease development [7]. Among them, miR-3651, firstly discovered in 2014, was confirmed to be a potential biomarker of oral cancer [8, 9]. Over the past few years, Zhu et al. have discovered aberrant increase of miR-3651 in HCC cases through microarray analysis of microRNA [10]. Zhao et al. have confirmed the function of miR-3651 in promoting the growth and invasion of HCC cells through targeting PTEN [11]. The above can confirm the crucial role of miR-3651 in HCC. However, as mentioned by Zhao et al., PTEN primarily impacts cells via the PI3K/Akt/mTOR pathway. Therefore, the associated pathway probably also has a potential connection with miR-3651, but it still requires further confirmation. The association of PI3K/AKT/mTOR signal transduction with miR-3651 in HCC also deserves further analysis. Accordingly, this study probed into the association of miR-3651 with the PI3K/AKT/mTOR pathway to more deeply understand the potential significance of miR-3651 in HCC and offer a more detailed reference to the follow-up exploration of novel diagnosis and therapy methods of HCC.
Totally, 83 HCC patients treated in our hospital between April 2017 and August 2018 and 100 patients with simple LC and 94 normal persons over the same time span were enrolled. The study was performed under strict Declaration of Helsinki and with informed consent forms signed by each participant. The ethics committee of the Affiliated Drum Tower Hospital of Nanjing University Medical School (2019ky002) approved the study. HCC patients were not greatly different from LC patients and normal person in clinical baseline data including age and gender (P > 0.05, Table 1).
HCC patients: patients confirmed with HCC due to LC by biopsy in the Department of Pathology of our hospital, patients in early pathological stage, patients > 18 years old, and those with detailed medical records. Exclude patients with other comorbid benign or malignant tumors, patients with cardiovascular or cerebrovascular diseases or immunodeficiency diseases, patients with dysfunction of crucial organs, patients with poor compliance due to mental disease, pregnant patients, and lactating patients. LC patients: LC was diagnosed after liver biopsy, patients > 18 years old, and those with detailed medical records. The exclusion criteria are the same as above. Normal person: people who have routine physical examination in our hospital, the results of the physical examination are normal, no previous history of major disease, >18 years old, and those with detailed medical records. The exclusion criteria are the same as above.
Fasting venous blood (5 mL) acquired from each HCC patient at admission and 6 hours after radical operation were put in coagulation-promoting tubes and let to stand at indoor temperature, followed by centrifugation for acquiring serum that was saved in a refrigerator (-80°C) for later analysis. A 2-year follow-up was conducted to every HCC patient, on which the overall survival rate was recorded.
HepG2 and HL-7702 offered by ATCC were subjected to incubation (5% CO2, 37°C) in 10% fetal bovine serum-contained DMEM.
miR-3651 mimic sequence (3651-mimics group), inhibitor sequence (3651-inhibition group), and negative control (3651-NC group) were transfected into HepG2 under the instructions of Lipofectamine 2000 kit (Thermo Fisher Scientific, the States), followed by quantification of miR-3651 by PCR to verify the transfection success rate. Additionally, 5 mmol/L stock solution was prepared by dissolving the PI3K/AKT/mTOR signalling pathway inhibitor BEZ235 into sterile DMSO, followed by dilution to 0.1 μmol/L with blood-free medium, and the prepared solution was used to intervene with HCC (BEZ235 group). A control group was set by culturing normal HCC cells with the same amount of normal saline.
Total RNA acquired via the Trizol method was treated by reverse transcription via a reverse transcription kit (Thermo Fisher Scientific, the States) under kit instructions to acquire cDNA that was then treated by amplification reaction. Reaction conditions: GenScript Biotechnology Co., Ltd. designed and constructed the primer sequences (Table 2). Gene expression was calculated via the 2-ΔΔCt method (internal reference: U6).
Transfected cells were transferred to 96-well plates (4 × 105 cells/well), and each group was provided with 3 duplicate wells. Then, the plates were subjected to routine culture with culture medium, followed by liquid replacement and addition of 20 μL MTT solution (Abcam, China) at 24, 48, and 72 h for incubation. The supernatant was removed after 4 h continuous incubation, followed by addition of formazan solution (Abcam, China) to stop the reaction. A microplate reader was adopted for determining the optical density (OD) at 490 nm, on which cell growth curves were drawn.
Diluted Matrigel along with resuspended cells was placed in the upper compartment of the Transwell chamber and 10% serum-contained DMEM to the lower compartment. After 24 h, the membrane-penetrating cells were treated by immobilization and staining and then counted under the microscope.
Cell lysate was adopted for lysing cells that were then treated by centrifugation, and then, BCA (Beyotime Biotechnology, China) was adopted for quantification of the total protein. Total protein (50 μg) was treated by SDS-PAGE and placed on a membrane, followed by immersion in defatted milk, addition of I antibody, and overnight incubation (4°C). II antibody was put into it after TBST washing the next day, and ECL was developed after 1 h incubation. The protein expression was calculated (internal reference: GAPDH). Antibodies were all offered by Thermo Fisher Scientific (the States).
This study adopted SPSS 22.0 for statistical analyses. Intergroup comparison of counting data [n (%)] was conducted via the chi-square test, and intergroup comparison of measurement data (−χ ± s) was performed via the t-test, one-way ANOVA, and post hoc LSD test. ROC curves were drawn for analyzing the predictive value, and the Kaplan-Meier method was adopted for calculating the survival rate and the log-rank test for comparing it. P < 0.05 implies a notable difference.
According to PCR assay results, HCC patients showed higher serum miR-3651 than LC patients and normal person (3.53 ± 0.59vs.2.87 ± 0.49vs.1.78 ± 0.44, P < 0.05, Figure 1(a)). According to ROC curve-based analysis, under the area under the curve (AUC) of 0.8219, serum miR-3651 > 3.41 had a sensitivity and specificity of 59.04% and 92.00%, respectively, in forecasting the occurrence of HCC in LC patients (P < 0.05, Figure 1(b)).
After therapy, HCC patients presented serum miR-3651 of 3.00 ± 0.48, notably lower than that at admission (P < 0.05, Figure 2(a)). In terms of follow-up, 78 HCC patients were successfully tracked, of which 17 patients died, so the overall 2-year mortality was 21.79%. Patients who died eventually presented serum miR-3651 of 3.41 ± 0.32 after therapy, notably higher than that of those who survived finally after therapy (P < 0.05, Figure 2(b)). According to ROC curve-based analysis, under the AUC of 0.7701, serum miR-3651 > 3.21 had a sensitivity and a specificity of 94.12% and 70.49%, respectively, in forecasting the death of HCC patients within 2 years (P < 0.05, Figure 2(c)). Finally, based on the cutoff value, the patients were grouped into high-expression groups (miR-3651 > 3.12 after therapy for the former, n = 33) and low-expression groups (miR-3651 ≤ 3.12 after therapy for the former, n = 45). According to comparison of the two groups' survival curves, the high-expression group presented a notably higher mortality than the other (P < 0.05, Figure 2(d)).
In in vitro assays, HepG2 showed higher miR-3651 expression than HL-7702 (2.33 ± 0.12vs.1.21 ± 0.14, P < 0.05, Figure 3(a)). After transfection, the 3651-mimic group presented the highest miR-3651 expression (2.83 ± 0.57), and the 3651-inhibition group presented lower miR-3651 expression than the 3651-NC group (1.55 ± 0.07vs.2.20 ± 0.08, P < 0.05, Figure 3(b)), which verified the success of transfection. According to the results of MTT assay, the largest 72 h OD was found in the 3651-mimics group, followed by the 3651-NC group and the 3651-inhibition group (1.00 ± 0.04 > 0.63 ± 0.05 > 0.43 ± 0.02, all P < 0.05, Figure 3(c)). According to the Transwell assay (Figure 3(d)), the largest number of invasive cells was found in the 3651-mimics group, followed by the 3651-NC group and the 3651-inhibition group (187.67 ± 13.87 > 78.33 ± 13.65 > 46.00 ± 6.56, all P < 0.05, Figure 3(e)).
PI3K/AKT/mTOR pathway-associated proteins in HepG2 and HL-7702 were quantified (Figure 4(a)). As a result, HepG2 presented expression of P-PI3K, P-Akt, and P-mTOR proteins of 0.64 ± 0.04, 0.65 ± 0.06, and 0.63 ± 0.04, respectively, higher than that in HL-7702 (P < 0.05, Figure 4(b)). Subsequently, the expression of PI3K/AKT/mTOR pathway-related proteins in HepG2 after transfection was detected (Figure 4(c)); the 3651 mimics presented p-PI3K protein expression of 1.01 ± 0.03, p-AKT expression of 1.04 ± 0.07, and p-mTOR expression of 0.97 ± 0.09, which were all the highest among the three groups. The 3651-inhibition group presented p-PI3K protein expression of 0.24 ± 0.02, p-AKT expression of 0.27 ± 0.03, and p-mTOR expression of 0.25 ± 0.04, lower than those in the 3651-NC group (P < 0.05, Figure 4(d)).
The BEZ235 group showed a notably lower 72 h OD than the control group (0.43 ± 0.02vs.0.62 ± 0.03, P < 0.05, Figure 5(a)). The Transwell assay results (Figure 5(b)) revealed notably less invasive cells in the BEZ235 group than in the control group (42.00 ± 3.00vs.86.67 ± 7.37, P < 0.05, Figure 5(c)).
The PCR assay revealed lower LC3-II mRNA and Beclin-1 mRNA expression in HepG2 than in HL-7702 (0.81 ± 0.06vs.1.94 ± 0.09; 0.88 ± 0.04vs.2.10 ± 0.04; P < 0.05, Figure 6(a)). According to the Western blot results (Figure 6(b)), the expression of LC3-II and Beclin-1 proteins in HepG2 was 0.55 ± 0.03 and 0.58 ± 0.04, respectively, also notably lower than that in HL-7702 (P < 0.05, Figure 6(c)). Afterwards, HepG2 treated with miR-3651 mimics was cultured with BEZ235, and separate 3651-mimics group and 3651-NC group were set up. First, through Transwell experiments (Figure 6(d)), we found that the number of invasive cells in the 3651-mimics+BEZ235 group was 67.67 ± 3.51, and there was no difference in the number of invasive cells in the 3651-NC group (72.00 ± 6.08), which was lower than that of the 3651-mimics group (P < 0.05, Figure 6(e)). According to the results, the 3651-mimics+BEZ235 group was not greatly different from the 3651-NC group in LC3-II and Beclin-1 mRNA levels (0.82 ± 0.03vs.0.85 ± 0.04; 0.85 ± 0.04vs.0.89 ± 0.03), but showed notably lower levels of them than the 3651-mimics group (P < 0.05, Figure 6(f)). Similarly, according to the Western blot results (Figure 6(g)), the 3651-mimics+BEZ235 group was also not greatly different from the 3651-NC group in LC3-II and Beclin-1 protein levels (0.59 ± 0.05vs.0.59 ± 0.05; 0.58 ± 0.03vs.0.57 ± 0.03), but showed notably lower levels of them than the 3651-mimic group (P < 0.05, Figure 6(h)).
HCC is a high-risk disease that endangers the lives of millions of patients worldwide. Finding a more effective and accurate diagnosis and therapy means as soon as possible is the only solution to ensure the health of patients with it [12]. Over the past few years, the application of microRNA in tumor diseases has captured attention, which has laid a promising direction for the future molecular gene targeted therapy [13]. This study more deeply probed into the association of miR-3651 with HCC, which could offer more accurate and effective reference and guidance for the follow-up research. Prior research confirmed aberrant miR-3651 expression in HCC cases, and our study also verified it. In our study, HCC patients presented notably higher serum miR-3651 expression than LC patients, suggesting high miR-3651 expression in HCC cases, which was in agreement with the prior research results [14, 15]. Our study selected patients with simple LC as controls for ROC analysis, because LC has an enormous risk of pathological changes as the most crucial primary cause of HCC [16]. HCC is occult at the early stage, and a reliable means to monitor the possibility of HCC in LC patients is still under investigation [17]. In our study, miR-3651 demonstrated an excellent performance in forecasting the development of LC into HCC, which once again verified the crucial reference significance of miR-3651 for the future assessment of HCC. In addition, HCC patients showed a notable decrease in miR-3651 level after therapy, which verified a strong association of miR-3651 with the changes of HCC. Moreover, generally higher miR-3651 expression was found in patients who died after therapy, and miR-3651 presented a sensitivity of 85.71% in forecasting the death of patients, which indicated the great potential of miR-3651 to be an indicator for evaluating the prognosis of HCC. Barzago et al. have pointed out the potential of miR-3651 to be a prognostic marker of infection-related inflammatory diseases, which once again emphasized the crucial association of miR-3651 with tumor diseases [18]. According to the survival curves in our study, the increase of miR-3651 directly indicated the increased risk of death of HCC patients, which supported our above results and viewpoints. To sum up, we have preliminarily discussed the clinical application of miR-3651 in HCC. Prior research has verified the ability of miR-3651 to speed up the proliferation and invasion of HCC cells and the possible association of the pathway with PTEN. Accordingly, for the purpose of verifying the mechanism of miR-3651 in HCC, we also carried out in vitro assays. First of all, similar to the above results, the in vitro assays also revealed an increase of miR-3651 expression in HepG2. Similar to prior research results, the biological behaviour assays revealed that increasing miR-3651 could intensify the proliferation and invasion of HepG2, while silencing it could give rise to opposite results [19]. The repeated confirmation with various HCC cell strains showed the ability of overexpressed miR-3651 to enhance the activation of HCC cells. As we mentioned above, the PI3K/Akt/mTOR signalling pathway has been confirmed to be implicated in the development of many tumor diseases as the main downstream transduction pathway of PTEN [20]. Our study also found the obvious activation state of the PI3K/Akt/mTOR pathway in HepG2, which confirmed the association of PI3K/Akt/mTOR pathway with HCC. Moreover, the activation state of the pathway was further enhanced after the increase of miR-3651, while the activation state was suppressed after silence of miR-3651, suggesting the regulatory role of miR-3651 to the PI3K/Akt/mTOR pathway in HCC. Under the intervention of BEZ235, the growth and invasion activities of HepG2 cells were greatly suppressed, which indicated that suppression of the PI3K/Akt/mTOR pathway could impact the viability of HCC cells, which was consistent with prior research results [21]. In addition, the PI3K/Akt/mTOR pathway showed a strong correlation with the autophagy ability of tumor cells in our study, so we also detected the autophagy-associated proteins in HepG2 and found notable decrease of autophagy ability in HepG2. The increase of miR-3651 further weakened the autophagy process, and the impact of miR-3651 was completely reversed with the intervention of BEZ235. It follows from the above results that miR-3651 can regulate the viability and autophagy of HCC cells through mediating the PI3K/Akt/mTOR pathway, which lays a foundation for the possible targeted therapy of HCC in the future. We believe that the application of miR-3651 can not only serve as a reference for the diagnosis of HCC but also become a new treatment plan for HCC, thus providing a more reliable guarantee for the life safety of patients. Of course, we still need to confirm the effect of miR-3651 on living tumors through animal experiments. However, due to the limited experimental conditions, we cannot carry out animal experiments in this experiment, and we will add this in the future. In addition, we could further confirm the effect of miR-3651 on HCC cells through experiments such as cell cloning, scratching, and flow cytometry. However, due to limited funding, we also did not conduct these experiments. Finally, the effect of miR-3651 on HCC cells may be not only through the PI3K/AKT/mTOR signalling pathway, which also requires us to conduct more studies for analysis. In the future, we need to include more patient data to confirm the exact clinical significance of miR-3651 in HCC and conduct a more in-depth and comprehensive analysis of the action pathway of miR-3651 in HCC to obtain more effective results for clinical reference. To sum up, miR-3651 intensifies the growth and invasion of HCC cells through activating the PI3K/AKT/mTOR signalling pathway, which is probably a breakthrough in the future diagnosis and therapy of HCC, so it is worthy of further explorations. | true | true | true |
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PMC9553516 | Feng Xu,Na Xiong,Yuhong Yuan,Jun Liu | Prognostic Value of UBE2T and Its Correlation with Immune Infiltrates in Lung Adenocarcinoma | 20-09-2022 | Non-small cell lung cancer has a subtype with a high morbidity and mortality rate called lung adenocarcinoma (LUAD). It is critical to locate reliable prognostic biomarkers for LUAD at this time. Ubiquitin-conjugating enzyme E2T (UBE2T) has been found in numerous malignancies; however, its expression level and potential functions in LUAD are not completely understood at this time. A differentially expressed gene (DEG) screening method was used to identify genes that were expressed differently in 516 samples from LUAD and 59 samples from TCGA datasets. Clinicopathological markers were correlated with UBE2T expression. Using the Kaplan–Meier plotter database, UBE2T was evaluated for its prognostic value in the context of LUAD. In order to examine the importance of independent prognostic factors, both univariable and multivariable Cox regression models were applied. TIMER and CIBERSORT were utilized in order to investigate the connection that exists between UBE2T expression and tumor-infiltrating immune cells. This study collected 578 DEGs in total, as follows: 171 genes were significantly increased, while 408 genes were significantly decreased. We identified 9 survival-related DEGs in LUAD, including ASF1B, CA9, CCNB2, CCNE1, RRM2, SAPCD2, TCN1, TPX2, and UBE2T. Our attention focused on UBE2T, which was highly expressed in LUAD. A correlation was also found between high UBE2T expression and gender, age, advanced clinical stage, and decreased overall survival. In addition, multivariate analysis demonstrated UBE2T expression to be a significant independent diagnostic factor for patients suffering from LUAD. UBE2T was positively correlated with resting T cell CD4+ memory, myeloid dendritic cell resting, mast cell activated, macrophage M2, and B cell plasma, whereas it was negatively correlated with resting T cell CD4+ memory, MDC resting, MDC activated, macrophage M2, and B cell plasma. Overall, high expression levels of UBE2T correlated with poor overall survival in patients with LUAD, and UBE2T was an independent predictor involved in immune infiltration of LUAD. These findings offer fresh perspectives that contribute to our comprehension of the evolution of LUAD. | Prognostic Value of UBE2T and Its Correlation with Immune Infiltrates in Lung Adenocarcinoma
Non-small cell lung cancer has a subtype with a high morbidity and mortality rate called lung adenocarcinoma (LUAD). It is critical to locate reliable prognostic biomarkers for LUAD at this time. Ubiquitin-conjugating enzyme E2T (UBE2T) has been found in numerous malignancies; however, its expression level and potential functions in LUAD are not completely understood at this time. A differentially expressed gene (DEG) screening method was used to identify genes that were expressed differently in 516 samples from LUAD and 59 samples from TCGA datasets. Clinicopathological markers were correlated with UBE2T expression. Using the Kaplan–Meier plotter database, UBE2T was evaluated for its prognostic value in the context of LUAD. In order to examine the importance of independent prognostic factors, both univariable and multivariable Cox regression models were applied. TIMER and CIBERSORT were utilized in order to investigate the connection that exists between UBE2T expression and tumor-infiltrating immune cells. This study collected 578 DEGs in total, as follows: 171 genes were significantly increased, while 408 genes were significantly decreased. We identified 9 survival-related DEGs in LUAD, including ASF1B, CA9, CCNB2, CCNE1, RRM2, SAPCD2, TCN1, TPX2, and UBE2T. Our attention focused on UBE2T, which was highly expressed in LUAD. A correlation was also found between high UBE2T expression and gender, age, advanced clinical stage, and decreased overall survival. In addition, multivariate analysis demonstrated UBE2T expression to be a significant independent diagnostic factor for patients suffering from LUAD. UBE2T was positively correlated with resting T cell CD4+ memory, myeloid dendritic cell resting, mast cell activated, macrophage M2, and B cell plasma, whereas it was negatively correlated with resting T cell CD4+ memory, MDC resting, MDC activated, macrophage M2, and B cell plasma. Overall, high expression levels of UBE2T correlated with poor overall survival in patients with LUAD, and UBE2T was an independent predictor involved in immune infiltration of LUAD. These findings offer fresh perspectives that contribute to our comprehension of the evolution of LUAD.
Lung cancer is considered to be one of the most common malignant tumors all over the world [1, 2]. It has virtually reached the position of being the first major contributor to death among those living in China's urban areas [3, 4]. The majority of lung malignancies, approximately 70–80 percent, are diagnosed as non-small cell lung cancer (NSCLC) [5, 6]. Lung adenocarcinoma is a main subtype of NSCLC and is often diagnosed at an advanced disease stage [7]. Early surgical resection is currently the recommended course of treatment for patients diagnosed with LUAD. Following the completion of any necessary surgical procedures, the patient will undergo further chemotherapy to further increase their chances of survival [8, 9]. However, half of all people who have LUAD will suffer a relapse at some point and will ultimately pass away as a result of the disease's return. A reliable method of predicting patient survival status is needed in order to facilitate the diagnosis of early-stage LUAD and to provide patients with reasonable treatment regimens without wasting medical resources or delaying their recovery. There has been a shift in the therapy paradigm for LUAD over the past few years due to the use of immunotherapies for the therapy of patients suffering from LUAD [10, 11]. Since January 2015, there have been substantial advancements made in cancer immunotherapy [12]. Inhibiting programmed cell death protein 1 is successful in treating Hodgkin's lymphoma, generating optimism about its potential to change the way the disease is typically treated [13, 14]. Immunotherapy using inhibitors of programmed death-1, programmable death ligand-1, and cytotoxic T lymphocyte associated antigen-4 has been demonstrated to possess potential anticancer benefits in malignant melanoma [15, 16]. Growing data suggest that tumor-infiltrating immune cells in the tumor microenvironment contribute to tumor development, aggressiveness, and responsiveness to therapy [17, 18]. Growing evidence supporting the idea that cancer lymphocytes, such as cancer macrophages and cancer neutrophils, affect the prognosis and the efficiency of chemotherapy and immunotherapy is also rising [19]. Additionally, it has become more and more common to block immunological checkpoints like PD-1/PD-L1 and CTLA-4 in malignant tumors [20, 21]. The majority of malignancies do not react well to immunotherapy with a single drug because the tumor microenvironment contains immune elements. Clarifying immunogen types of tumor-immune interactions as well as finding new immune-related biomarkers and targeted therapies in LUAD are urgently needed. The TCGA project, which was completed just recently, includes matched clinical and molecular data of numerous tumors, which makes it possible to conduct a systematic investigation of the impact that single gene expression has on patients' chances of survival. In this study, we aimed to explore novel biomarkers via analyzing TCGA datasets. Using LUAD cohorts-based TCGA datasets, we screened differentially expressed genes (DEGs). We identified a novel LUAD-related gene ubiquitin-conjugating enzyme E2T (UBE2T) which was significantly expressed in LUAD and predicted a poor prognosis. UBE2T plays a significant function in a variety of pathological processes in a manner that is E2-enzyme-dependent. The reason for this is that it belongs to the E2 family of proteins, which are responsible for conjugating ubiquitin to substrates [22]. The expression of UBE2T has been reported to be dysregulated in several tumors, including cancers of the stomach, liver, and esophagus [23–25]. Despite this, there has been no investigation of the prognostic value of UBE2T in LUAD. Based on our findings, a new prognostic biomarker that is involved in the microenvironment of tumors may be developed for LUAD.
Over 10,000 cancer patients whose tumors were classified into one of 33 categories have been assessed and evaluated by the TCGA research network. To obtain transcriptome data of 33 different tumor types, we searched the TCGA database (https://portal.gdc.cancer.gov/). A total of 33 cancer types were studied. They were OV, PAAD, PRAD, READ, SKCM, STAD, TGCT, THCA, THYM, UCEC, and UCS. ACC, BLCA, BRCA, COAD, DLBC, ESCA, GBM, HNSC, KICH, KIRC, KIRP, LAML, LGG, LIHC, and UCS. The full names of all tumors are shown in Table S1.
Data from our research were mapped against version 38 (hg38) of the human genome using the STAR2 software. This allowed us to generate data on gene expression. The Sam Tools were utilized in order to identify the mapped reads that had a quality of 10 or higher. The feature count served as the reference transcriptome to define the read counts for each gene. With the aid of the edger package in R, differential expression analysis was conducted, and tumor samples were compared with normal samples that were matched to them in order to identify DEGs [26]. Among the genes that were selected for differential expression between tumor and normal samples, their false discovery rates (FDR) are less than 0.05 and their absolute log2 fold changes (log FC) are greater than 4.
The TCGA and Genotype Tissue Expression (GTEx) projects provided data on the differential expression of UBE2T between tumor and normal tissue that was matched to a tumor. A tissue bank and data resource called GTEx has been established by the National Institutes of Health Common Fund (https://gtexportal.org). A total of 53 human normal tissues from about 1,000 people were examined for genetic variants, RNA sequencing, and additional molecular traits. We chose log2 (TPM+1) converted expression data for plotting, which was how we chose the parameters.
Whether UBE2T expression and immune cell presence were correlated was investigated using the Tumor Immune Estimation Resource database (TIMER) [27]. The TIMER database greatly assisted in the evaluation and integration of immune cells for RNA sequencing samples from the TCGA. These immune cells are thought to contain human B cells, human CD4+ T cells, human CD8+ T cells, human macrophages, human neutrophils, and human dendritic cells. The proportional fractions of 22 different immune cell types invading each tumor sample were calculated using the R tool CIBERSORT.
In this research, we examined the relationship between more than 40 immune checkpoint genes and UBE2T expression. The R software program “GGplot2” was used to retrieve these immune checkpoint genes, estimate the correlation between gene expression and immune checkpoint gene expression, and generate a diagonal heat map [28]. Using a diagonal heat map, we were able to illustrate the association. As shown in the upper triangle, the P value and significance of the correlation are expressed in color, while the correlation coefficient is illustrated in the lower triangle. The ∗ in the graph indicates a significant correlation P less than 0.05, the ∗∗ represents a significant correlation P less than 0.01, and the ∗∗∗ indicates a significant personality P less than 0.001.
The data were examined using the R program (Version 3.6.3, The R Foundation for Statistical Computing). The unpaired t test was applied to test the differential expression of UBE2T in cancer tissues compared to adjacent nonmalignant tissues. The log-rank test was used to evaluate the Kaplan–Meier survival curves. The Cox regression model for multivariate analysis was used to ascertain the existence of independent prognostic variables. A P value of less than 0.05 was used to determine a statistical significance.
This study retrospectively analyzed data from 516 LUAD samples and 59 control samples from TCGA datasets. The DEGs were analyzed using the limma package. In total, 578 DEGs were identified: 171 were significantly upregulated and 408 were significantly downregulated (Figures 1(a) and 1(b)).
Then, we performed a Kaplan–Meier analysis on LUAD to screen for DEGs associated with survival in the context of survival caused by DEGs, with P less than 0.01. As shown in Figure 2, we identified 9 survival-related DEGs in LUAD, including ASF1B, CA9, CCNB2, CCNE1, RRM2, SAPCD2, TCN1, TPX2, and UBE2T. A PubMed search revealed that several of them have been reported in various types of tumors, including LUAD. However, no research has been conducted on the expression and function of UBE2T in LUAD. Thus, we focused on UBE2T.
We examined the expression of UBE2T in several tumors and the normal tissues that bordered them to evaluate whether or not it is associated with malignancy. According to TCGA data, UBE2T mRNA expression was significantly higher in tumor tissues from the BLCA, BRCA, CESC, CHOL, COAD, ESCA, GBM, HNSC, KIRC, KIRP, LIHC, LUAD, LUSC, PAAD, PCPG, PRAD, READ, STAD, THCA, and UCEC than in normal tissues, suggesting that this molecule may play an oncogenic role in tumor progression (Figure 3). The analysis of UBE2T expression in cancer utilizing the TCGA and GTEx databases revealed a similar result as well (Figure S1). Besides, we further assessed the prognostic value of UBE2T for pan-cancer. The correlation between increased UBE2T expression and reduced overall survival in ACC, BRCA, KIRC, KIRP, LGG, LIHC, LUAD, MESO, OV, PAAD, STAD, and THYM is shown in Figure S2.
First, in contrast to nontumor specimens, we discovered a clear increase in UBE2T expression in LUAD tissues (Figures 4(a) and 4(b)). The link between UBE2T expression and a number of clinical variables was then investigated. Additionally, we discovered that high UBE2T expression was associated with gender (Figure 4(c)), age (Figure 4(d)), and advanced clinical stage (Figure 4(e)). Additionally, pTNM-stage and UBE2T expression were significantly correlated, according to univariate analysis (Figure 5(a)). The UBE2T expression and pTNM-stage were shown to be independent predictive variables after multivariate data analysis (Figure 5(b)). The degree of immune infiltration in malignancies and the expression of UBE2T are correlated. As a result of tumorigenesis, the growth process is a difficult one that is accompanied by several different phenomena, such as increased proliferation, resistance to apoptosis, increased angiogenesis, and escape from immunity, among other phenomena. TME is one of them that plays an important part. TILs not only inhibited the growth of tumors but also shielded cancer cells from being destroyed, making them an important player in the fight against cancer. To look into the potential connection between UBE2T expression and immune cell infiltration, data on immune cell infiltration from two independent sources were used in a correlation study. The findings of the TIMER2 and CIBERSOR tests revealed that UBE2T was favorably linked with the amount of immune cell infiltration in the TCGA pan-cancer model (Figure S3 and Figure 6). This study's key finding was that UBE2T correlated favorably with T cell gamma delta, T cell follicular helper, T cell CD4+ memory activated, NK cell activated, macrophage M0, and B cell naive and adversely with T cell CD4+ memory resting, myeloid dendritic cell resting, mast cell activated, macrophage M2, and B cell plasma (Figure 6). Data on immune cell infiltration from three sources were consistently examined.
The relationship between the UBE2T expression and immunological checkpoint genes was examined using eight popular immune checkpoint genes. Figure S4 presents the findings. In a variety of cancers, UBE2T expression was associated favorably with the levels of numerous immune checkpoint genes, including UVM, THCA, LIHC, LGG, KIRC, and BLCA (Figure S4). On the other hand, it was discovered that the LAG3 expression and UBE2T expression were positively associated. The expression of UBE2T and immunological checkpoint genes was examined to see whether there was a relationship between them. The research used eight popular immune checkpoint genes.
Everyone knows that lung cancer is the sort of cancer that causes the most fatalities worldwide [29]. Over 80% of all instances of lung cancer are diagnosed in individuals with NSCLC, and about 50% of these patients have LUAD [30]. Despite improvements in medication regimens, the survival rate of individuals with LUAD remains very poor. In addition to the high-level variability of LUAD, there are a plethora of complicated etiologic factors that may make it challenging to predict the prognosis [31, 32]. Therefore, the creation of creative prognostic models is urgently required. The TCGA database was used to get clinical and mRNA expression data from LUAD level 3 RNA seq for the present research. Then, we carried out a comparison of the differential expression between LUAD-positive samples and normal lung tissue. There were found to be 408 substantially downregulated genes and 171 significantly upregulated genes out of a total of 578 DEGs. Then, we discovered 9 DEGs in LUAD that were associated with survival. UBE2T was one among those that caught our interest. Previous studies have hypothesized that UBE2T may contribute to a variety of tumor forms. For instance, Yu et al. found that RACK1 was ubiquitinated and degraded at the lysine K172, K225, and K257 residues without the aid of an E3 ligase by UBE2T, which overactivated the Wnt/-catenin signaling pathway. This opens up a new window of possibility for particular GC patients who have abnormal Wnt/-catenin signaling [23]. Liu and his colleagues found that both the mRNA and protein levels of UBE2T were considerably greater in HCC tissues compared to nontumor tissues close to the tumor. It was also shown that UBE2T overexpression prevented hepatoma cell proliferation, colony formation, tumorigenesis, migration, and invasion, but UBE2T inhibition had the reverse effect [24]. Additionally, it was shown that the UBE2T expression was markedly increased in GBM tissues and was associated with a bad prognosis. Blocking UBE2T dramatically decreased cell invasion and migration, according to in vitro study. This was done by stabilizing GRP78 and controlling EMT [33]. UBE2T may have previously been shown to promote both autophagy and proliferation, which raises the possibility that by inhibiting this gene, lung cancer cells may not go through autophagy. It was discovered that the p53/AMPK/mTOR signaling pathway was engaged during UBE2T-mediated autophagy, proving that UBE2T induced autophagy via this mechanism. However, the prognostic value of UBE2T has not been investigated. In this study, we examined the associations between the expression of UBE2T and several clinical factors. We also found that advanced clinical stages, gender, and age were associated with higher UBE2T expression. Multivariate analysis was used to identify the p-TNM stage and UBE2T expression as independent prognostic factors. Our study showed that UBE2T has the potential to be used as a sophisticated prognostic biomarker for LUAD patients. Our findings were consistent with previous results that UBE2T may serve as a tumor promotor. According to current thinking, TME significantly affects the clinical treatment response and prognosis of patients with malignancies [34]. This idea is supported by the advancement of precise and high-throughput technology. Immune cells that have invaded tumor patients' TMEs have been proven in an increasing number of studies to have either a pro- or an antitumorigenic function [35, 36]. A positive prognosis for LUAD patients is related to immune cell infiltration in tumors, according to Rachel and others. The TCGA database has made it feasible to gather several global gene expression profiles as well as clinical information. In accordance with our findings, UBE2T was negatively correlated with T cell CD4+ memory resting, myeloid dendritic cell resting, mast cell activated, macrophage M2, and B cell plasma, and positively correlated with T cell gamma delta, T cell follicular helper, T cell CD4+ memory activated, NK cell activated, and B cell naive. Pan-cancer tests have also shown that UBE2T is critical for TME. The field of cancer treatment, LUAD in particular, has lately experienced a drastic upheaval as a result of considerable advancements in immunotherapy [37]. First-line pembrolizumab, an immune checkpoint inhibitor that targets PD-1, in combination with pemetrexed-carboplatin continues to demonstrate increased response and survival in advanced NSCLC in comparison to chemotherapy alone [38, 39]. Durvalumab, a human IgG1 monoclonal antibody that targets PD-L1, may prolong overall survival in Stage III non-small-cell lung cancer patients following chemoradiation [40]. Immunotherapy, however, could only benefit a tiny portion of patients if they are not picked correctly. Therefore, identifying reliable biomarkers to screen the majority of immunotherapy patients is critical. The expression of PD-L1 and TMB may serve as predictive indicators for the efficacy of ICBs, according to prior research. There are, however, restrictions to be aware of. For instance, because of the high geographical and temporal variation in the expression of PD-L1, the use of TMB is constrained since there are no uniform criteria that can be utilized to establish the cut-off value. In this study, we found that UBE2T expression was positively correlated with the expression of many immunological checkpoint genes, including UVM, THCA, LIHC, LGG, KIRC, and BLCA. However, we recently found a favorable correlation between the LAG3 expression and UBE2T expression. We infer from the aforementioned results that the immune infiltration's function in regulating UBE2T expression may have an impact on the onset and development of LUAD. This study inevitably contains several limitations that need to be taken into account. Firstly, because the prognosis for UBE2T in this study was based on information from the TCGA databases, new clinical data are required to confirm it. Additionally, UBE2T's involvement in the mechanism that it used in LUAD samples is not currently explained by wet experimental evidence. Therefore, more works is needed to shed light on the potential connection between UBE2T and the prognosis of LUAD. We intend to investigate the impact of UBE2T on LUAD cells by in vitro invasion and migration experiments, confirm the regulatory relationship between UBE2T and EMT development, and, finally, suggest investigating the impact of UBE2T on LUAD using animal models.
LUAD had an increased expression of UBE2T and its expression was significantly correlated with variables such as gender, age, and advanced clinical stage. Patients with high levels of UBE2T expression exhibited significantly shorter overall survival rates, and UBE2T could be used as a biomarker for LUAD prognosis. These findings not only offered crucial cues for the identification of novel treatment targets in LUAD but they also established a framework for the investigation of potential UBE2T pathways in LUAD. | true | true | true |
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PMC9553525 | Jun Rao,Jinjin Fu,Chuchen Meng,Jin Huang,Xiangrong Qin,Shaohua Zhuang | Corrigendum to “LncRNA SNHG3 Promotes Gastric Cancer Cells Proliferation, Migration, and Invasion by Targeting miR-326” | 20-09-2022 | Corrigendum to “LncRNA SNHG3 Promotes Gastric Cancer Cells Proliferation, Migration, and Invasion by Targeting miR-326”
In the article titled “LncRNA SNHG3 Promotes Gastric Cancer Cells Proliferation, Migration, and Invasion by Targeting miR-326” [1], concerns with the figures have been identified as initially raised on PubPeer [2]. In the published article, the right side panel of Figure 2(c) is the same as the middle two panels of Figure 6(c), the first left panel of Figure 2(d) is the same as the first left panel of Figure 3(d), and the N-cadherin of Figure 2(b) is the same as TWIST in HGC-27 of Figure 5(e). The authors explained that these errors were introduced during the preparation of the manuscript, and this does not affect the results and conclusions of the article. While the authors initially responded to provide an explanation to the concerns along with the revised figures, they have not responded to requests to approve this notice. This corrigendum is therefore published with the agreement of the editorial board to ensure the appropriate correction of the issues detailed above. The corrected Figures 2 and 6 are as follows. | true | true | true |
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PMC9553848 | Jiayuan Su,Jinrong Zhou,Yachan Feng,Haojie Zhang,Xinyu Zhang,Xiaorong Zhao,Yong Li,Xueling Guo | circPTN Promotes the Progression of Non-Small Cell Lung Cancer through Upregulation of E2F2 by Sponging miR-432-5p | 20-09-2022 | Background Non-small cell lung cancer (NSCLC) is one of the most prevalent cancers, accounting for around 80% of total lung cancer cases worldwide. Exploring the function and mechanism of circRNAs could provide insights into the diagnosis and treatment for NSCLC. Methods In this study, we collected tumor tissues and adjacent normal tissues from NSCLC patients to detect the expression level of circPTN and analyzed the association of its expression level with the clinicopathological parameter of NSCLC patients. Moreover, the functional engagement of circPTN in NSCLC cells was examined by cell counting kit-8 (CCK-8) cell proliferation assay, transwell migration and invasion assays, and tube formation assay. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting (WB) analysis were used to detect gene and protein expression, respectively. The molecular targets of cicrPTN were predicted using starBase online resources, which was validated by RNA immunoprecipitation (RIP) and dual-luciferase reporter assay. Results Compared with adjacent normal tissues, there was a remarkable increase of the circPTN levels in NSCLC tissues. A high level of circPTN expression was associated with more lymph node metastasis (LNM) and advanced TNM stages. Functionally, circPTN knockdown inhibited the proliferation, migration, and invasion and tube formation ability of NSCLC cells. We further demonstrated that circPTN regulated the malignant phenotype of NSCLC cells through targeting the miR-432-5p/E2F2 axis. Conclusion Together, our results suggest that circPTN, which is upregulated in NSCLC tissues, could serve as a prognostic marker for NSCLC patients. circPTN regulates the malignant progression of NSCLC cells through targeting the miR-432-5p/E2F2 axis, which may be employed as a potential strategy for the management of NSCLC. | circPTN Promotes the Progression of Non-Small Cell Lung Cancer through Upregulation of E2F2 by Sponging miR-432-5p
Non-small cell lung cancer (NSCLC) is one of the most prevalent cancers, accounting for around 80% of total lung cancer cases worldwide. Exploring the function and mechanism of circRNAs could provide insights into the diagnosis and treatment for NSCLC.
In this study, we collected tumor tissues and adjacent normal tissues from NSCLC patients to detect the expression level of circPTN and analyzed the association of its expression level with the clinicopathological parameter of NSCLC patients. Moreover, the functional engagement of circPTN in NSCLC cells was examined by cell counting kit-8 (CCK-8) cell proliferation assay, transwell migration and invasion assays, and tube formation assay. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting (WB) analysis were used to detect gene and protein expression, respectively. The molecular targets of cicrPTN were predicted using starBase online resources, which was validated by RNA immunoprecipitation (RIP) and dual-luciferase reporter assay.
Compared with adjacent normal tissues, there was a remarkable increase of the circPTN levels in NSCLC tissues. A high level of circPTN expression was associated with more lymph node metastasis (LNM) and advanced TNM stages. Functionally, circPTN knockdown inhibited the proliferation, migration, and invasion and tube formation ability of NSCLC cells. We further demonstrated that circPTN regulated the malignant phenotype of NSCLC cells through targeting the miR-432-5p/E2F2 axis.
Together, our results suggest that circPTN, which is upregulated in NSCLC tissues, could serve as a prognostic marker for NSCLC patients. circPTN regulates the malignant progression of NSCLC cells through targeting the miR-432-5p/E2F2 axis, which may be employed as a potential strategy for the management of NSCLC.
Lung cancer has become one of the most common cancers globally [1], with an increasing incidence in recent years [2]. In the meantime, lung cancer has become one of the main cancer-related mortalities globally. Non-small cell lung cancer (NSCLC) is the main subtype of lung cancer, accounting for around 80% of total lung cancer cases [3]. Despite the development of various treatment modalities, the overall survival (OS) is unsatisfactory, especially in patients with metastasis, with a 5-year OS rate less than 5% [4]. Exploring the markers for early diagnosis and prognosis prediction and investigating the mechanisms in its progression are of great important for the effective management of NSCLC in clinics. Unlike linear RNAs, circRNAs have a closed-loop structure, rendering them high stability and resistance to the degradation by exonucleases [5]. circRNAs frequently serve as molecular sponges for other noncoding RNAs such as micro-ribonucleic acid (miRNA), which in turn regulates the activity of miRNAs and the expression of the downstream target mRNAs [6]. circRNAs have been implicated in regulating the initiation or progression of many pathological conditions [7], such as cancers [8], atherosclerosis (AS), neurological diseases, endocrine and metabolic diseases, and viral infections [9]. Due to its stable circular structure [10], circRNAs are highly abundant in eukaryotic cells, and their expression pattern shows tissue-specificity [11]. Recently, 257 novel circRNAs were identified in the samples of patients with colorectal cancer [12], indicating that cancer-specific expression of cicrRNAs play critical roles in cancer progression. Another study demonstrated that serum circ-KLDHC10 level in HCC patients were significantly elevated compared with healthy subjects [13], which may serve as a diagnostic marker. In contrast, hsa_circ_0000190 showed significant downregulation in plasma samples in patients with gastric cancers [14]. Interestingly, a recent study indicates that there was a significant difference in the expression of circRNAs in patients with gastric cancer (GC) before and after surgery [15]. In addition, circRNAs are also implicated in the initiation and progression of multiple types of cancer [16–18]. Moreover, different circRNAs deregulated in NSCLC have been proposed as diagnostic markers for the management of NSCLC patients [19–21], indicating a clinical value of circRNA investigation. miRNAs are a class of short (average 22 nucleotides) endogenous non-coding RNAs with critical roles in post-transcriptional gene regulation in cancer development and progression [22, 23]. miRNAs are able to regulate the expression of oncogenes or tumor suppressor genes by competitively biding to the seed sequences in the untranslated region (UTR) of target mRNAs, ultimately inducing target mRNA degradation or translational arrest [24]. A previous report indicated that miR-432-5p was downregulated in lung cancer, suggesting its tumor suppressor function [25]. It was reported that circPTN functions as an oncogene in glioma and liver cancer [25, 26] by targeting miR-432-5p. However, the functional roles of circPTN and miR-432-5p in NSCLC remain unclear. Considering these aspects, in this study, we attempted to unveil the expression pattern and functional role of circPTN and miR-432-5p in NSCLC. We demonstrated the upregulation of circPTN in NSCLC tissues and studied its functions in NSCLC cells by cell proliferation assay, transwell migration and invasion assays, and vessel formation assay. Furthermore, the mechanistic interactions among of circPTN, miR-432-5p, and E2F2 (E2F Transcription Factor 2) were predicted by starBase and investigated by RNA immunoprecipitation (RIP) and dual-luciferase reporter assays. Overall, our data shed light on the role of circPTN/miR-432-5p/E2F2 axis in regulating the malignancy of NSCLC cells, which provides insights into the diagnosis, treatment, and prognosis assessment of NSCLC.
A total of 90 NSCLC samples and paired para-tumor tissues in NSCLC patients were collected by surgery from October 2019 to January 20121 in the Xichang People's Hospital. All the enrolled patients had not gone through chemotherapy or radiotherapy. Prior to sample collection, informed consent was provided by each patient. All the experimental procedures were approval by the Ethics Committee of Xichang People's Hospital.
Human bronchial epithelial (HBE) cells and NSCLC cells (A549, CALU3, CALU6, H1229, and H1650) were obtained from Beyotime (Hangzhou, China) and Cell Bank of the Chinese Academy of Sciences (Shanghai, China). All the cells were cultured in the RPMI-1640 medium (Gibco, Rockville, MD, USA) supplemented with 10% fetal bovine serum (FBS, Gibco, Rockville, MD, USA) and 100 U/ml of penicillin and 100 μg/ml of streptomycin in a humidified incubator containing 5% CO2 at 37°C.
Cells were inoculated within the 6-well plates until 75% confluence. Cell transfection was performed using Lipofectamine™ 2000 reagent (Invitrogen, Carlsbad, CA) or Entranser™-R4000 (Engreen Biosystem, Beijing, China) according the manufacturer's instructions. 10 μL of Lipofectamine 2000 and 10 μL of siRNA-SNHG12 or siRNA-NC (RiboBio Co. Ltd., Guangzhou, China) were mixed in 500 μL of serum-free medium for 15 min. For plasmid, 4 μl of Entranser™-R4000 reagent and 2.68 μg of pcDNA-SNHG12 or pcDNA empty vector (GenePharma, Suzhou, China) were mixed in 500 μL serum-free medium for 15 min. After the incubation, the mixture was added into each well dropwise and the cells were incubated for 6 h. The medium was replaced with fresh culture medium after 6 h of transfection, and the cells were subjected to further experiment after 48 h.
Total RNA samples were extracted using miRNeasy mini kit (QIAGEN, Hilden, Germany). An miRNA RT kit (Applied Biosystems, Foster City, CA, USA) was utilized for reverse transcription. qRT-PCR was performed using SYBR Green Master Mixture (Roche, Basel, Switzerland) on the 7500 Fast Real-Time PCR System (Applied Biosystems, USA). 2-ΔΔCt method was adopted for relative gene expression analysis, with GAPDH and U6 being the endogenous references. The primer sequences (Genewiz, South Plainfield, NJ, USA) are as follows (from 5'–3'): circPTN-forward: TCAAGAATGCAGGCTCAAC, reverse: TCAAGAATGCAGGCTCAAC; miR-432-5p-forward: AACGAGACGACGACAGACT, reverse: CTTGGAGTAGGTCATTGGGT; E2F2-forward: CGTCCCTGAGTTCCCAACC, reverse: GCGAAGTGTCATACCGAGTCTT; GAPDH-forward: CTGGGCTACACTGAGCACC, reverse: AAGTGGTCGTTGAGGGCAATG; and U6-forward: CTCGCT TCGGCAGCACA, reverse: AACGCT TCACGA ATTTGCGT. Thermal cycling conditions for qPCR were as follows: 95°C for 2 minutes, 40 cycles of 95°C for 30 seconds, 60°C for 30 seconds, and 72°C for 60 seconds.
Cell proliferation was examined using the CCK-8 assay (Beyotime, C0037). Initially, the cells (2 × 103 cells/well) were seeded into the 96-well plate and incubated for 0, 24, 48, and 72 h. At indicated time points, 100 μL of 10% CCK-8 working solution was added to the wells for 2 h of incubation at 37°C in 5% CO2. The absorbance values of different groups were measured at 450 nm using the microplate reader (BioTeke, Winooski, VT, USA).
The proliferation of cells was determined using the EdU staining proliferation kit (KeyFluor488 EdU Kit, keyGEN BioTECH, Jiangsu, China), following the manufacturer's instructions. Cells were seeded in 96-well plates (1 × 104 cells/well) in 100 μL medium. The next day, the cells were cultured with 20 μM EdU for 2 h under 5% CO2 and 37°C. Then, 4% paraformaldehyde was added to fix the cells for 30 min, and 0.5% Triton-X-100 in PBS was added and incubated for 20 min. After the removal of the solution, 1x Click-iT® reaction cocktail was added to cells and incubated for 30 min. The staining cocktail was removed and cells were counter-stained by 500 nM DAPI in PBS and the images were captured under a Leica AM6000 microscope (Leica, Wetzlar, Germany).
Cell invasion and migration were assessed by transwell assay. Briefly, cells with different treatments were trypsinized and resuspended in serum-free medium. The transwell upper chamber (Corning, New York, USA) without Matrigel (BD Biosciences, MA, USA) was used for migration assay, while transwell chamber coated with Matrigel was used for invasion assay. A total of 2.5 × 105 cells were seeded into the upper chamber in 400 μL serum-free medium, and 500 μL of 20% serum-containing medium was added to the lower chamber. After 24 hours, cells on the membrane were fixed with 3.7% paraformaldehyde for 10 min and stained with 0.5% crystal violet (Sigma, Germany) for 20 min. Cells were photographed under a Leica AM6000 microscope.
Tube formation was performed using an in vitro angiogenesis assay kit (ab204726; Abcam). Initially, cells (2.0 × 104) were seeded in a 96-well plate coated with 50 μl of extracellular matrix (ECM) solution. After 18 h, cell morphology was observed with a phase-contrast microscope (DMI6000B; Leica, Wetzlar, Germany). The Image J Angiogenesis Analyzer (National Institutes of Health (NIH), Bethesda, MD, USA) was used for quantification of the network structure.
Cell lysates were collected using IP lysis buffer (Beyotime, P0013), with 10% total lysate saved as input. 100 nM of biotin-labeled control probe or wild-type (WT) circPTN probe was mixed with cell lysate and incubated for a 12 h at 4°C. 100 μL of Dynabeads M-280 Streptavidin (Thermo Fisher Scientific, CA, USA) was added to the solution and incubated for 2 h under 4°C. The beads were precipitated using a magnetic bar and washed three times using high salt buffer (500 mM NaCl, 1% Triton X-100, 0.1% SDS, 20 mM Tris-HCl, pH 8.0, 2 mM EDTA). Finally, the precipitated RNA samples or RNA in the input samples were purified using the TRIzol reagent (Invitrogen, Carlsbad, CA, USA) for qRT-PCR assay.
The sequence containing the wild-type binding site or the sequence with mutated binding site was cloned into the PmirGLO vector expressing firefly luciferase (Promega, WI, USA). The reporter plasmid and Renilla luciferase (hRlucneo) control plasmid were co-transfected into cells using LipofectamineTM 2000 (Invitrogen). 48 h after the transfection, the relative luciferase activities were measured using dual-luciferase reporter assay kit (Promega, WI, USA) on a luminescence GloMax® discover microplate reader (Promega). Firefly luciferase activity in each sample was normalized to that of Renilla luciferase.
RIPA buffer (Beyotime Biotechnology, Shanghai, China) was utilized to extract total protein, and protein concentration was determined using a BCA protein assay kit (Beyotime Biotechnology, Shanghai, China) as per instructions. The protein samples were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto PVDF membranes (Millipore, Billerica, MA). After blocking with the skimmed milk, the membrane was incubated using the following antibodies: E2F2 (Ab138515, Abcam), actin (ab8227, Abcam), E-cadherin (ab231303, Abcam), N-cadherin (ab76057, Abcam), vimentin (ab137321, Abcam) at 1 : 1000 dilutions at 4°C overnight. The membrane was washed with the TBST buffer and then incubated with HRP-conjugated secondary antibody under ambient temperature for 2 h. The protein bands were visualized using the ECL detection kit (Yeasen, Shanghai, China), with actin as the internal control.
All the animal experiments were approved by the Animal Use and Care Committee of Hebei University of Science and Technology and carried out according to the institutional regulations and guidelines. Briefly, the female BALB/c nude mice (4-week-old) were randomly assigned into 2 groups (n = 6 in a group): 1 × 106 cells stably transfected with sh-NC or cell stably transfected with sh-circPTN by subcutaneous injection on the flank of the mice. Tumor volume was determined at 7-day intervals, with the following formula: V (tumor) = 0.5 × length × width2. On day 28, the mice were euthanized by carbon dioxide asphyxiation and cervical dislocation. The tumor samples were removed for histological and IHC analysis.
Tumor tissues were fixed with 4% paraformaldehyde (PFA, V/V), followed by paraffin embedding. 4-μm tissue sections in paraffin were soaked in xylene for 15 min before dehydration with gradient ethanol. Each section was then soaked with citric acid (pH 6.0 DAKO) for 10 min at 95° for antigen retrieval and cooled to ambient temperature. After washing with TBST buffer for a 15-min period, the sections were incubated with 3% H2O2 for 10 min. Tissue sections were blocked using 5% bovine serum albumin (BSA) for 30 min, followed by overnight incubation using primary antibodies E2F2 (Ab138515, Abcam) and Ki67 (ab15580, Abcam) under 4°C. Color development was performed using a DAB color-rendering kit (Soleibol, Japan). The images were captured using a Leica AM6000 microscope.
H&E staining was performed using the H&E stain kit (ab245880, Abcam). Tissue sections were incubated in hematoxylin solution, Mayer's (Lillie's Modification), for 5 min. The section was rinsed twice with distilled water and incubated with adequate bluing reagent for 30 seconds. After washing with distilled water, the section was dehydrated in absolute alcohol, followed by staining with eosin Y solution for 2 min. The section was rinsed using absolute ethanol for three times and then mounted to a slide, and the images were collected under an inverse microscope.
The data were expressed as means ± SD. Kaplan–Meier (K-M) curve was used to analyze the overall survival in NSCLC patients. GraphPad Prism 5 (GraphPad Software, La Jolla, CA, USA) was utilized for statistical analysis. Student's t-test was adopted to compare the difference between two groups, while one-way ANOVA was used to compare the difference among multiple groups. P < 0.05 was deemed to be statistical significant.
Initially, the expression levels of circPTN were compared between NSCLC tissues and para-tumor tissues. qRT-PCR results showed circPTN level was upregulated in NSCLC tissues as compared to the para-cancerous tissues (Figure 1a). Besides, the cicrPTN level was also higher in the patients with metastasis when compared to the ones without metastasis (Figure 1(b)). The patients were divided into circPTN high-expression and low-expression groups based on the median expression value of circPTN. A high circPTN expression was associated with more lymph node metastasis (LNM) and advanced TNM stage (Table 1). Further, as revealed by the KM plotter, high circPTN expression was correlated with a worse overall survival in NSCLC patients (Figure 1(c)). In addition, circPTN expression levels were also significantly higher in NSCLC cells compared to Human bronchial epithelial (HBE) cells (Figure 1(c)). These data indicates that high level expression of circPTN predicts a poor prognosis in NSCLC patients.
Two NSCLC cell lines (A549, H1229) with the highest circPTN expression (Figure 1(d)) were selected for subsequent experiments. After the transfection of siRNAs, circPTN levels were significantly reduced by sh-circPTN in H1229 and A549 cells (Figure 2(a)). CCK-8 proliferation assay and EdU incorporation assay showed that circPTN knockout significantly inhibited the cell proliferation in both cell lines (Figure 2(b) and 2(c)). As revealed in the Transwell assays, circPTN knockout impaired the migration (Figure 2(d)) and invasion abilities (Figure 2(e)). In addition, tube-forming ability was also undermined upon circPTN silencing (Figure 2(f)). We also examined epithelial–mesenchymal transition (EMT)-related proteins by Western blot. CircPTN silencing increased the expression of epithelial marker E-cadherin, while mesenchymal markers including vimentin and N-cadherin were decreased (Figure 2(g)). Together, these data suggest that circPTN expression is indispensable of the malignant phenotype of NSCLC cells.
To search for the downstream miRNA targets, we employed three different software tools (“circAtlas,” “circBank,” and “circInteractome”) to predict the interacting partners of circPTN, which revealed that hsa-miR-326 and hsa-miR-432-5p could be potential targets (Figure 3(a)). RNA pull-down analysis using biotin-labeled circPTN probe showed that both miRNAs were enriched with the circPTN probe, with a much higher enrichment for miR-432-5p (Figure 3(b)). We cloned the potential binding sites (WT) or the mutated binding sites (MUT) between circPTN and miR-432-5p and performed dual-luciferase reporter assay in the presence of miR-432-5p mimic or miR-NC (Figure 3(c)). The results showed that miR-432-5p mimic significantly suppressed luciferase activity of WT reporter, while the mutation of the biding sites abrogated this effect (Figure 3(d)). In addition, RIP-assay demonstrated that Ago2 antibody enriched more circPTN and miR-432-5p when compared with the IgG group (Figure 3(e)). Moreover, miR-432-5p expression level showed a downregulation in NSCLC tissues (Figure 3(f)), and there was a negative correlation between miR-432-5p and circPTN in NSCLC tissues (Figure 3(g)). Together, these data suggest that miR-432-5p is a target negatively regulated by circPTN.
To explore the downstream target of miR-432-5p, TargetScan software was employed to predict that there was binding sites in the 3' UTR of E2F2 mRNA for miR-432-5p (Figure 4(a)). miR-432-5p mimic significantly suppressed the luciferase activity of WT reporter compared with miR-NC, while inhibition was not abrogated when the predicted E2F2 binding sites were mutated (Figure 4(b)). miR-432-5p overexpression significantly reduced E2F2 protein level (Figure 4(c)). In addition, circPTN knockdown also reduced the E2F2 protein level and the co-transfection of miR-432-5p inhibitor partially restored E2F2 expression (Figure 4(d)). As revealed by qRT-PCR and WB assays, E2F2 showed a relatively higher expression in NSCLC tissues compared to the adjacent normal tissues (Figure 4(e) and 4(f)). Moreover, E2F2 expression was negatively correlated with miR-432-5p level, but positively correlated with circPTN in NSCLC tissues (Figure 4(g) and 4(h)). These data imply that circPTN regulates E2F2 expression through sponging miR-432-5p in NSCLC cells.
We next sought to validate the role of miR-432-5p/E2F2 axis in the effect of circPTN. We employed pcDNA-E2F2 expression vector, which could effectively promote the protein level of E2F2 in NSCLC cells (Figure 5(a)). CCK-8 proliferation assay and EdU staining assays showed that circPTN knockdown inhibited cell proliferation, which was partially rescued after the co-transfection of pcDNA-E2F2 plasmid or miR-432-5p inhibitor (Figure 5(b) and 5(c)). Similar rescue effects were observed using Transwell migration and invasion assays and tube formation assay in NSCLC cells (Figures 5(d)–5(f)). As revealed by WB assay, circPTN silencing suppressed the expression of mesenchymal markers (vimentin and N-cadherin) but increased the expression of E-cadherin. However, the co-transfection of pcDNA-E2F2 plasmid or miR-432-5p inhibitor partially reversed the effect of circPTN silencing (Figure 5(g)). Together, these data suggest that miR-432-5p/E2F2 axis mediates the role of circPTN in regulating the malignant phenotype of NSCLC cells.
To evaluate the role of circPTN in tumorigenesis, we established subcutaneous xenograft growth model in nude mice using H1299 cells stably expressing sh-NC or sh-circPTN. circPTN knockdown significantly inhibited the tumor volume increase when compared with the sh-NC group (Figure 6(a)). In addition, knockdown of circPTN significantly lowered the tumor weight (Figure 6(b)). The retarded tumor growth in the sh-circPTN group was associated with a reduced E2F2 level and an increased miR-432-5p level in the xenograft tumors (Figure 6(c)). Based on IHC analysis, both Ki-67 (proliferation marker) and E2F2 levels were significantly suppressed in sh-circPTN group (Figure 6(d)). Moreover, relative to the sh-NC group, there were less pulmonary metastases in the lung tissues after circPTN knockdown (Figure 6(e)). Therefore, circPTN expression is required to support the tumorigenesis of NSCLC cells in vivo.
CircRNAs have been proposed as cancer diagnostic biomarkers as they show superior stability over linear RNAs. Cancer-related circRNAs can be detected in plasma exosomes from nude mice bearing tumor xenografts [27]. In addition, EML4-ALK (one of the fusion genes in cancer) can also be detected in the plasma samples from NSCLC patients [28]. In this study, we reported a high-level expression of circPTN in NSCLC cells and tissues, which is associated with a poor prognosis in NSCLC patients. Furthermore, silencing circPTN impaired the malignant phenotype of NSCLC cells. These results highlight the potential of circPTN as a prognostic marker for NSCLC patients. circRNAs could sponge miRNAs to regulate gene expression during tumor progression [7]. Through bioinformatics prediction and RNA pull-down experiment, miR-432-5p was identified as a downstream target of circPTN. Since circPTN and miR-432-5p also showed negative correlation in NSCLC cells, these data suggest circPTN sponges miR-432-5p and negatively regulates its activity in NSCLC cells. However, it remains to be investigated what the upstream mechanisms are underlying the upregulation of circPTN in NSCLC cells. Previous studies have demonstrated that miR-432-5p acts as a tumor suppressor molecule that is frequently downregulated in various tumors, including pituitary adenomas [29], hepatocellular carcinoma [30], osteosarcoma [31], lung adenocarcinoma [32], and nasopharyngeal carcinoma [33]. Since circPTN sponges miR-432-5p and downregulates miR-432-5p, our data also suggest that miR-432 acts as a tumor-suppressor factor in NSCLC cells. We further revealed that E2F2 is a downstream target of miR-432-5p. E2F2 is negatively correlated with miR-432-50 expression but positively correlated with circPTN expression. The overexpression of E2F2 also rescued the phenotype of NSCLC cells upon circPTN silencing. These data suggest that E2F2 acts as an oncogene, which is upregulated by circPTN and negatively regulated by miR-432-5p in NSCLC cells. These data seem consistent with the previously reported oncogenic role of E2F2 in different cancers [34–36]. E2F2 belongs to the E2F transcription factor family that binds to DNA with DPDP1-polypeptide at the E2 recognition site in gene promoter region, thus producing the gene expressions related to DNA replication and cell cycle progression [35]. E2F2 plays a critical role in promoting the progression of the cell cycle [37]. In this context, E2F2 overexpression can be an important factor contributing to the accelerated cell cycle progression, which predicts dismal overall survival in NSCLC patients [31]. Indeed, its overexpression could rescue the retarded proliferation in NSCLC cells upon circPTN silencing. Overall, these data support the notion that E2F2 acts as an oncogenic transcription factor downstream of circPTN, which promotes proliferation and tumor progression in NSCLC cells.
In summary, our results revealed the upregulation of circPTN in NSCLC tumors and its contribution to the malignant phenotype of NSCLC cells. circPTN maintains the expression of E2F2 in NSCLC cells by sponging miR-432-5p. Since a high level of circPTN is correlated with the poor prognosis in NSCLC patients, circPTN may serve as a prognostic marker in NSCLC. | true | true | true |
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PMC9553902 | 36202613 | Anaïs M Quéméner,Laura Bachelot,Marc Aubry,Stéphane Avner,Delphine Leclerc,Gilles Salbert,Florian Cabillic,Didier Decaudin,Bernard Mari,Frédéric Mouriaux,Marie-Dominique Galibert,David Gilot | Non-canonical miRNA-RNA base-pairing impedes tumor suppressor activity of miR-16 | 06-10-2022 | In uveal melanoma tumors, the RNA decay activity of the tumor suppressor miR-16 is impaired by sponge RNAs. These RNAs defined a powerful signature to predict overall survival. | Non-canonical miRNA-RNA base-pairing impedes tumor suppressor activity of miR-16
In uveal melanoma tumors, the RNA decay activity of the tumor suppressor miR-16 is impaired by sponge RNAs. These RNAs defined a powerful signature to predict overall survival.
Uveal melanoma (UM) is the most common primary intraocular tumor in adults. No effective treatment is currently able to counteract UM metastasis (Jager et al, 2020). UM carries mutually exclusive mutations that trigger overactivity of the Gαq pathway (G protein subunit alpha q [GNAQ], G protein subunit alpha 11 [GNA11], Phospholipase C Beta 4 [PLCB4], or Cysteinyl Leukotriene Receptor 2 [CYSLTR2]) (Robertson et al, 2018). UM is considered to be a G protein-coupled receptor disease. However, additional genetic events occur, such as BES alterations, BRCA1-associated protein 1 (BAP1), Eukaryotic Translation Initiation Factor 1A X-Linked (EIF1AX) and Splicing Factor 3b Subunit 1 (SF3B1), and recurrent copy number variations (CNVs). UM is usually a diploid tumor with recurrent CNV of whole chromosomes or arms. Among these genome structural variations, monosomy 3 is the most frequent (∼50% of cases). 1p loss, 1q gain, 6p gain, 6q loss, 8 gain, 8p loss, and 8q gain complete the UM genomic landscape. Monosomy 3 is clearly associated with a high risk of metastasis (Horsman et al, 1990; Bagger et al, 2014; Robertson et al, 2018; Shain et al, 2019). Although the loss of chromosome 3 induces the loss of BAP1 (3p21.1), the role of the other genes located on chromosome 3 in tumor aggressiveness is not excluded. Gain of 8q is also common in UM (∼50% of cases). It has been suggested that genes on chromosome 8q, such as MYC, and POU Class 5 Homeobox 1 (POU5F1), and Protein Tyrosine Phosphatase 4A3 (PTP4A3) may explain the poor overall survival (OS) of UM patients (Meir et al, 2007; Durante et al, 2020; Pandiani et al, 2021). PTP4A3 has been shown to promote migration and invasiveness in an UM cell line, and high PTP4A3 mRNA levels correlate with poor OSs of patients. It is important to note that the high level of PTP4A3 mRNA (up-regulated in 66% of UM) is not merely a consequence of 8q gain (Laurent et al, 2011; Duciel et al, 2019). To date, the molecular mechanism promoting high expression levels of PTP4A3 and MYC remains unsolved despite the deleterious consequences. Although UM is considered to be a G protein–coupled receptor disease with BES alterations and CNVs, at least three other cellular processes seem to be frequently deregulated. These include the YAP pathway which is activated via Hippo-independent activation, splicing activity and translation initiation as a result of alterations in BAP1, Serine And Arginine Rich Splicing Factor 2 (SRSF2), RNA Binding Motif Protein 10 (RBM10) EIF1AX, and other genes (Robertson et al, 2018; Shain et al, 2019). In 2018, an integrated analysis of 80 primary UMs was performed by The Cancer Genome Atlas (TCGA) to identify the deregulated pathways in this rare cancer with the end goal of finding druggable targets. Four mRNA signatures were generated based on tumor progression (Robertson et al, 2018). Other signatures have been generated (Harbour & Chen, 2013; Li et al, 2018; Luo et al, 2020) with few common genes. Recently, single-cell RNA sequencing results identified another RNA-signature called PC1. Using this signature, Bertolotto’s team was then able to predict, with great accuracy, which patients would develop metastases (Pandiani et al, 2021; Strub et al, 2021). Partially overlapping signatures identified 5-Hydroxytryptamine Receptor 2B (HTR2B) as a marker of poor prognosis (Robertson et al, 2018; Weidmann et al, 2018; Le-Bel et al, 2019; Ni et al, 2019; Onken et al, 2021; Pandiani et al, 2021). Gene expression patterns determine cell fate such as invasion capability; a critical process required for UM metastasis. miRNA shapes gene expression by inducing RNA decay via miRNA–RNA base-pairing. The factors determining miRNA binding to RNA are not fully understood. Biochemical characterization of miRNA targets (targetome) has indicated that miRNAs mainly induce RNA decay via the seed region of miRNA (nucleotides 2–7) and that in silico predictions are imperfect (Bartel, 2009). Counterintuitively, increasing evidence indicates that miRNAs bind to a subset of RNA without inducing their decay. In this case, the base-pairing between the seed region of the miRNA and the RNA is imperfect. The biological role of these imperfect interactions is still a topic of debate. It has been suggested that these interactions are artefactual, rare, and not relevant because miRNA does not exert decay activity (Agarwal et al, 2015; Bartel, 2018). Nevertheless, experiments based on cross-linked immunoprecipitation (CLIP) and alternative methods, performed by different teams, have identified such interactions (Loeb et al, 2012; Helwak et al, 2013; Grosswendt et al, 2014; Luna et al, 2015). It has been hypothesized that the imperfect miRNA binding to RNA might hamper the miRNA decay activity (Bartel, 2009). In other words, miRNA can be inactivated when “sponged” or “sequestered” in RNA via imperfect binding (also known as non-canonical binding). This concept, initially described in Arabidopsis thaliana, relies on the competition between RNAs to bind to a limited amount of miRNA (Franco-Zorrilla et al, 2007). This model has been extended to eukaryotes as the competing endogenous RNA (ceRNA) model (Salmena et al, 2011). The interpretation of ceRNA results is still a topic of debate because the stoichiometry between miRNA and RNAs (sponges) is not (or rarely) investigated. Yet, the overexpression of synthetic constructs sponging miRNA (miRNA sponges) has been shown to effectively reduce the activity of miRNA in cancer and plant cells, strongly suggesting that miRNA sequestration is achievable, in particular experimental conditions. We summarized the criteria describing a miRNA sponge in 2017 (Migault et al, 2017). Briefly, a sponge should be highly expressed to sequester all the targeted-miRNA and ideally should contain several imperfect miRNA-binding sites per linear RNA molecule such as tyrosinase-related 1 (TYRP1) mRNA (Gilot et al, 2017). Convincingly, the sequestration of miRNA has also been illustrated in vivo on circular RNA (Kleaveland et al, 2018; Hanniford et al, 2020), confirming the physiological relevance of this type of miRNA regulation. To date, well-characterized miRNA sponges have been rare in the literature because of the specific expression pattern of circRNA and the difficulty in predicting imperfect base-pairing between miRNA and sponges using current algorithms thought for linear RNA. Because one copy of the MIR16 gene is located on chromosome 3 and monosomy 3 is clearly associated with a high risk of metastasis, we evaluated the miR-16 expression level and activity of this tumor suppressor in UM. We hypothesized that the global miR-16 activity might be diminished in the case of monosomy and/or would be inactivated by sequestration on RNA via non-canonical binding.
miR-16 is encoded by two intronic loci on the human genome. MIR16-1 is located on the intronic region of Deleted in Lymphocytic Leukemia 2 (DLEU2) on chromosome 13 and MIR16-2 on the intronic region of Structural Maintenance of Chromosomes 4 (SMC4) on chromosome 3 (Fig 1A). Both are transcribed into pri-miR-16-1 and pri-miR-16-2, then respectively processed into pre-miR-16-1 and pre-miR-16-2 to generate a similar product; miR-16 (Lagos-Quintana et al, 2001; Mourelatos et al, 2002). Because chromosome 3 monosomy is detected in more than 50% of patients with UM (Robertson et al, 2018), we postulated that the expression level of the tumor suppressor miR-16 might be reduced and consequently might impact tumor growth as observed for Chronic Lymphocytic Leukemia (LLC) patients (Calin et al, 2002) (Fig 1B). We confirmed a 50% decrease in miR-16 expression in samples from leukemia patients mainly because of the absence of pri-miR-16-1 synthesis (Fig 1C). Next, we examined the expression levels of mature miR-16 in patients with UM (TCGA cohort) according to the chromosome 3 copy number. Surprisingly, miR-16 expression was not altered by chromosome 3 monosomy in UM (Fig 1D). To strengthen these results, we used RT-qPCR to compare the miR-16 expression level in three UM cell lines with the miR-16 levels found in the 501Mel cell line (cutaneous melanoma). We had performed the latter in a previous study, obtaining an absolute quantification of miR-16 by Northern blot experiments (Gilot et al, 2017). These commercial cell lines harbour different mutations determined by Amirouchene-Angelozzi and colleagues and also by Jager and colleagues. MP41 is GNA11 mutated, but the second event is still unknown. Mel202 and 92-1 cell lines are GNAQ mutated, whereas the second event is the mutation of SF3B1 and EIF1AX, respectively (Amirouchene-Angelozzi et al, 2014; Jager et al, 2016). miR-16 is highly expressed in all three UM cell lines, and its expression seems independent of the chromosome 3 status in these selected cell lines. Normal human melanocytes have been used as controls (Fig 1E). Altogether, these results showed that the miR-16 expression level is not reduced in chromosome 3 monosomy UM tumors and cell lines. However, miRNA expression does not always correlate with miR-16 activity. Sequestration of miR-16 by coding and non-coding RNA, referred to as miRNA-sponges, can dampen the miRNA activity as we demonstrated in cutaneous melanoma (Gilot et al, 2017). Repression of miR-16 target mRNA is thus alleviated, promoting in fine tumor growth (Karreth & Pandolfi, 2013; Migault et al, 2017). We hypothesized that a comparable mechanism might mediate miR-16 inactivation in UM. To test this hypothesis, we first investigated the tumor suppressor activity of miR-16 in UM cells by elevating miR-16 expression levels. UM cell density decreased specifically after 72 h following transfection of synthetic miR-16 (Fig 1F–H), suggesting that miR-16 indeed acts as a tumor suppressor in human UM.
To identify the RNAs involved in miR-16 sequestration, and consequently the dysregulated target RNAs, we defined the miR-16 interactome (mRNA interacting with biotinylated miR-16) using RNA pull-down. We confronted this result with transcriptomic profiling in response to synthetic miR-16 transfection in UM cells that define the miR-16 targetome (MP41) (Fig 2A–D and Table S1A). To discard artefactual interactants due to nonspecific background inherent to all biotinylated experiments (Lal et al, 2011; Tan & Lieberman, 2016; Dash et al, 2018), we analyzed our data in two steps. First, we plotted the log fold change (logFC) expression after miR-16 transfection and the detection of these RNAs in pull-down using biotinylated miR-16 (Fig 2B). miR-16 interactants were arbitrarily defined (logFC < −0.5 or >0.5 and a number of reads superior to 100 in the pull-down assay). Thus, we defined two windows (b and c) containing, respectively, 476 and 497 potential miR-16 interactants. Second, we removed all highly detected RNAs (>500 reads) in the biotinylated miR-CTR condition, considering them as false-positive candidates. Finally, we obtained two groups of miR-16 partners. First, 327 miR-16 interactants for which expression levels decreased in response to miR-16 transfection, strongly suggesting that these RNAs (b’ window) correspond to miR-16 targets (targetome) in our model. Some of these miR-16 targets have already been identified as a miR-16 target in the literature, including Cyclin D1 (CCND1), Cyclin D3 (CCND3), and WEE1, validating our experimental workflow (Liu et al, 2008; Cai et al, 2012; Lezina et al, 2013). Second, we applied the same filter for the up-regulated RNAs and we obtained an additional cleaned list of 403 miR-16 interactants (window c’ in Fig 2B) (list available in Table S1A). Table S1. miR-16 interactome and signatures. The biological function of up-regulated miRNA interactants remains unclear in the literature even though they have already been highlighted by different teams (Vasudevan et al, 2007). Here, we postulated that down-regulated miR-16 interactants are “real miR-16 targets” and up-regulated miR-16 interactants might correspond to “potential miR-16 sponges” (Fig 2D). Because a miRNA-sponge (mRNA) should be highly expressed and contain non-canonical miRNA-binding site(s) avoiding its decay (Gilot et al, 2017), we focused on highly up-regulated miR-16 interactants (basal normalized expression level > 10) (window c’’ in Fig 2B), identifying 57 potential miR-16 sponges in UM (list available in Table S1A). As expected, 30% of down-regulated RNAs (miR-16 targets) contained predicted canonical miR-16–binding sites (microRNA response element [MRE]-16) (Fig 2D, E, and G) (Agarwal et al, 2015) and only 2% of the up-regulated miR-16 interactants did (Fig 2D and F), suggesting that miR-16 base-pairing to potential sponge RNAs might be non-canonical. To explain why only 30% of miR-16 targets display MRE-16 predicted by TargetScan 7.2, we further studied the miR-16–binding sites on down-regulated RNAs by examining the complete sequence of these RNAs and not only their 3′UTR using Cistrome SeqPos motif analysis. Interestingly, the most meaningful motif resembles the miR-16–binding site (motif #1: 3′-GCTGCTG-5′ [underlined sequence is complementary to miR-16 sequence: 5′_uAGCAGCac----_3′]). Of note, this motif is not retrieved exactly in up-regulated miR-16 interactants (potential sponge RNA) (Fig S1). However, motif #1, identified on sponge RNAs; -GCTG (or T or A) CT-, is quite similar to motif #1, identified on miR-16 targets, except for the nucleotide in position 5 (G, T, or A). This result suggests that a bulge may be created when the seed sequence of miR-16 binds to the sponge RNAs. This type of bulge is usually described to strongly reduce or abolish the RNA decay mediated by a miRNA (Agarwal et al, 2015; Kim et al, 2016a), in accordance with our hypothesis.
Before exploring the role of these miR-16 interactants, we verified that they were not cell-line restricted. Thus, using the same approach (synthetic miR-16 transfection), we validated 19 candidates in two other UM cell lines (Mel202 and 92-1) (Fig 3A and B). We observed a down-regulation of these miR-16 targets in all cell lines except MYB in the Mel202 cell line. We obtained comparable results in the HCT116 colon cell line in which almost all miRNAs are lost because of DROSHA KO (Luna et al, 2015), including endogenous miR-16 (Fig 3C). Altogether, these results suggest that the miR-16 targets identified in the MP41 cell line are highly conserved in the same cancer models (UM), despite the diversity of driver mutations and chromosome abnormal copy number that characterize these three cell lines. Moreover, the miR-16 targetome is, at least in part, common to other models such as those in the colon. Next, we investigated how miR-16 reduces melanoma cell survival/proliferation. Even though we confirmed that miR-16 targets cell cycle regulators such as CCND3 and WEE1 (Fig 3A), we investigated the biological consequences of the RNA decay of less-characterized RNA in UM. We thus performed depletions of four miR-16 targets (Angiomotin [AMOT], Transforming Acidic Coiled-Coil Containing Protein 1 [TACC1]; Nuclear receptor-binding protein [NRBP1]; Dna J Heat Shock Protein Family Hsp40 Member B4, and [DNAJB4]). We selected these candidates according to decreasing expression during the kinetic experiment (Fig 3B), MRE-16 identified in their 3′UTR, and the lack of a clear connection between these RNAs and UM. We showed that depletion of AMOT, TACC1, NRBP1, or DNAJB4 reduced cell density in UM cells (Fig 3D and E). Altogether, our results suggest that miR-16 reduces melanoma cell proliferation by targeting different essential pathways/processes, including cell cycle regulators (Fig 3F). It is tempting to postulate that the loss of miR-16 activity due to miR-16 sequestration could promote cell proliferation by derepressing these miR-16 targets.
Because the function of up-regulated miR-16 interactants is poorly studied, we first validated their miR-16–mediated increase in other cell lines (Mel202, 92-1 and HCT116 KO DROSHA) as done for miR-16 targets. For most of the tested RNA, we validated their increase after miR-16 transfection in at least one other cell line. Among them, some seem to be cell line specific (Fig 4A and B). In addition, 50% of the potential sponge mRNAs tested were still increased after miR-16 transfection in DROSHA knock-out cells in which almost all miRNAs, including miR-16, are lost, suggesting that miR-16 acts directly on these sponges rather than through competition with another miRNA involved in sponge decay. Next, we assessed the translational consequence of miR-16 binding on these up-regulated miR-16 interactants because miRNA binding on canonical binding sites commonly provokes a translation blockade and induces RNA decay via seed base-pairing (Bartel, 2004). Here, we focused our attention on glycogen phosphorylase B (PYGB), defined as our best miR-16 sponge candidate because of its high expression level in UM (Fig 2F) and its increased response to miR-16 transfection in three UM models (Fig 4A). We showed that both PYGB mRNA and protein increased after miR-16 transfection in three UM cell lines (Fig 4A and C). To elucidate the molecular mechanism, explaining the translation up-regulation mediated by miR-16, we looked for miR-16–binding sites on PYGB mRNA using the RNAhybrid webtool (Krüger & Rehmsmeier, 2006). It uses the energy needed to predict interaction between two RNAs. Two potential non-canonical miR-16–binding sites with high energy were found on PYGB mRNA (Fig 4D). To determine whether these two non-canonical miR-16–binding sites are involved in the PYGB protein up-regulation by miR-16, we cloned these sequences (sites 1 or 2, wild-type or mutated [WT or MUT]) fused with the luciferase coding sequence. The translation effectiveness of these chimeric RNAs was estimated by assessing luciferase activity. As a control, we used the luciferase coding sequence fused to canonical MRE-16 (from CCND1) (Fig 4E). As expected (Bonci et al, 2008), we found decrease in luciferase activity after miR-16 transfection for this canonical seed base-pairing. In contrast, the non-canonical miR-16–binding sites promoted higher luciferase activity compared with mutated sequences (Fig 4E and F). Altogether, our results strongly suggest that miRNA/RNA base-pairing determines RNA stability and the translation rate; and a non-canonical MRE can promote translation, in contrast to a canonical MRE. To further challenge the miR-16 sequestration hypothesis while preserving the stoichiometry between miR-16 and its interactome, we next depleted PYGB mRNA and quantified endogenous miR-16 targets (Fig 4G and H) selected as a function of: (i) a miR-16–dependent mRNA decay (Fig 3), (ii) presence of a predicted MRE-16 in their 3′UTR (Fig 2), and (iii) a decrease in MP41 cell density after their depletion (Fig 3D). Because the depletion of only one miR-16 sponge (PYGB) was followed by a moderate decrease in several miR-16 target RNAs (Fig 4G and H), it is tempting to conclude that miR-16 sequestration involves several RNAs with non-canonical MRE-16. This model of sequestration may explain why we identified 57 potential miR-16 sponges in UM (Fig 2B).
Our model is based on a constant level of miR-16. We investigated whether a high level of miR-16 sponges might be associated with a loss of canonical miR-16 activity and consequently associated with a poor OS of patients. We demonstrated that quantification of 57 miR-16 sponge candidates effectively predicted survival in UM patients (TCGA cohort), reflecting metastasis risk (Fig 5A). Unsupervised gene expression analysis identified two clusters: light and dark grey (cluster 2 and 1, respectively) (Fig 5A). These clusters are highly correlated with those defined by TCGA. Remarkably, the miR-16 expression level was comparable in the two groups, supporting the sponging hypothesis (Fig 5B). In accordance with our hypothesis, we showed that a high level of miR-16 sponges is associated with a dismal survival (Fig 5C) and that miR-16 targets are derepressed in cluster 1 (Figs 5C and S2). Altogether, these results indicate that miR-16 activity (assessed using miR-16 sponges and target expression levels) is a useful marker for clinicians, in contrast to miR-16 expression. Because 57 RNAs are too numerous to be exploited clinically, we developed a risk model (Luo et al, 2020) (Fig 6A and Table S2), identifying four RNAs useful for predicting the OS of patients with UM (signature S4: Figs 6B and S3). The S4 signature’s ability to predict survival was confirmed in an independent cohort (n = 63; GSE22138) (Laurent et al, 2011) (Fig 6C). Table S2. Sponges risk model. Taken together, our results demonstrated that abnormal (non-canonical) miR-16 activity is associated with a poor clinical outcome in UM.
Gene expression is fine-tuned by miRNA at the post-transcriptional level. Alteration of miRNA expression or activity is associated with numerous diseases. We also now know that miRNA sequestration is an important event. Thus, it seems crucial to quantify a miRNA activity as much as its expression in the assessment of the role of miRNA in cancer. Here, we characterize a molecular mechanism explaining the loss of tumor suppressor activity of miR-16 (loss of brake effect), which is associated with metastasis risk and poor OS in UM (Figs 5 and 6). Instead of promoting RNA decay of miR-16 targets such as cell cycle regulators (CCND3, CCND1, and WEE1), non-canonical miR-16 activity mediates the expression of pro-tumoral genes (acceleration effect). These include PTP4A3 and HTR2B (Laurent et al, 2011; Le-Bel et al, 2019; Onken et al, 2021). Canonical activity (mRNA decay) of the tumor suppressor miR-16 is impaired by miR-16 sequestration on non-canonical MRE-16. We identified, using complementary experiments, potential miR-16 sponge RNAs (defined as up-regulated miR-16 interactants). Importantly, we showed that non-canonical miR-16 binding on these mRNAs promotes their accumulation. Additional experiments are needed to explain this phenomenon. It is tempting to postulate that miR-16 on non-canonical MRE-16 might recruit FMR1 Autosomal Homolog 1 (FXR1), promoting RNA circularization and non-canonical translation (Vasudevan et al, 2007; Bukhari et al, 2016). This mechanism might explain the mRNA up-regulation in response to miR-16 binding and the increase in protein observed in PYGB. In addition, this circularization might thus increase the sponge activity of linear RNA because the most potent miRNA sponges are probably circRNAs (Guo et al, 2014). In accordance with this hypothesis, a recent study demonstrated that miRNAs loaded in Ago2 are enriched in the 3′UTR of several RNAs without inducing their decay. Authors have clearly demonstrated that MYC RNA levels are increased in response to miRNA binding (Chu et al, 2020). Altogether, our results suggest that non-canonical miR-16 activity led to gain-of-function of pro-tumoral genes such as PTP4A3 and HTR2B. These mRNAs are overexpressed in most UM cases associated with a poor clinical outcome, and could be targeted using antisense oligonucleotides. Thus, we suggest that miR-16 can exert pro- or anti-tumoral activity depending of its base-pairing to RNA. The current concept of competition between RNAs to bind miRNA is still a topic of debate (Smillie et al, 2018). Here, we showed that miR-16 sequestration is probably carried out by several RNAs in UM because single PYGB knock-down induces a modest decay of miR-16 targets. This is in accordance with the identification of 57 potential miR-16 sponges in UM. However, additional biochemical experiments are need to further characterize the miR-16 interactions with these potential miRNA sponges as well as the potential miRNA targets identified here. The clinical relevance of our results has been demonstrated using different UM cohorts. Our sponge signature (57 genes) and the signature S4 are therefore able to predict, with great accuracy, which patients will develop metastasis, as well as the PC1 signature established from single-cell RNA sequencing results (Pandiani et al, 2021; Strub et al, 2021). It is of interest that few genes are common to both of these two effective signatures. For our signature, all 57 genes are potential miR-16 interactants. To the best of our knowledge, this is the first time that a predictive signature has been composed of genes belonging to the same mechanism (miR-16) in UM. In conclusion, our results highlight the need to update the current models explaining miRNA activity and its role in gene regulation and diseases.
MP41 cell line was obtained from Decaudin’s laboratory at Curie Institute, Paris, France. Mel202 and 92.1 cell lines were obtained from European Collection of Authenticated Cell Cultures (ECACC) (Merck). 501Mel cell line was obtained from American Type Culture Collection (ATCC). HCT116 WT and HCT116 KO DROSHA (Kim et al, 2016b) cell lines were obtained from Korean Collection for Type Cultures (KCTC), Microbial Resource Center. All cell lines were maintained in humidified air (37°C, 5% CO2). UM cell lines were maintained in RPMI-1640 medium (Gibco, Thermo Fisher Scientific) supplemented with 20% FBS (EurobioScientific) and 1% penicillin–streptomycin antibiotics (Gibco, Thermo Fisher Scientific). 501Mel was maintained in RPMI-1640 medium (Gibco, Thermo Fisher Scientific) supplemented with 10% FBS (EurobioScientific) and 1% penicillin–streptomycin (PS) antibiotics (Gibco, Thermo Fisher Scientific). HCT116 cell lines were maintained in McCoy’s 5A (Gibco, Thermo Fisher Scientific) supplemented with 10% FBS (EurobioScientific) and 1% penicillin–streptomycin antibiotics (Gibco, Thermo Fisher Scientific). All cell lines have been routinely tested for mycoplasma contamination (Mycoplasma contamination detection kit; rep-pt1; InvivoGen).
Sequences are available in Table S3. All siRNAs and synthetic mimics were transfected at 66 nM using Lipofectamine RNAiMAX (Thermo Fisher Scientific) according to the manufacturer’s instructions. For cell density assay: 80,000 cells for 92-1 and HCT116 KO DROSHA, HCT116 WT, and 10,000 for MP41 and 12,000 for 92-1 cells were seeded in 96-well plates, in quadruplicates. For RNA and proteins analysis, 250,000 cells were seeded in six-well plates. Cells were harvested 72 h after transfection (or kinetic). All siRNAs were purchased from IDT DNA. All mimics were purchased from Dharmacon. Table S3. Sequences of primers, siRNAs and antibodies.
Lentiviral particles carrying shRNA vectors targeting human PYGB mRNA (shPYGB, TL310025V), and scramble shRNA (shCTR, TR30021V) were purchased from Origen. Lentiviral production was performed as recommended (https://www.epfl.ch/labs/tronolab/) using HEK 293T cells. After infection, cells were maintained in the presence of puromycin 1 μg/ml for selection (Invivogen).
RNA was isolated from cell samples using NucleoSpin RNA Plus kit (Macherey-Nagel) and quantified using a NanoDrop 1000 Spectrophotometer (Thermo Fisher Scientific). Reverse transcription was performed with the High Capacity cDNA Reverse Transcription kit (Applied Biosystems). Quantitative PCR was performed on 1 ng cDNA, in 384-well plates using the SYBR Green PCR Master Mix (Applied Biosystems) with the QuantStudio 7 Flex Real-Time PCR System (Applied Biosystems). RNA levels were normalized against human GAPDH. Relative amounts of transcripts were determined using the ΔΔ − Ct method and human GAPDH transcript level was used as an internal control for each cell line sample. miRNA was isolated using mirVana miRNA isolation kit (Ambion; Life Technologies). Reverse transcription was performed with the TaqMan microRNA Reverse Transcription Kit (Applied Biosystems) with the Megaplex RT Primers Pool A v2.1 (Applied Biosystems). Quantitative PCR was performed on 1 ng cDNA, in 384-well plates using the TaqMan Gene Expression Master Mix (Applied Biosystems) with the QuantStudio 7 Flex Real-Time PCR System (Applied Biosystems). Relative amounts of transcripts were determined using the Δ Δ − Ct method and human RNU6B was used as an internal control for each cell line sample. The primers were used are described in Table S3.
Cell density was measured by methylene blue colorimetric assay (Gilot et al, 2017). Briefly, cells were fixed for 30 min with 70% ethanol. Then, fixed cells were dried and stained 30 min with 1% methylene blue dye in borate buffer. Plates were washed 3 times with fresh tap water and 100 μl of 0.1N HCl per well were added. Plates were analyzed with a spectrophotometer at 620 nm.
Experiments were performed as previously described (Gilot et al, 2017). Membranes (GE HealthCare) were probed with suitable antibodies and signals were detected using the Amersham Imager 680 (Thermo Fisher Scientific). The antibodies are described in Table S3. Uncropped Western blots are available in Source data.
Total RNAs were quantified using a NanoDrop 1000 Spectrophotometer (Thermo Fisher Scientific) and RNA integrity (RIN > 8) was evaluated using RNA nano-chips on the Agilent 2100 Bioanalyzer Instrument (Agilent Technologies). Libraries generation and sequencing experiments have been conducted as previously reported (Corre et al, 2018).
These experiments were performed on MP41 cell according to the protocol published by Judy Lieberman’s laboratory (Tan & Lieberman, 2016) but with minor modifications. 15 millions of MP41 cells were seeded in 3 × 150-mm dishes (5 millions each) and were transfected using Lipofectamine 2000 (Thermo Fisher Scientific) (42 μl per dish) the next day with 100 nM of biotinylated miR-16 or miR-CTR (Dharmacon). Next, they were harvested ∼24 h post transfection. Cells from the three dishes were treated separately. Meanwhile, magnetic beads (Streptavidine Dynabeads M-280 DYNAL; Thermo Fisher Scientific) were washed and blocked according to the protocol (Tan & Lieberman, 2016). Cell lysate and washed beads were incubated for 4 h at 4°C on a rotating agitator. All next steps: the precipitation and the purification of coupled RNA was performed according to the protocol. We pooled the three same conditions (from the three transfected plates) in the end of the RNA purification. Purified RNA was quantified using a NanoDrop 1000 Spectrophotometer (Thermo Fisher Scientific) followed by the sequencing.
RNA sequencing of pull-downed RNA was performed by Novogene according to its RIP sequencing protocol (Illumina PE150/Q30≥80%).
The miRNA-binding sites on RNA (MRE) were predicted by webtool TargetScan 7.2 (Agarwal et al, 2015) and RNAhybrid (Rehmsmeier et al, 2004) both available online. Non-canonical MREs have been identified using RNAhybrid and Cistrome SeqPos motif analysis (Liu et al, 2011). From RNAseq data, 903 genes were found to be down-regulated (with fold change 1.5). miR-16 peaks falling within those genes were called following the procedure described by Sérandour et al (2012). The resulting bed file containing 504 peaks was used for de novo motif search with the SeqPos tool from Cistrome (Liu et al, 2011), which looked for enriched DNA motifs within these DNA regions. Annotated genes associated with de novo motifs were identified. To assess the survival prognosis capabilities of the (selected genes or sponges/targets), we performed univariate Cox analyses of the expression data for these genes, with OS as a dependent variable. Patients were divided into two categories according to the median expression of each gene: low expression (below median) and high expression (above median). The Kaplan–Meier method was used to estimate the survival distributions. Log-rank tests were used to test the difference between survival groups. Analyses were carried out with the survival R package.
We used the TCGA-UVM cohort downloaded from the Xena Browser as a training cohort and the GEO dataset GSE22138 as a validation cohort. We trained an optimal multi-gene survival model based on the expression of the sponges in the training cohort by selecting survival-associated genes with the rbsurv R package using 1,000 iterations. Briefly, this package allows a sequential selection of genes based on the Cox proportional hazard model and on maximization of log-likelihood. To increase robustness, this package also selects survival-associated genes by repetition (1,000 times) of a separation between the training and validation sets of samples. Risk scores were determined using classical Cox model risk formulae with a linear combination of the gene expression values weighted by the estimated regression coefficients. The risk cutoff was set to the median of the linear predictor. The Kaplan–Meier method was used to estimate the survival distributions. Log-rank tests were used to test the difference between survival groups. Analyses were carried out with the survival and survivalROC R packages.
Data are presented as mean ± SD unless otherwise specified, and differences were considered significant at a P-value of less than 0.05. Comparisons were performed using bilateral Student test (with non-equivalent variances). All statistical analyses were performed using Prism 8 software (GraphPad) or Microsoft Excel software. OS was estimated using the Kaplan–Meier method. Univariate analysis using the Cox regression model or log-rank test, as specified, was performed to estimate hazard ratios and 95% confidence intervals. All experiments were performed three or more times independently under similar conditions, unless otherwise specified in the figure legends (raw data available in Table S4). Table S4. Raw data.
Further information and requests for resources and reagents should be directed to and will be fulfilled by David Gilot ([email protected]). All unique/stable reagents generated in this study are available from the Lead Contact with a completed Materials Transfer Agreement. All other data supporting the findings of this study are available from the corresponding author on reasonable request. The human melanoma data set (UM, IlluminaHiSeq) was derived from the TCGA Research Network: http://cancergenome.nih.gov. The data set derived from this resource that supports the findings of this study is available at https://genome-cancer.ucsc.edu. mRNAseq and RIPseq data that support the findings of this study have been deposited in the Gene Expression Omnibus under accession code GSE180399 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE180399) and ArrayExpress under accession code E-MTAB-10940 (https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-10940/). | true | true | true |
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PMC9554105 | Chao Niu,Min Li,Yongchong Chen,Xiaoying Zhang,Shan Zhu,Xin Zhou,Lei Zhou,Zhaozhi Li,Jianting Xu,Ji-fan Hu,Yufeng Wang,Jiuwei Cui | LncRNA NCAL1 potentiates natural killer cell cytotoxicity through the Gab2-PI3K-AKT pathway | 28-09-2022 | noncoding RNA,natural killer cell,epigenetics,cytotoxicity,immune therapy | Natural killer (NK) cells perform immune surveillance functions in tumors. The antitumor effects of NK cells are closely related to tumor occurrence and development. However, the molecular factors that determine NK cell antitumor activity remain to be characterized. In the present study, we identified a novel long noncoding RNA (lncRNA), NK cell activity-associated lncRNA 1 (NCAL1), and investigated its function in NK cells. NCAL1 was primarily located in NK cell nuclei, where it functioned by activating Gab2, a scaffold protein with an essential role in immune cells. Gab2 positively regulated the killing activity of NK cells. Mechanistically, NCAL1 upregulated Gab2 epigenetically by binding to the Gab2 promoter, which decreased methylation, recruited the transcription factor Sp1, and increased H3K4me3 and H3K27ac levels in the Gab2 promoter. Furthermore, NCAL1 enhanced the cytotoxicity of NK cells toward tumor cells through the Gab2-PI3K-AKT pathway. Thus, NCAL1 potentiates NK cell cytotoxicity and is a promising therapeutic target to improve NK cell therapy. | LncRNA NCAL1 potentiates natural killer cell cytotoxicity through the Gab2-PI3K-AKT pathway
Natural killer (NK) cells perform immune surveillance functions in tumors. The antitumor effects of NK cells are closely related to tumor occurrence and development. However, the molecular factors that determine NK cell antitumor activity remain to be characterized. In the present study, we identified a novel long noncoding RNA (lncRNA), NK cell activity-associated lncRNA 1 (NCAL1), and investigated its function in NK cells. NCAL1 was primarily located in NK cell nuclei, where it functioned by activating Gab2, a scaffold protein with an essential role in immune cells. Gab2 positively regulated the killing activity of NK cells. Mechanistically, NCAL1 upregulated Gab2 epigenetically by binding to the Gab2 promoter, which decreased methylation, recruited the transcription factor Sp1, and increased H3K4me3 and H3K27ac levels in the Gab2 promoter. Furthermore, NCAL1 enhanced the cytotoxicity of NK cells toward tumor cells through the Gab2-PI3K-AKT pathway. Thus, NCAL1 potentiates NK cell cytotoxicity and is a promising therapeutic target to improve NK cell therapy.
Natural killer (NK) cells are important immune cells involved in innate immunity. These cells act as the first line of defense against cancer cells and tumor virus infection (1, 2). Further, NK cells can directly kill tumor cells. Because of nonspecific effects, the natural killing activity of NK cells does not require antigen participation and has no major histocompatibility complex restrictions (3, 4). NK cells also play potent immunomodulatory roles by interacting with other immune cells to regulate the immune state and function in the body (1, 5). Clinical studies demonstrated that adoptive immunotherapy using NK cells has potential applications for malignant tumors and exerts effects on various solid tumors and hematological malignancies (6). Therefore, NK cell therapy is a promising immunotherapy strategy for treating various cancers (7, 8). Although NK cell activity controls tumor growth, NK cells are susceptible to many immunosuppressive mechanisms in the tumor microenvironment (9, 10). Ways to improve the antitumor effect of NK cells should be a focus of research on NK cell therapy in the future (8). Long noncoding RNAs (lncRNAs) are noncoding RNAs that are more than 200 nucleotides long (11). Most transcripts produced by mammalian genome sequences are lncRNAs (12). Previous studies showed that lncRNAs play important roles in epigenetic regulation, the cell cycle, cell differentiation, and many other activities. Thus, lncRNAs have recently gained attention in genetic research (13–15). Although research on lncRNAs has made rapid progress, the functions of most lncRNAs remain unclear (16), particularly in NK cells, in which only two lncRNAs have been reported (17, 18). lnc-CD56 positively correlates with CD56 expression in primary human NK cells and differentiates NK cells from human hematopoietic progenitor cells (17). lncRNA-GAS5 promotes NK cell activity against gastric cancer by reducing miR-18a (18). Determining lncRNA functions in NK cells would improve our understanding of NK cell-mediated antitumor mechanisms. We previously found that the histone deacetylase inhibitor, valproic acid, can reduce NK cell cytotoxicity (19). In this study, we performed next-generation sequencing (NGS) on activated human NK cells treated with valproic acid to identify lncRNAs that regulate NK cell activity. We identified a previously uncharacterized lncRNA, NK cell activity-associated lncRNA 1 (NCAL1), as a potential factor that regulates NK cell-mediated cytotoxicity. We aimed to investigate the mechanism underlying the role of NCAL1 in NK cells.
Peripheral blood mononuclear cells (PBMCs) were isolated from the blood of six healthy donors using Ficoll (cat: 1114547; Axis-Shield PoC AS, Oslo, Norway) gradient density centrifugation. This procedure was approved by the Ethics Committee of the First Hospital of Jilin University (2017–022). All participants provided informed consent to participate in this study. Primary NK cells were isolated from human PBMCs using a MACSxpress NK Cell Isolation Kit (cat: 130-098-185; Miltenyi Biotec, Bergisch Gladbach, Germany) and were cultured in Aly505 medium (cat: 01400P10; Cell Science & Technology Institute, Inc., Yamagata, Japan) containing 10% autologous serum and 600 IU/mL interleukin-2 (cat: 130-097-743; Miltenyi Biotec). B cells, T cells, and γδ T cells were sorted with FACS Aria II (BD Biosciences, San Jose, CA, USA). NK92MI cells (cat: CL-0533; Procell Life Science & Technology Co., Ltd., Wuhan, China) were cultured in α-minimum essential medium (cat: 1749161; Gibco, Grand Island, NY, USA) containing 2 mM L-glutamine (cat: 25030081; Gibco), 1.5 g/L sodium bicarbonate (cat: S5761; Sigma-Aldrich, St. Louis, MO, USA), 0.2 mM inositol, 0.1 mM β-mercaptoethanol (cat: M6250, Sigma-Aldrich), 0.02 mM folic acid (cat: F8758, Sigma-Aldrich), 12.5% horse serum (cat: 16050122; Gibco), and 12.5% fetal bovine serum (cat: SFBE; Natocor, Córdoba, Argentina). Gab2-overexpressing NK92MI cells were cultured with 5 μM of the PI3K inhibitor pictilisib (cat: S1065; Selleckchem, Houston, TX, USA) for 24 h.
Full-length NCAL1 was obtained using 3′ and 5′ RACE, which was performed using a Marathon cDNA Amplification Kit (cat: 634913; TaKaRa, Shiga, Japan). The primers used for RACE are listed in Table 1 .
Full-length NCAL1 was cloned into the pCDH-CMV-MCS-copGFP vector (CD511B-1) with an N-terminal start codon (ATG) and 3×Flag tag. The plasmid was transfected into HEK293T cells as previously described (20). Flag fusion GFP served as a positive control. After 48 h, immunoblotting was performed to detect the Flag tag (cat: 14793; Cell Signaling Technology, Danvers, MA, USA).
RNA fluorescence in situ hybridization was performed as previously reported (21). Briefly, NK92MI cells were fixed on glass slides by centrifugation. The cells were washed twice with RNase-free phosphate-buffered saline (PBS). Cells on the glass slide were fixed using 4% paraformaldehyde in PBS on ice for 10 min. Freshly prepared 0.5% TritonX-100 was added to the slide, which was incubated on ice for 10 min. After dehydration and drying with ethanol, 10 µL of denatured digoxigenin-labeled RNA probe (50 ng total) was added dropwise onto the slide. The probe contains exon 4 and parts of exons 3 and 5 of NCAL1 ( Supplementary Figure 1C ). Then, the slide was placed in a wet box and hybridized overnight at 42°C. After washing, an anti-digoxin-fluorescein antibody (cat:11207741910; Roche Diagnostics, Mannheim, Germany) was added and incubated for 4 h. The slides were washed three times with PBS for 5 min each. DAPI (20 ng/mL; cat: C1002; Beyotime, Shanghai, China) was added dropwise onto the slide and incubated for 10 min at 24°C. After washing three times with PBS for 5 min each, the slides were imaged using an FV3000 confocal microscope (Olympus, Tokyo, Japan). The probe sequence information is listed in Table 1 .
RNA was isolated from the nucleus and cytoplasm of NK92MI cells using a nucleocytoplasmic separation kit (cat: AM1921; Invitrogen, Carlsbad, CA, USA). Polymerase chain reaction (PCR) was performed to detect NCAL1 in the nucleus and cytoplasm. β-Actin and U6 were used as controls. The primer information is listed in Table 1 .
NCAL1- and Gab2-overexpressing plasmids were constructed using pCDH-CMV-MCS-EF1-copGFP and were used for lentiviral packaging. HEK293T cells were transfected with these plasmids as previously described (20).
Primary NK cells or NK92MI cells were seeded in six-well plates (cat: 703001; NEST Biotechnology Co., Ltd, Wuxi, China) at 500,000 cells/well with 2 mL of medium containing 8 μg/mL polybrene. Cells were infected with different lentiviruses at a multiplicity of infection (MOI) of 10, centrifuged at 2000 rpm for 2 h at 37°C, and cultured at 37°C. The medium was replaced with fresh medium every 2 days, beginning 12–14 h after infection.
A panel of siRNAs for NCAL1 and Gab2 was designed and synthesized by Viewsolid Biotech (Beijing, China). The primer sequences are listed in Table 1 . NK92MI cells were transfected with 200 nM siRNAs using Cell Line Nucleofector Kit R (cat: VCA-1003; Lonza, Basel, Switzerland).
Total RNA was extracted using an RNA extraction kit (cat: K0732; Thermo Fisher Scientific, Waltham, MA, USA). cDNA was obtained using a cDNA synthesis kit (cat: 11123ES10; Yeasen, Shanghai, China). Quantitative PCR (qPCR) was performed using 2×RealStar Green Fast Mixture (cat: A303-05; GenStar, Beijing, China) in a CFX384 Real-Time System C1000 Touch Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA). The primers used for qPCR are listed in Table 1 .
NK92MI cells overexpressing NCAL1 were sequenced at the Novogene Bioinformatics Institute (Beijing, China).
NK92MI and K562 cells were incubated at a ratio of 5:1 at 37 °C in 5% CO2. Mouse monoclonal antibody against human CD107a-APC (5 μL/test, cat: 560664, lot: 9183690; BD Biosciences) or isotype control antibody was added to the cells. After incubation for 1 h, 0.1% GolgiStop (cat: 555028; BD Biosciences) was added. After another 3 h of incubation, the cells were collected and stained with mouse monoclonal antibodies against human CD56-FITC (5 μL/test, cat: 562794, lot: 0010250; BD Biosciences). The cells were washed once with PBS and analyzed using a FACSAria II flow cytometer (BD Biosciences). The data were analyzed using FlowJo software version 10 (Tree Star, Inc., Ashland, OR, USA).
NK cell-mediated cytotoxicity was analyzed by performing a calcein-release test as previously described (22). Briefly, 100 μL of K562 (target) cells labeled with calcein-AM (cat: C326; Dojindo Laboratories, Kumamoto, Japan) at a concentration of 5 × 104 cells/mL were added to 96-well plates. Then, 100 μL of NK (effector) cells per well were added at effector-to-target cell ratios of 1.25:1, 2.5:1, 5:1, and/or 10:1. Minimum release was achieved by incubating the target cells in medium alone, and maximum release was achieved after treatment with 0.46% Triton X-100. All experiments were performed in triplicate. The plates were incubated at 37°C in 5% CO2. After 4 h, 100 μL of supernatant was transferred into black 96-well plates and evaluated using a Synergy HT Microplate Reader (BioTek Instruments, Winooski, VT, USA). Cytotoxicity was calculated using the following formula: specific lysis (%) = [(experimental release – minimum release)/(maximum release – minimum release)] × 100%.
RNA reverse transcription-associated trap (RAT) was performed as previously reported (23, 24). NK92MI cells were fixed with formaldehyde and were treated with a hypotonic solution (10 mM HEPES pH 7.9, 1.5 mM MgCl2, 10 mM KCl, 0.4% NP40) to lyse the cell membrane and isolate the nuclei. Reverse transcription was carried out using biotin-labeled dNTP Mix (cat: R0191; Thermo Fisher Scientific) with specific primers complementary to NCAL1 ( Table 1 ). The nucleus was lysed by ultrasonication, and biotinylated lncRNA-cDNA/chromatin DNA complexes were pulled down with streptavidin Dynabeads (cat: 11205D; Invitrogen). Protease K (cat: AM2542; Thermo Fisher Scientific) was added to degrade the protein and genomic DNA interacting with NCAL1.
Genomic DNA from NCAL-overexpressing NK92MI cells was isolated using a DNeasy Blood and Tissue kit (cat: 69504; Qiagen GmbH, Hilden, Germany). The DNA was modified with bisulfate using an EZ DNA Methylation-Gold kit (cat: D5005Z; ZYMO Research, Los Angeles, CA, USA). DNA was amplified using specific primers for Gab2 ( Table 1 ). The PCR products were cloned using a pJET PCR Cloning kit (cat: K1231, Thermo Fisher Scientific). Ten independent clones from each sample were sequenced to determine the DNA methylation status.
Chromatin immunoprecipitation (ChIP) assays were performed using a Pierce Agarose ChIP Kit (cat: 26156; Thermo Fisher Scientific). Specific trimethyl-H3K4 antibody (10 μL/10 μg chromatin; cat: 9727s, lot: 10; Cell Signaling Technology), acetyl-H3K27 antibody (20 μL/10 μg chromatin; cat: 4353s, lot: 8; Cell Signaling Technology), and Sp1 antibody (5 μL/10 μg chromatin; cat: PA5-29165, lot: RK2287676, Invitrogen) were used to determine the promoter profile of Gab2. Normal rabbit IgG was used as a negative control. DNA was extracted and analyzed using qPCR with specific primers ( Table 1 ) targeting the Gab2 promoter. Enrichment was calculated using the following formula: Input % = 2 [Ct (NCAL1/vector group) – (Ct (input of NCAL1/vector group) – Log2 (input dilution factor of NCAL1/vector group))].
Proteins from different groups of NK92MI cells were extracted and quantified using a BCA Protein Assay Kit (cat: PA115-02; Tiangen Biotech Co., Ltd., Beijing, China). Western blotting analysis was performed using mouse monoclonal antibodies against pAKT, AKT, PI3K, and pPI3K (dilution=1:1000; cat: 4060S, lot: 16; cat: 9272S, lot: 28; cat: 4257S, lot: 7; cat: 4228S, lot: 5; respectively, Cell Signaling Technology) and β-Actin (cat: AF5003, lot: 123020210325; Beyotime); appropriate secondary antibodies; and an ECL kit (Beijing Labgic Technology Co., Ltd., Beijing, China).
Data were analyzed by two-tailed paired/unpaired t-tests and one/two-way analysis of variance (ANOVA) using GraphPad Prism 8 software (GraphPad, Inc., San Diego, CA, USA).
The molecular factors that control NK cell activity against tumor cells are not completely understood. Using RNA-seq, we identified the lncRNA NCAL1 as a potential factor that correlates with NK cell activity. NCAL1 is located on the short arm of chromosome 2 and has 17 exons ( Supplementary Figure 1A ). Using a cDNA end RACE assay, we characterized the full-length NCAL1 sequence ( Supplementary Figure 1B ). Another lncRNA, CYTOR, is near NCAL1 on chromosome 2 but differs from NCAL1 except for the first exon ( Supplementary Figure 1C ). A lncRNA was considered a novel isoform if it shared some exons with an annotated gene. Therefore, we believe that NCAL1 is a novel lncRNA (GenBank accession number: BankIt2596396 Seq1 ON863928). Since CYTOR is located close to NCAL1, shares a first exon, and has several isoforms, we hypothesized that NCAL1 may also have several isoforms. More importantly, we found that the expression of NCAL1 in primary NK cells was significantly higher than that in the other immune cells ( Figure 1A ). To explore the functional role of NCAL1, we evaluated the functional relevance of NCAL1 expression in primary NK cells and NK92MI cells. NCAL1 was expressed under the control of the CMV promoter in a lentiviral vector (pCDH). An empty vector was used as the negative control. After lentiviral transfection, primary NK cells were collected for real-time qPCR and cytotoxicity assays. Primary NK cell activity significantly increased when NCAL1 was overexpressed ( Figure 1B ). Next, we examined whether NCAL1 could activate the killing activity of NK92MI cells. NCAL1 was overexpressed in NK92MI cells using a lentivirus system with GFP. Forty-eight hours post-transfection, most NK92MI cells expressed GFP ( Supplementary Figure 2A ). Then, GFP expression in NK cells was confirmed using flow cytometry, with the proportion of GFP reaching as high as 45.6% ( Supplementary Figure 2B ). When NCAL1 was overexpressed ( Figure 1C ), the killing activity of NK92MI cells was significantly increased at all effector-to-target ratios (1.25:1, 25.49% vs. 35.34%, p < 0.01; 2.5:1, 38.13% vs. 46.29%, p < 0.01; and 5:1, 53.98% vs. 67.54%, p < 0.001) ( Figure 1D ). Moreover, CD107a expression in NCAL1-overexpressing NK92MI cells was significantly higher than that in the control group (74.85% vs. 63.90%, p < 0.01; mean fluorescence intensity: 4337 vs. 3188, p < 0.01) ( Figures 1E, F ).
To further explore the effect of NCAL1 on NK cell-mediated cytotoxicity, we used small interfering RNA (siRNA) to knock down NCAL1 expression in NK92MI cells. The siRNAs were located in exons 3 and 5 of NCAL1, where NCAL1 can be spliced ( Supplementary Figure 1C ). After knocking down NCAL1 ( Figure 2A ), the ability of NK cells to kill tumor cells decreased at different effector-to-target ratios (1.25:1, 29.91% vs. 14.14%, p < 0.001, 29.91% vs. 23.08%, p < 0.05; 2.5:1, 43.61% vs. 28.30%, p < 0.001, 43.61% vs. 36.60%, p < 0.01; 5:1, 55.07% vs. 36.81%, p < 0.001, 55.07% vs. 44.80%, p < 0.001) ( Figure 2B ). Additionally, CD107a expression in NK92MI cells was decreased after knocking down NCAL1 ( Figures 2C, D ).
Most lncRNAs do not encode proteins. To examine the protein-coding function of NCAL1, full-length NCAL1 was cloned into the pCDH vector with the N-terminal start codon ATG and Flag tag. The plasmid was then transfected into HEK293T cells. After 48 h, immunoblotting was performed to detect the Flag tag, which confirmed that NCAL1 had no protein-coding function ( Figure 3A ). lncRNA functions are associated with their subcellular localization (25). Cytoplasmic and nuclear RNA isolation assays and RNA fluorescence in situ hybridization indicated that NCAL1 was primarily located in the nucleus ( Figures 3B, C ).
To explore the mechanism by which NCAL1 regulates NK activity, we collected NCAL1-overexpressing NK92MI cells and used RNA-seq to identify the downstream targets of NCAL1 in NK cells. NCAL1 overexpression in NK92MI cells upregulated 162 genes and downregulated 75 genes. Differentially expressed genes that are possibly related to NK cell function were selected as candidate genes. qPCR was performed to verify the candidate genes. qPCR results showed that NCAL1 overexpression significantly upregulated Gab2 ( Supplementary Figure 3 ; Figure 4A ). Gab2 gene and protein expression were examined using qPCR and western blotting. We found that Gab2 mRNA and protein expression were significantly increased by NCAL1 overexpression ( Figures 4B, C ). Consistently, siRNA-mediated NCAL1 knockdown significantly decreased Gab2 mRNA and protein expression ( Figures 4D, E ). These results indicate that NCAL1 positively regulates Gab2 gene expression and increases its protein expression. To evaluate the crosstalk between Gab2 and NK cell cytotoxicity, a Gab2-overexpressing plasmid was constructed and transfected into NK92MI cells using a lentivirus transfection system. Gab2 mRNA and protein were successfully expressed in NK92MI cells ( Figures 4F, G ). We observed that NK92MI cells overexpressing Gab2 showed a stronger killing effect on tumor target cells compared to the control group at different effector-to-target ratios ( Figure 4H ). Furthermore, CD107a expression in Gab2-overexpressing NK92MI cells was significantly higher than that in the control group ( Figures 4I–K ). These results indicate that Gab2 expression is positively correlated with NK cell-mediated cytotoxicity.
To characterize the role of NCAL1 in Gab2 regulation, we mapped NCAL1 targets genome-wide using a RAT approach ( Supplementary Figure 4 ). NK92MI cells were collected, and NCAL1 was labeled in situ with biotin-dCTP using stringent reverse transcription with three NCAL1-specific complementary primers. Random primers were used as negative controls. Then, biotin–NCAL1 cDNA chromatin complexes were isolated using streptavidin beads. We observed DNA binding to NCAL1 using RAT. We then designed primers targeting the regions upstream and downstream of the Gab2 transcriptional start site (TSS) and performed qPCR. DNA enrichment was mainly concentrated at the Gab2 TSS (Sites II and III in Figure 5A ), suggesting that NCAL1 may epigenetically regulate the Gab2 promoter. Using the UCSC database (http://genome.ucsc.edu/), we identified methylation islands in the Gab2 promoter region ( Figure 5B ). NCAL1 significantly induced Gab2 promoter demethylation ( Figures 5C, D ). There were several potential Sp1 transcription factor binding sites around the CpG islands in the Gab2 promoter region, as predicted by the Alibaba 2.1 software (http://gene-regulation.com/pub/programs/alibaba2/index.html) ( Figure 5E ). Therefore, we investigated whether NCAL1 affected the binding of Sp1 to the Gab2 promoter. ChIP-qPCR indicated that NCAL1 substantially increased Sp1 binding to potential binding sites around the CpG islands of the Gab2 promoter ( Figure 5F ). These data suggest that NCAL1 promotes Gab2 expression by inducing DNA demethylation and promoting Sp1 binding at the Gab2 promoter. Furthermore, we determined that H3K27ac and H3K4me3 were enriched at the TSS of Gab2, based on the data from the UCSC database. To determine the effect of NCAL1 on H3K27ac and H3K4me3 enrichment at the Gab2 promoter, NCAL1 was overexpressed in NK92MI cells. ChIP was carried out using antibodies against H3K27ac and H3K4me3. Three pairs of primers around the TSS of Gab2 were selected ( Figure 5G ), and qPCR was performed to detect H3K27ac and H3K4me3 near the Gab2 TSS. NCAL1 enhanced H3K27ac and H3K4me3 levels at the Gab2 TSS ( Figures 5H, I ). Collectively, these results suggest that NCAL1 promotes Gab2 gene expression by modifying the epigenotypes in the Gab2 promoter.
To analyze the mechanism by which NCAL1 regulates NK92MI cell-mediated cytotoxicity, we examined the PI3K-AKT signaling pathway, which is closely related to Gab2 and NK cell activation (26–28). We found that pAKT and pPI3K expression significantly increased after overexpressing NCAL1 and Gab2 ( Figure 6A ). PI3K-AKT activation was weakened when Gab2 was knocked down in NCAL1-overexpressing NK92MI cells ( Figure 6B ). Furthermore, inhibition of PI3K with pictilisib suppressed AKT phosphorylation ( Figure 6C, D ) and inhibited the killing activity of Gab2-overexpressing NK cells ( Figure 6E ). These results suggest that NCAL1 improves the NK cell-mediated cytotoxicity through the Gab2-PI3K-AKT axis.
NK cells are important for natural immunity. These cells are involved in immune surveillance and can identify and eliminate mutated cells in the body, thereby preventing cancer onset and progression (29, 30). lncRNAs perform diverse biological functions (31), such as regulating gene expression at the transcript level, thus participating in many biological processes such as chromatin modification, chromosome silencing, genome imprinting, and transcriptional activation (13, 32–34). Although thousands of lncRNAs have been identified in the human transcriptome (35), most of their functions remain uncharacterized (36). Previously, we discovered that valproic acid could inhibit the killing ability of NK cells (19). NGS was performed to identify lncRNAs in NK cells that are altered by treatment with valproic acid ( Supplementary Figure 5 ). By analyzing the NGS data, we identified an unknown lncRNA on chromosome 2 called NCAL1. We observed that NCAL1 expression is higher in NK cells than in the other immune cells. Further experiments indicated that NCAL1 is positively correlated with NK cell-mediated cytotoxicity. Interestingly, after primary NK cells were treated with the S protein of SARS-CoV-2, NCAL1 expression decreased, and NK cell activity toward K562 cells decreased (unpublished data). These results indicate that NCAL1 may play an important role in the killing ability of NK cells. lncRNA localization in cells is closely related to their function (37). NCAL1 is mainly found in the nucleus, indicating that it regulates NK cell function by modifying gene transcription. The overexpression of NCAL1 in NK cells upregulated Gab2 expression. Gab2 is a scaffold protein with multiple functions in immune cell signaling (38). In mast cells, Gab2 is important for degranulation and cytokine release (27). Further, Gab2 can inhibit T cell receptor-mediated signaling events (39). However, the function of Gab2 in human NK cells remains unclear. NCAL1 may partly enhance the cytotoxicity of human NK cells by upregulating Gab2 expression. Indeed, we found that when Gab2 is overexpressed in human NK cells, NK cell activity toward tumor cells significantly increases, indicating that Gab2 positively regulates the killing activity of human NK cells. However, Gab2 does not disrupt NK cell development and function in mice (40). Considering the striking differences in Gab2 functions between human and mouse NK cells, our findings suggest that the role of Gab2 is species-specific. Gab2 contains multiple tyrosine phosphorylation sites (41). After phosphorylation, these sites can recruit signaling molecules, including molecules that contain SH2 domains, mainly SHP2 and PI3K (28). We found that the PI3K-AKT pathway is activated when either Gab2 or NCAL1 is overexpressed in NK cells. PI3K-AKT axis activation is closely related to the cytotoxicity of NK cells (26, 42). The activation of PI3K-AKT was suppressed when Gab2 was knocked down in NCAL1-overexpressing NK92MI cells. A PI3K inhibitor suppressed AKT phosphorylation and inhibited the cytotoxicity of NK cells overexpressing Gab2. Therefore, NCAL1 may activate the PI3K-AKT axis and increase the cytotoxicity of NK cells by upregulating Gab2 expression. Furthermore, we found that NCAL1 binds to the Gab2 promoter and promotes its demethylation. However, further studies are needed to determine how NCAL1 induces Gab2 promoter demethylation. Our results predict several potential Sp1 transcription factor-binding sites and enriched H3K27ac and H3K4me3 levels in the Gab2 promoter region. ChIP experiments showed that NCAL1 enriched Sp1, H3K4me3, and H3K27ac levels at the Gab2 promoter. These results indicate that NCAL1 binds to the Gab2 promoter region and regulates Gab2 gene transcription through an epigenetic mechanism ( Figure 6F ). Therefore, we speculate that NCAL1 might reduce Gab2 methylation, which loosens the associated chromatin and promotes increased Sp1, H3K27ac, and H3K4me3 levels. In conclusion, our study identified a new lncRNA NCAL1 that is highly enriched in and is positively related to the cytotoxicity of NK cells. NCAL1 increases the killing activity of NK cells by enhancing Gab2 expression, which subsequently activates the PI3K-AKT pathway. These results indicate that NCAL1 may serve as a potential target to improve the killing ability of NK cells and the efficacy of NK cell therapy.
The original contributions presented in the study are included in the article/ Supplementary Material . The sequencing data presented in the study are deposited in the GEO repository, accession number GSE211801. Further inquiries can be directed to the corresponding authors.
The studies involving human participants were reviewed and approved by The Ethics Committee of the First Hospital of Jilin University. The patients/participants provided their written informed consent to participate in this study.
JC, XinZ, J-FH, and YW conceived and supervised the study. CN and ML designed and carried out part of the experiments and drafted the entire manuscript. XiaZ, YC, SZ, LZ, ZL, and JX carried out part of the experiments. All authors contributed to the article and approved the submitted version.
This work was supported by grants from the National Key Research and Development Program of China (grant numbers 2020YFA0707704 and 2018YFA0106902), the Innovative Program of the National Natural Science Foundation of China (82050003), the National Natural Science Foundation of China (grant numbers 31700764, 81972684, 81922055, 31871297, 81874052, and 81702589), a project funded by the China Postdoctoral Science Foundation (grant number 2021M691208), the Jilin Provincial Science and Technology Department (grant numbers 20200201180JC, 20210303002SF, 20200602032ZP, and 20190303146SF), the Jilin Provincial Education Department (grant number JJKH20221060KJ), the Jilin Provincial Development and Reform Commission (grant number 2021C10), the Changchun Science and Technology Bureau (grant number 21ZGY28), and the China Guanghua Foundation & First Hospital of Jilin University (grant numbers JDYYGH2019004 and JDYYGH2019012).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9554183 | Yanping Hu,Yangcan Chen,Jing Xu,Xinge Wang,Shengqiu Luo,Bangwei Mao,Qi Zhou,Wei Li | Metagenomic discovery of novel CRISPR-Cas13 systems | 11-10-2022 | Bioinformatics,Cell biology | Metagenomic discovery of novel CRISPR-Cas13 systems
Dear Editor, CRISPR-Cas systems are crucial adaptive immune components of microbial resistance against the invasion of mobile genetic elements (MGEs) and serve as the core of current cutting-edge genome engineering technologies. Unlike the widely applied Cas9 or Cas12 DNA editing tools in present use, Cas13 is an RNA-guided programable RNA-targeting single effector system that enables gene manipulation at the transcriptional level. At present, only four subtypes of Cas13 have been identified. An expanded catalog of CRISPR-Cas13 systems can provide phylogenetic insights and may offer opportunities for the development of novel RNA-editing tools. By mining bulk metagenomic data (> 10 TB) from various environments, we identified hundreds of orthologs of known and novel Cas13 systems in this study, the latter of which could be classified into five novel subtypes based on protein sequence similarity. Notably, the novel Cas13 systems discovered in this study can be developed into efficient RNA editors and expand the RNA-editing toolbox. In this study, we developed a computational pipeline for the de novo identification of novel Cas13 proteins (Fig. 1a). Initially, putative CRISPR arrays were identified from sequenced data. Then, 20 kb regions of DNA flanking the CRISPR arrays were extracted for predicting the open reading frames (ORFs). Proteins with more than 400 residues were selected for further analyses. A Cas13 library consisting of profile hidden Markov models (HMMs) of all known Cas13a, Cas13b, Cas13c, and Cas13d protein sequences in the NCBI database was subsequently constructed. We proposed that the use of this library, which includes the features of all known Cas13 proteins, could maximize the possibility of discovering potential novel Cas13 proteins from uncharacterized protein sequences. The identified proteins that were devoid of two higher eukaryotes and prokaryotes nucleotide-binding (HEPN) domains were assumed to be incomplete and less likely to be active and were therefore not selected for further analyses. Novel Cas13 proteins were further defined based on the results of phylogenetic analyses. In order to test the accuracy of the bioinformatics pipeline developed herein, the pipeline was initially used to search for previously discovered Cas13 proteins in the NCBI’s prokaryotic database. As expected, previously discovered Cas13 systems were successfully identified using the pipeline (Supplementary Fig. S1a). We next searched for novel Cas13 proteins from metagenomic databases containing data from host-associated, aquatic, and soil environments (Supplementary Tables S1–S6). Compared to the commonly accessible data in the NCBI database, metagenomic data enables the identification of a greater number of novel Cas13 proteins (Fig. 1b, c and Supplementary Fig. S1b–d), demonstrating the importance and necessity of metagenomic mining. The protein sequences were next subjected to phylogenetic analyses, and the results demonstrated that the novel Cas13 proteins clustered into seven new branches distinct from those of the known subtypes (Fig. 1d). Of these seven clades, two clades, namely, Cas13Bt-A and Cas13Bt-B, with an approximate average sequence length of 800 amino acids (aa), could be clustered into the same clades as the previously discovered Cas13X, Cas13Y, and Cas13bt proteins (Fig. 1e). The remaining five clades were designated as Cas13e to Cas13i, with protein lengths ranging from 740 to 1300 aa (Fig. 1d–f). Specifically, the average lengths of Cas13e and Cas13f-i proteins were ~800 and 1100 aa, respectively (Fig. 1f). Analysis of the CRISPR locus revealed that with the exception of Cas13g, all the novel Cas13 subtypes discovered herein lacked conserved adaptation genes, including Cas1 and Cas2 (Supplementary Fig. S1e). We next analyzed the features in the CRISPR array. Like other CRISPR-Cas13 systems, the average lengths of the spacers and direct repeats (DRs) of the novel Cas13 systems are 30 and 36 nt, respectively (Supplementary Fig. S2a, b). Multiple sequence alignment of the DRs revealed that they are highly conserved and have similar predicted secondary RNA structures, which were similar to the characteristics of the DR sequences of previously identified Cas13a, Cas13b, and Cas13d systems (Supplementary Fig. S2a, b). Using the spacer sequences as a query, the potential targets of natural crRNA from the CRISPR locus were investigated by searching the IMG/VR, Genbank-Phage, and Ref-Plasmid databases. Positive hits indicated that these CRISPR-Cas13 systems could be active in hosts and defend against foreign MGEs. We next analyzed the features of the sequences of the novel Cas13 proteins. Multiple sequence alignment of these novel proteins of each subtype revealed that their HEPN domains were highly conserved, and the RNXXXH motif was most conserved, accounting for ~74% of all RXXXXH motifs (Supplementary Fig. S3a, b). We observed that only Cas13a, Cas13c, and Cas13d possessed an elongated N-terminal domain (NTD) (Fig. 1g). The existing structure of Cas13 revealed that Cas13a and Cas13d contain an NTD at the N-terminus, which is the least conserved region in Cas13 proteins and forms a binding channel for the DR region; however, this domain is absent in Cas13b. Interestingly, while Cas13a, Cas13c, and Cas13d systems use mature crRNAs with a 5′-DR sequence for effective RNA interference, we noticed that the mature crRNAs of Cas13b, Cas13Bt-A, and Cas13Bt-B systems contained a 3′-DR sequence. Based on this consistency, we speculated whether the existence of the NTD domain of the novel CRISPR-Cas13 systems could be used for predicting the optimal configuration of the crRNA for effective RNA inference. Using this hypothesis, we deduced that the novel Cas13e, Cas13f, Cas13g, Cas13h, and Cas13i systems, with a 3′-DR sequence in the crRNA, would be more efficient in cleaving RNA (Supplementary Fig. S4a). We employed a mammalian cell-based mCherry disruption system for evaluating the RNA cleavage activity of the novel Cas13 proteins (Supplementary Fig. S4b). Consistent with our speculation, we observed that the use of crRNAs with 3′-DR sequences, and not 5′-DR sequences, enabled the effective disruption of the mCherry mRNA by Cas13e1, Cas13f1, Cas13g1, Cas13h1, and Cas13i1 (Fig. 1h and Supplementary Fig. S4a). Collectively, the lack of the NTD domain in Cas13 can reflect on the structural differences of its cognate mature crRNA, and this rule can be used when employing novel Cas13 proteins with little known structural information for RNA editing in mammalian cells. The clinical application of Cas13-based RNA-editing systems continues to be challenging at present, partly due to the fact that the large size of RNA editors exceeds the packaging capacity of adeno-associated virus (AAV) vectors. The hypercompact Cas13 proteins discovered in this study can aid in overcoming this limitation. In order to identify novel small Cas13 systems with high activity, the mCherry reporter system was used for initial screening (Supplementary Fig. S4b, c). The mCherry signals were substantially reduced using the novel Cas13 proteins (Supplementary Fig. S4d). To verify the endogenous gene knockdown activity of the novel Cas13 proteins, two sites in the ANXA4 gene were selected for testing in HEK293T cells (Fig. 1i). Of note, Cas13e3 achieved the highest knockdown activity among all the Cas13 systems screened herein, with the efficiency at the two sites being 92% and 84% (Fig. 1i). We, therefore, selected Cas13e3 for further characterization owing to its high efficiency and the ultrasmall protein size (767 aa). In order to investigate the optimal length of the spacer for Cas13e3 editing, we tested two different crRNAs for targeting the mCherry mRNA, with spacers of lengths ranging from 5 to 50 nt (Supplementary Fig. S5a). Cas13e3 achieved the highest average knockdown efficiency at the two selected sites when the 27-nt spacer was used (Supplementary Fig. S5a). The 27-nt spacer was therefore used for subsequent experiments. We next sought to determine the protospacer flanking sequence (PFS) requirement of Cas13e3. The results of screening revealed no PFS preference for Cas13e3 (Supplementary Fig. S5b). Besides, we observed that fusion with the nuclear localization signal (NLS) could increase the knockdown efficiency of Cas13e3 (Supplementary Fig. S5c). In order to investigate the knockdown efficiency of Cas13e3 on a larger scale, a total of 15 crRNAs targeting five genes were tested (Fig. 1j). We also tested the activities of Cas13X.1 and RfxCas13d at the same sites for comparison. Notably, we observed that Cas13e3 exhibited robust knockdown activity that was comparable to that of Cas13X.1 and RfxCas13d (Fig. 1j, k). We further investigated the specificity of Cas13e3 on a genome-wide scale. A total of 102, 323, and 133 differentially expressed genes were detected using RNA-Seq for the Cas13X.1, RfxCas13d, and Cas13e3 systems, respectively (Supplementary Fig. S6a), indicating that the specificity of Cas13e3 was comparable to that of Cas13X.1, while its off-target effect was lower than that of RfxCas13d (Supplementary Fig. S6a). In order to compare the collateral RNA cleavage activities of Cas13X.1, RfxCas13d, and Cas13e3, the fluorescence intensity of enhanced green fluorescent protein (EGFP) was measured when targeting the mCherry mRNA. Notably, collateral RNA cleavage activities were not detected for Cas13X.1 and Cas13e3, while RfxCas13d showed dramatic trans-cleavage activity for EGFP transcripts (Supplementary Fig. S6b). In conclusion, these results demonstrated that Cas13e3 is a hypercompact RNA editor with high interference efficiency and low collateral activity. In this study, we developed a computational pipeline to sensitively discover novel CRISPR systems by constructing a library containing comprehensive Cas13 features. By mining metagenomic data, we identified five novel Cas13 clades. We verified that several of the novel Cas13 families have RNA-degrading capacity in mammalian cells. Importantly, the novel Cas13e3 protein discovered in this study is an ultracompact Cas13 protein, and can be developed into an efficient transcriptome editor in mammalian cells. The novel systems identified in this study substantially increase the diversity of CRISPR-Cas13 systems and largely expand the programmable RNA-editing toolbox.
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PMC9554441 | Michael P. Jeffrey,Chad W. MacPherson,Thomas A. Tompkins,Julia M. Green-Johnson | Lacticaseibacillus rhamnosus R0011 secretome attenuates Salmonella enterica serovar Typhimurium secretome-induced intestinal epithelial cell monolayer damage and pro-inflammatory mediator production in intestinal epithelial cell and antigen-presenting cell co-cultures | 28-09-2022 | macrophage inhibitory factor (MIF),Lacticaseibacillus rhamnosus R0011 secretome,Transwell,Salmonella enterica serovar Typhimurium secretome,intestinal epithelial cell,cytokines,antigen-presenting cell (APC),monocyte | Certain lactic acid bacteria (LAB) are associated with immune modulatory activities including down-regulation of pro-inflammatory gene transcription and expression. While host antigen-presenting cells (APCs) and intestinal epithelial cells (IEC) can interact directly with both pathogenic and commensal bacteria through innate immune pattern recognition receptors, recent evidence indicates indirect communication through secreted molecules is an important inter-domain communication mechanism. This communication route may be especially important in the context of IEC and APC interactions which shape host immune responses within the gut environment. We have previously shown that the Lacticaseibacillus rhamnosus R0011 secretome (LrS) dampens pro-inflammatory gene transcription and mediator production from Tumor Necrosis Factor-α and Salmonella enterica serovar Typhimurium secretome (STS)-challenged HT-29 IECs through the induction of negative regulators of innate immunity. However, many questions remain about interactions mediated through these bacterial-derived soluble components and the resulting host immune outcomes in the context of IEC and APC interactions. In the present study, we examined the ability of the LrS to down-regulate pro-inflammatory gene transcription and cytokine production from STS-challenged T84 human IEC and THP-1 human monocyte co-cultures. Cytokine and chemokine profiling revealed that apically delivered LrS induces apical secretion of macrophage inhibitory factor (MIF) and down-regulates STS-induced pro-inflammatory mediator secretion into the apical and basolateral chambers of the T84/THP-1 co-culture. Transcriptional profiling confirmed these results, as the LrS attenuated STS challenge-induced CXCL8 and NFκB1 expression in T84 IECs and THP-1 APCs. Interestingly, the LrS also reversed STS-induced damage to monolayer transepithelial resistance (TER) and permeability, results which were confirmed by ZO-1 gene expression and immunofluorescence visualization of ZO-1 expression in T84 IEC monolayers. The addition of a MIF-neutralizing antibody abrogated the ability of the LrS to reverse STS-induced damage to T84 IEC monolayer integrity, suggesting a novel role for MIF in maintaining IEC barrier function and integrity in response to soluble components derived from LAB. The results presented here provide mechanistic evidence for indirect communication mechanisms used by LAB to modulate immune responses to pathogen challenge, using in vitro approaches which allow for IEC and APC cell communication in a context which more closely mimics that which occurs in vivo. | Lacticaseibacillus rhamnosus R0011 secretome attenuates Salmonella enterica serovar Typhimurium secretome-induced intestinal epithelial cell monolayer damage and pro-inflammatory mediator production in intestinal epithelial cell and antigen-presenting cell co-cultures
Certain lactic acid bacteria (LAB) are associated with immune modulatory activities including down-regulation of pro-inflammatory gene transcription and expression. While host antigen-presenting cells (APCs) and intestinal epithelial cells (IEC) can interact directly with both pathogenic and commensal bacteria through innate immune pattern recognition receptors, recent evidence indicates indirect communication through secreted molecules is an important inter-domain communication mechanism. This communication route may be especially important in the context of IEC and APC interactions which shape host immune responses within the gut environment. We have previously shown that the Lacticaseibacillus rhamnosus R0011 secretome (LrS) dampens pro-inflammatory gene transcription and mediator production from Tumor Necrosis Factor-α and Salmonella enterica serovar Typhimurium secretome (STS)-challenged HT-29 IECs through the induction of negative regulators of innate immunity. However, many questions remain about interactions mediated through these bacterial-derived soluble components and the resulting host immune outcomes in the context of IEC and APC interactions. In the present study, we examined the ability of the LrS to down-regulate pro-inflammatory gene transcription and cytokine production from STS-challenged T84 human IEC and THP-1 human monocyte co-cultures. Cytokine and chemokine profiling revealed that apically delivered LrS induces apical secretion of macrophage inhibitory factor (MIF) and down-regulates STS-induced pro-inflammatory mediator secretion into the apical and basolateral chambers of the T84/THP-1 co-culture. Transcriptional profiling confirmed these results, as the LrS attenuated STS challenge-induced CXCL8 and NFκB1 expression in T84 IECs and THP-1 APCs. Interestingly, the LrS also reversed STS-induced damage to monolayer transepithelial resistance (TER) and permeability, results which were confirmed by ZO-1 gene expression and immunofluorescence visualization of ZO-1 expression in T84 IEC monolayers. The addition of a MIF-neutralizing antibody abrogated the ability of the LrS to reverse STS-induced damage to T84 IEC monolayer integrity, suggesting a novel role for MIF in maintaining IEC barrier function and integrity in response to soluble components derived from LAB. The results presented here provide mechanistic evidence for indirect communication mechanisms used by LAB to modulate immune responses to pathogen challenge, using in vitro approaches which allow for IEC and APC cell communication in a context which more closely mimics that which occurs in vivo.
Interactions between IECs and APCs help to shape the immune outcomes of bidirectional host-microbe communication at the gut mucosal interface. While IECs provide a physical barrier at the external interface of the intestinal lumen, they are also important mediators of host-microbe communication by integrating microbial-derived signals to the underlying APC populations (Peterson and Artis, 2014; Goto, 2019). As the primary sensors of microbial activity in the gut environment, IECs have the capacity to induce and influence antimicrobial and immunoregulatory activity of underlying APCs through cytokine and mediator production induced by signal transduction events following IEC PRR recognition of microbial components. Due to the constant barrage of microbial signals, IECs must tightly regulate their activation in order to maintain a state of homeostasis and reduce hyperresponsiveness to the normal gut microbiota (Burgueno and Abreu, 2020). For this reason, TLR expression is often limited to the basolateral side of polarized IECs, limiting the extent of interactions with microbial components found within the luminal contents of the intestine. For example, TLR5, which is responsible for recognizing bacterial flagella, is typically limited to the basolateral side of polarized IECs (Gewirtz et al., 2001). This enables IECs to respond to flagellated bacteria only if there is a breakdown of the epithelial barrier or translocation of the bacterium across the epithelial barrier, necessitating the need for a robust inflammatory response from the surrounding immune cell population to clear out the invading bacteria. The consequences of TLR recognition of microbial contents can also be dependent on whether the ligand is recognized on the apical or basolateral side of polarized IECs (Abreu, 2010). TLR9, which recognizes unmethylated CpG DNA sequences, is expressed on both the apical and basolateral side of polarized IECs. When TLR9 is activated on the apical surface of IECs, there is a muted response with the activation of genes involved in the regulation of NF-κB signaling, whereas basolateral recognition of CpG DNA induces the activation of classical NF-κB signaling (Lee et al., 2006), reinforcing the importance of examining immune outcomes in the context of polarized IECs and spatial compartmentalization of PRR-induced signaling within the gut. IECs express tight junction proteins including the occludins, claudins, zonula occludens (ZO), and junctional adhesion molecules which work in concert to prevent the paracellular transport of intestinal luminal contents into the basolateral side of the epithelium (Gunzel and Yu, 2013; Suzuki, 2013). These proteins are tightly regulated and are key cellular players in the maintenance of normal barrier integrity and function (Karczewski and Groot, 2000; Harhaj and Antonetti, 2004; Marchiando et al., 2010). As such, perturbations in their activity can lead to the breakdown of the gut epithelial barrier resulting in the activation of dysregulated immune activity within the underlying APC population and the potential for dissemination of luminal contents and bacteria into systemic circulation. Certain pro-inflammatory cytokines, such as IFN-γ, can act to increase intestinal barrier permeability by reducing ZO-1 expression and localization (Scharl et al., 2009), while some gut-associated pathogens, such as S. enterica serovar Typhimurium, can also produce virulence factors which selectively disrupt ZO-1 and other tight junction proteins allowing for their translocation across the intestinal barrier (Tafazoli et al., 2003; Boyle et al., 2006). Commensal microorganisms and LAB have been shown to strengthen epithelial barrier integrity, a mechanism believed to be used by these bacteria to enhance their capacity for host colonization, and to antagonize the detrimental impacts of certain gut-associated pathogens on the gut epithelium (Ohland and Macnaughton, 2010; Madsen, 2012). Although most studies examining the impacts of gut-associated bacteria on gut epithelial barrier integrity have focused on direct interactions between live bacteria and IECs, some have suggested a role of microbial-derived metabolites and soluble components in this context. For example, E. coli Nissle 1917 conditioned media increased Caco-2 IEC monolayer integrity (Stetinova et al., 2010) and secreted peptides from Bifidobacterium infantis reversed TNF-α and IFN-γ-induced IEC barrier damage (Ewaschuk et al., 2008). In vitro approaches to study the interactions between epithelial cells and APCs have relied on the use of Transwell cell culture inserts. These cell culture inserts allow for the examination of gut barrier integrity and function by measuring the transport of apically delivered ions and other macromolecules across a monolayer of IECs grown on a microporous membrane (Donato et al., 2011). To achieve this, IECs are cultured until a polarized monolayer is formed within the Transwell insert, creating distinct apical, and basolateral compartments in vitro. IEC barrier function and permeability can then be readily studied following cell challenge by measuring the transepithelial electrical resistance (TER) and the flux of a fluorescently labeled sugar of known molecular weight across the IEC monolayer (Harhaj and Antonetti, 2004). T84 human IECs are a widely used cell line for in vitro study of IECs, and do not easily differentiate into a heterogenous cell population with altered phenotypic characteristics following polarization into a confluent monolayer, making them an ideal tool for studying IEC barrier function and permeability in response to cell challenge (Dharmsathaphorn and Madara, 1990; Hillgren et al., 1995; Donato et al., 2011). To facilitate the study of IEC and APC interactions with bacteria, APCs can be cultured in the basolateral chamber and bacteria and their soluble components can be administered into the apical chamber following IEC monolayer formation to simulate interactions found within the gut-mucosal interface. This approach provides a useful in vitro system to study the dynamics of microbe-mediated immune communication in the context of IEC and APC interactions. Several chemokines and cytokines are involved in intestinal epithelial barrier disruption by intestinal pathogens, including IFN-γ, TNF-α, and CXCL8 (Hansen et al., 2013; Andrews et al., 2018; Paradis et al., 2021). Certain cytokines also play key roles in intestinal epithelial barrier maintenance and repair, including MIF (Vujicic et al., 2018, 2020), and we have previously found that the LrS induces MIF production by IECs (Jeffrey et al., 2020b). In addition, the innate immune regulators ATF3 and DUSP1/MKP-1 are involved in intestinal epithelial barrier regeneration and maintenance, the latter through regulation of the p38MAPK signaling pathway (Chang et al., 2015; Talavera et al., 2015; Glal et al., 2018; Sheng et al., 2020) while NFκB1 expression is implicated in intestinal barrier disruption (Al-Sadi et al., 2010; McDaniel et al., 2016). We have previously shown that the LrS has the capacity to modulate immune outcomes in both human IECs and APCs with transcriptional and cytokine/chemokine profiling revealing context-dependent and cell-type specific immunomodulatory activity of the LrS, including induction of negative regulators of innate immunity ATF3 and DUSP1 (Jeffrey et al., 2020a,b). However, many questions remain about the LrS in regulating host immune outcomes in the context of IEC and APC interactions. To date, most studies examining the effects of LAB and their secreted products have focused on host immune responses using a single cell type (IEC or APC) in vitro and therefore do not necessarily reflect the impact these bacteria may have on interactions between these key cell types involved in innate immunity. Recent evidence also suggests that the effects of LAB and their secreted factors can be very different when tested in co-cultures of human IECs and APCs (Bermudez-Brito et al., 2015). As such, the aim of this study was to examine the immunomodulatory impacts of the LrS using co-cultures of human IECs and APC, focusing on cytokines and chemokines involved in gut epithelial barrier disruption and maintenance, markers of gut barrier integrity, and on expression of genes involved in regulating innate immune activity and barrier integrity at the intestinal barrier level. Analysis of the effects of the LrS in Transwell systems using co-cultures of human IECs and APCs provides an approach to further investigate the potential role of microbial secretomes in modulating host immune activity at the gut mucosal interface.
Lyophilized Lactobacillus rhamnosus R0011 was obtained from RIMAP (Montreal, Quebec, Canada). The LrS was prepared as previously described (Jeffrey et al., 2018). Briefly, bacteria were grown in deMan, Rogosa and Sharpe (MRS) medium (Difco, Canada) at 37°C for 17 h in a shaking incubator and then diluted in non-supplemented RPMI-1,640 medium and allowed to further propagate for an additional 23 h under the same conditions. Both the bacterial culture and controls were centrifuged at 3,000 × g for 20 min and filtered through a 0.22 μm filter (Progene, Canada) to remove any bacteria. The filtered supernatant samples were also subjected to size fractionation using < 10 kDa Amicon Ultra—15 centrifugal filter (EMD Millipore, MA, USA). For preparation of the STS, bacteria were propagated overnight in tryptone soya broth (Oxoid) in a shaking incubator at 37°C. Overnight cultures were centrifuged at 3,000 × g for 20 min at 4°C and filtered through a 0.22 μm filter and the secretome was stored at −80°C.
The T84 human colorectal carcinoma cell line was obtained from the American Type Culture Collection (ATCC, #CCL-248) and was maintained in DMEM/F-12 medium supplemented with 10% bovine calf serum and 0.05 mg/mL gentamicin (Sigma-Aldrich, MO, USA) and were grown in 75 cm2 tissue culture flasks (Greiner-Bio-One, NC, USA) at 37°C, 5% CO2 in a humidified incubator (Thermo Fisher Scientific, MA, USA) as described previously (Jeffrey et al., 2018). T84s IECs were enumerated and viability determined using Trypan Blue following sub-culturing. Cells were then resuspended in complete culture medium (DMEM/F-12 medium supplemented with 10% bovine calf serum and 0.05 mg/mL gentamicin) and 1.0 × 106 cells were seeded into 12-well Millicell hanging cell culture inserts with a pore size of 0.4 μM (EMD Millipore, MA, USA). To obtain polarized confluent monolayers, seeded T84 IECs were incubated at 37°C, 5% CO2 in a humidified incubator for 7 days, or until a minimum TER of 1,000 Ωcm2 as described previously (Sherman et al., 2005). T84 IEC cell culture medium was aspirated and replaced with fresh non-supplemented (no calf serum) DMEM/F12 medium containing the LrS (30%v/v), the STS (1% v/v), or a combination of these secretome challenges in the apical chamber of the hanging cell culture and THP-1 human monocyte cells were then added to the basolateral chamber at a concentration of 1 × 106 cells/mL for 24 h. These secretome concentrations have been previously shown to have immunomodulatory activity without negative impacts to cellular viability (Jeffrey et al., 2020b). For some challenges, cells were also cultured with an antibody specific for human MIF (AF-289-PB) (0.05 μg/mL) (R&D Systems) or with goat IgG isotype controls (AB-108-C) (0.05 μg/mL) (R&D Systems). This anti-MIF antibody has been used successfully to block the activity of MIF produced by IECs (Man et al., 2008). Following challenge, supernatants were collected from both the apical and basolateral sides of the Transwell inserts. TER measurements were done in triplicate using the Millicell ERS-2 Voltohmmeter (Millipore Sigma, MA, USA) to determine changes in epithelial monolayer integrity compared to controls and initial readings. Total RNA was also harvested after exposure to the various challenges from both T84 IECs and THP-1 human monocytes using the phenol-based TRIzol method of RNA extraction (Chomczynski, 1993) following manufacturer’s protocols (Thermo Fisher Scientific, MA, USA). Briefly, 2 mL of TRIzol reagent was added to each culture flask to lyse the IEC. Cell culture homogenates were added to Phase Lock Gel-Heavy tubes for phase separation of total RNA. Total extracted RNA was then purified using the RNeasy Plus Mini Kit (Qiagen, Hildon, Germany). The purity and quality of RNA was determined using a BioDrop Duo Spectrophotometer.
To determine the impact of the LrS or the STS on the permeability of T84 IEC monolayers, the flux of FITC-dextran across the epithelial monolayer was determined. Following cell challenge, T84 monolayers were washed with Hank’s Balanced Salt Solution (HBSS) (Millipore Sigma). Following washing, HBSS was added into the apical and basolateral chambers of the hanging cell culture insert and allowed to equilibrate for 30 min in a 37°C, 5% CO2 humidified incubator. The HBSS in the apical chamber was then replaced with HBSS containing 1 mg/mL of 4 kDa FITC-dextran (Millipore Sigma) and allowed to incubate for 1 h. Following incubation, a sample from the basolateral chamber was taken and placed into a black 96-well plate and fluorescence was quantified using a Synergy HT Microplate Reader (BioTek Instruments) set to 485/20 excitation and a 535/20 emission filter pair and a PMT sensitivity of 55. A FITC-dextran standard was used to quantify the concentration of FITC-dextran crossing the epithelial monolayer. This was repeated every hour for a total of 6 h and the transepithelial flux was determined by taking the average concentration of FITC-dextran and dividing by the surface area of the hanging cell culture insert; this was expressed as nM/cm2/h (Sanders et al., 1995).
DNase-treated RNA (1 μg) from controls and each challenge were reverse transcribed with Superscript IV following manufacturer’s protocols as previously described (Macpherson et al., 2014). Reverse-transcribed cDNA was diluted 1:4 prior to amplification and 2.5 μL of diluted cDNA was used with SsoAdvanced Universal SYBR Green Supermix (Bio-Rad, CA, USA) in RT-qPCR. Gene-specific primers for targets identified as being potentially important in LrS-mediated impacts on IEC and THP-1 monocyte activity as described previously were used (Table 1; Jeffrey et al., 2020a,b). An initial incubation of 5 min at 95°C was performed, followed by 40 cycles consisting of template denaturation (15 s at 95°C) and one-step annealing and elongation (30 s at 60°C), with a Bio-Rad CFX Connect instrument (Bio-Rad, CA, USA). Four biological replicates were analyzed for each gene tested, and fold change expression levels were normalized to the expression levels of two reference genes for T84 IECs (RPLPO and B2M) and THP-1 monocytes (RPL37A and ACTB) and negative controls using Bio-Rad CFX Manager 3.1 software.
Changes in T84 IEC monolayer integrity following challenge with the LrS or the STS was visualized by staining ZO-1 with an anti-ZO-1 monoclonal antibody (ZO1-1A12) conjugated with Alexa Fluor 488 (Thermo Fisher Scientific), following manufacturing protocols. Briefly, following conditioning, cells were fixed with 3.75% formaldehyde, permeabilized with 0.5% Triton X-100, and stained with anti-ZO for 2 h at room temperature. Cells were counter-stained and mounted using ProLong™ Diamond Antifade Mountant with DAPI (Thermo Fisher Scientific Cat #: P36966).
Cell culture supernatants from both the apical and basolateral chambers of the hanging cell culture inserts were collected following 24 h of challenge in order to allow sufficient time for the production of key inflammatory cytokines and chemokines and to determine directionality of cytokine release. Cytokine and chemokine profiling was performed using the Bio-Plex Pro™ 40-Plex Human Chemokine Panel (Bio-Rad #171ak99mr2) and the Bio-Plex Pro™ Human Inflammation Panel 1, 37-Plex (Bio-Rad #171AL001M). All 40 chemokines (CCL21, BCA-1/CXCL13, CTACK/CCL27, ENA-78/CXCL5, Eotaxin/CCL11, Eotaxin-2/CCL24, Eotaxin-3/CCL26, Fractalkine/CX3CL1, GCP-2/CXCL6, GM-CSF, Gro-α/CXCL1, Gro-β/CXCL2, I-309/CCL1, IFN-υ, IL-1β, IL-2, IL-4, IL-6, IL-8/CXCL8, IL-10, IL-16, IP-10/CXCL10, I-TAC/CXCL11, MCP-1/CCL2, MCP-2/CCL8, MCP-3/CCL7, MCP-4/CCL13, MDC/CCL22, MIF, MIG/CXCL9, MIP-1α/CCL3, MIP-1δ/CCL15, MIP-3α/CCL20, MIP-3β/CCL19, MPIF-1/CCL23, SCYB16/CXCL16, SDF-1α + β/CXCL12, TARC/CCL17, TECK/CCL25, TNF-α) or 37 cytokines [APRIL/TNFSF13, BAFF/TNFSF13B, sCD30/TNFRSF8, sCD163, Chitinase-3-like 1, gp130/sIL-6Rβ, IFN-α2, IFN-β, IFN-γ, IL-2, sIL-6Rα, IL-8, IL-10, IL-11, IL-12 (p40), IL-12 (p70), IL-19, IL-20, IL-22, IL-26, IL-27 (p28), IL-28A/IFN-λ2, IL-29/IFN-λ1, IL-32, IL-34, IL-35, LIGHT/TNFSF14, MMP-1, MMP-2, MMP-3, Osteocalcin, Osteopontin, Pentraxin-3, sTNF-R1, sTNF-R2, TSLP, TWEAK/TNFSF12] were multiplexed on the same 96-well plate. Chemokine/cytokine standards were serially diluted and chemokine profiling from all cell challenges was done following manufacturer’s instructions (Bio-Rad, CA, USA) with 4 biological replicates. Quality controls were also included to ensure the validity of the concentrations that were obtained. The Bio-Plex Manager™ software was used to determine the concentration of the analytes within each sample using the generated standard curves and concentration was expressed in pg/mL (concentration in range). Statistical analysis was done using GraphPad Prism’s (Version 8) one-way analysis of variance (ANOVA) and Tukey’s multiple comparison test when the ANOVA indicated significant differences were present. All data are shown as the mean pg/mL ± standard error of the mean (SEM). Z-scores were determined and visualized using R version 4.0.0 and package Bioconductor to determine the overall impact of each challenge on cytokine and chemokine production from T84 IEC and THP-1 monocyte co-cultures.
Differential cell-surface marker expression of CD74 on T84 IECs challenged with the LrS, STS, LrS, and STS or medium controls was determined using a BD Accuri C6 flow cytometer. Following challenge, 1 × 106 cells were resuspended in D-phosphate buffered saline (D-PBS) and cells were stained with the viability dye 7-AAD (Tonbo, 13–6,993) for 10 min on ice while protected from light. Cells were washed with 1 mL of cell staining buffer (CSB) (4% calf serum, 5 mM EDTA in D-PBS) and centrifuged for 5 min at 400 × g (4°C). Immediately following viability staining, non-specific Fc-mediated interactions were blocked by the addition of 100 μL of blocking buffer [10% calf serum (heat inactivated) in D-PBS] to the cell suspension for 10 min. Anti-human CD74 (BioLegend, clone LN2) was added to the cell suspension followed by incubation on ice and protected from light for 30 min. Cells were washed with CSB as described above, resuspended in 100 μL of fixation buffer (4% paraformaldehyde-PBS) and incubated for 30 min at room temperature protected from light. Data acquisition was done using the BD Accuri Plus flow cytometer and corresponding software package. 30,000 viable cells (as determined by incorporation of 7-AAD viability dye [Tonbo 13–6,993)] were acquired for each experiment and subsequent analysis was done using FlowJo v. 10.
Cytokine and chemokine profiling of IEC and APC co-cultures was done to determine whether apically delivered LrS and STS could alter functional immune outcomes in co-cultures of T84 IEC monolayers and THP-1 human monocytes. STS-challenge resulted in increased production of CCL1, CCL15, CCL20, CCL21, CCL24, CCL26, CX3CL1, CXCL1, CXCL2, CXCL8, CXCL10, CXCL11, CXCL16, IFN-γ, TNF-α, TNFSF13, TNFSF13B, C3L1, and gp130/sIL-6Rβ into the apical chamber of the co-culture system when compared to controls (n = 4; p < 0.05) (Figure 1 and Supplementary Figures 1A, B). This correlated with increased production of CCL15, CCL21, CCL23, CCL27, CX3CL1, GM-CSF, CXCL1, CXCL8, IFNγ, IL-6RA, IL-16, and C3L1 found within the basolateral chamber of the co-culture system when compared to controls, suggesting that the STS has the capacity to influence immune effector function of cells found beneath an IEC monolayer (n = 4; p < 0.05) (Figure 1 and Supplementary Figure 2). In contrast, challenge with the LrS only resulted in increased apical production of CD163, IL-32, IL-34, MIF, and TNFR2, with no significant impact on cytokines and chemokines found within the basolateral chamber (n = 4; p < 0.05) (Figures 1, 2 and Supplementary Figure 3). Challenge of IEC-APC co-cultures with a combination of the STS and LrS resulted in attenuation of all STS-induced pro-inflammatory mediator production to constitutive levels in both the apical and basolateral chambers of the co-culture system, indicating that apically delivered LrS can attenuate STS-induced inflammatory mediator production in co-cultures of IECs and APCs (p < 0.05; Figure 1).
Analysis of changes in gene-expression profiles in co-cultures of T84 IECs and THP-1 monocytes in response to challenge with the LrS or the STS was carried out to interrogate potential mechanism(s) of action behind the immunomodulatory activity of the LrS observed in individual cell populations. Consistent with the results obtained from the cytokine/chemokine profiling, STS-challenge of T84 IECs resulted in increased transcription of CXCL8 (n = 3; p < 0.05) (Figure 3), an effect also seen in the underlying THP-1 monocyte cell population (Figure 4). STS-challenge also up-regulated the transcription of NFκB1, a key transcription factor in the NF-κB signaling complex, in T84 IECs (n = 3; p < 0.05) and THP-1 monocytes (n = 3; p < 0.05) (Figures 3, 4). Interestingly, STS challenge down-regulated the expression of ZO-1, a gene encoding a tight-junction associated protein, indicating that the STS may be impacting tight-junctions within T84 IEC monolayers (n = 3; p < 0.05) (Figure 3). Concurrent challenge of co-cultures of T84 IECs and THP-1 monocytes with the LrS and the STS resulted in the attenuation of STS-induced transcription of CXCL8 and NFκB1 in both T84 IECs and THP-1 monocytes, coupled with increased transcription of ZO-1 and of ATF3 and DUSP1, negative regulators of innate immunity, in T84 IECs (n = 3; p < 0.05) (Figures 3, 4). Moreover, concurrent challenge of co-cultures of T84 IECs and THP-1 monocytes with the LrS and the STS up-regulated the expression of ZFP36L1, CD36, and ATF3 in the underlying THP-1 monocyte cell population when compared to STS- or LrS-challenge alone (n = 3; p < 0.05) (Figure 4).
To further interrogate potential underlying mechanism(s) of action behind the observed bioactivity of the LrS in the context of STS challenge within a co-culture system, the impact of the LrS and STS on IEC barrier integrity and permeability was determined. The LrS had no significant impact on TER measurements of T84 IEC monolayers, with no significant changes to the paracellular flux of FITC-dextran when compared to controls (n = 4; p > 0.05) (Figure 5), indicating no detrimental impacts on IEC monolayer integrity and permeability. In contrast, T84 IECs challenged with the STS had a significantly lower TER measurement than cells incubated with the LrS (n = 4; p < 0.05) (Figure 5A), confirming the results obtained by RT-qPCR analysis which indicated that the STS reduced the expression of tight junction proteins. This correlated with significantly higher amounts of paracellular flux of FITC-dextran when compared to controls and cells challenged with the LrS (n = 4; p < 0.05) (Figure 5), indicating overall deleterious impacts of the STS on IEC monolayer function and integrity. Co-challenge of STS-challenged T84 monolayers with the LrS resulted in no significant alterations in TER or paracellular flux, suggesting that the LrS can antagonize the negative impacts of STS-challenge on IEC monolayer integrity (n = 4; p < 0.05) (Figure 5). Morphological changes in T84 monolayers confirmed these findings as T84 IECs challenged with the STS displayed broken tight junctions via reduced expression of ZO-1 (Figure 6). In contrast, T84 IECs challenged with the LrS or co-challenged with both the STS and LrS had intact tight junctions (Figure 6). The addition of a MIF neutralizing antibody abrogated the observed bioactivity of the LrS on STS-challenged T84 IEC barrier integrity and function (Figures 7A,B), suggesting that LrS-induced MIF production may play a protective role in maintaining IEC barrier integrity. Moreover, the cell-surface expression of CD74, one of the cellular receptors for MIF, was higher on T84 IECs challenged with the LrS or co-challenged with both the STS and LrS (Figures 7C,D).
Interactions between IECs and the underlying APC population act in concert to shape immune responses to apically sensed bacteria and their soluble mediators. While current evidence suggests that certain LAB and gut-associated pathogenic bacteria or their soluble mediators can influence host immune outcomes in single cell in vitro cell cultures, less is known about their impacts on IEC and APC co-cultures. Moreover, the impact of soluble mediators derived from both LAB and gut-associated pathogens on IEC monolayer integrity and subsequent activity on the underlying APC population remains unknown, with recent evidence suggesting that this is an important route of host-microbe immune communication within the GALT. Cytokine and chemokine profiling revealed that LrS challenge induced a muted response from T84 IEC and THP-1 monocyte co-cultures, with no significant changes in the production of cytokines and chemokines from THP-1 monocytes found within the basolateral chamber of the co-culture system. However, the LrS induced the production of IL-32 into the apical compartment of the co-culture system. Although IL-32 has been associated with the pathophysiology of inflammatory bowel disease (Khawar et al., 2016), evidence suggests that it may also play an immunoregulatory role in the progression of disease. For example, IL-32 can inhibit TNF-α-induced IL-8 production by inhibiting the translation of IL-8 mRNA into functional protein through an unknown mechanism (Imaeda et al., 2011). LrS challenge also induced the production of MIF by T84 IECs into the apical chamber, a result consistent with that seen previously in HT-29 IECs challenged with the LrS (Jeffrey et al., 2020b), indicating that LrS-induced MIF production is not limited to HT-29 IECs. MIF has pleiotropic roles in regulating immune outcomes in IECs. However, MIF also plays an integral role in initiating inflammatory responses in APCs through NLRP3 inflammasome activation and subsequent release of inflammatory mediators (Lang et al., 2018). Interestingly, LrS challenge did not increase MIF secretion into the basolateral chamber or induce MIF production from THP-1 monocytes, suggesting that LrS-induced MIF production is spatially compartmentalized into the apical chamber, limiting potential activation of the underlying THP-1 monocytes. Limiting the directionality of the release of certain cytokines and chemokines by IECs may serve as a means of muting bidirectional immune communication and subsequent activation of the underlying APC population within the GALT to certain challenges while still allowing for paracrine communication with adjacent IECs. STS-challenge resulted in increased production of pro-inflammatory cytokines and chemokines found in the apical and basolateral chambers of the co-culture system. Indeed, previous evidence describes a route through which ST can invade the intestinal mucosa by infecting IECs and the underlying APC populations. However, induction of pro-inflammatory mediator production in co-cultures of T84 IECs and THP-1 monocytes in response to STS challenge represents a potential novel route of pathogenicity mediated through soluble mediators derived from gut-associated pathogens. While the mechanisms through which STS induced THP-1 cells to release proinflammatory cytokines and chemokines into the basolateral chambers remain to be determined, one possibility is that STS-mediated disruption of the T84 IEC barrier led to increased access of pro-inflammatory STS components to the THP-1 cells, directly resulting in heightened production of pro-inflammatory mediators by these APCs. Pro-inflammatory cytokine and chemokine production by THP-1 APCs may also be induced by pro-inflammatory cytokines released by STS-induced activation of T84 IECs, and it possible that both of these routes operate in vivo during Salmonella infection. Co-challenge with the LrS attenuated STS-induced pro-inflammatory mediator production from T84 IEC and THP-1 monocyte co-cultures, a result that is in keeping with the observed bioactivity of the LrS in STS-challenged HT-29 IECs (Jeffrey et al., 2020b). In contrast, Lactobacillus paracasei CNCM-4034 and its secretome was found to induce pro-inflammatory mediator production and enhance pro-inflammatory gene transcription in response to challenge with Salmonella typhi in Caco-2 IEC and APC co-cultures, illustrating differences in secretome-mediated effects of lactobacilli on immune activity (Bermudez-Brito et al., 2015). Challenge with the LrS induced the expression of ATF3 and DUSP1, but not TRIB3 in T84 IECs. This is in contrast to previous transcriptional profiling of HT-29 IECs following LrS challenge, as induction of these negative regulators of innate immunity was only seen following co-challenge of HT-29 IECs with the LrS and TNF-α or the STS (Jeffrey et al., 2020b). THP-1 human monocytes were less responsive to LrS challenge than T84 IECs as there were no significant changes to gene expression profiles in the absence of pro-inflammatory challenge. Co-challenge of STS-challenged co-cultures with the LrS attenuated NF-κB1 as well as CXCL8 gene expression in both T84 IECs and THP-1 monocytes, confirming the results obtained in the cytokine and chemokine profiling. As was seen in HT-29 IECs co-challenged with the LrS and the STS (Jeffrey et al., 2020b), there was also increased expression of ATF3, DUSP1, and TRIB3 in STS-challenged T84 IECs following concurrent secretome challenge, suggesting conserved immunoregulatory activity of the LrS across different in vitro IEC models and in co-culture systems. Interestingly, the STS-challenge also reduced the expression of ZO-1, a tight-junction protein integral to proper function of the IEC barrier, providing potential insight into STS-induced pro-inflammatory responses in THP-1 monocytes observed in the basolateral chamber of the co-culture system. Deterioration of IEC monolayer integrity through disruption of tight junction proteins such as ZO-1 is a hallmark of S. enterica serovar Typhimurium infection, resulting in enhanced translocation of the bacteria into the lamina propria (Boyle et al., 2006; Kohler et al., 2007). In keeping with these findings, the STS decreased T84 IEC TER and increased the flux of FITC-dextran across T84 IEC monolayers, indicating damage to IEC monolayer integrity and function. These results were further confirmed through visual inspection of ZO-1 expression following STS-challenge. Typically, damage to IEC monolayer integrity caused by S. enterica serovar Typhimurium infection is mediated by the direct delivery of virulence factors into host cells via a type III secretion system (Coburn et al., 2007a,b). However, the results presented here suggest that secretome components derived from S. enterica serovar Typhimurium grown under normal conditions can also disrupt normal IEC monolayer function. The LrS attenuated STS-induced damage to T84 IEC monolayer integrity and function. Although there have been other reports of LAB-mediated strengthening of IEC monolayer barrier integrity, the results presented here suggest a possible novel route through which soluble mediators derived from LAB can antagonize the activity of certain gut-associated pathogens. Addition of a MIF-neutralizing antibody reversed the ability of the LrS to attenuate STS-induced damage to IEC epithelial monolayer integrity. Recent evidence has suggested that MIF is integral for IEC repair and regeneration as well as for normal barrier function of IECs, as MIF deficient mice have increased intestinal permeability due to impairment of tight junction proteins such as ZO-1 (Vujicic et al., 2018, 2020). Mechanistically, MIF binds to CD74 (Leng et al., 2003), typically following pro-inflammatory challenge or perturbations in normal IEC activity (Farr et al., 2020b). Interestingly, T84 IECs challenged with the LrS or co-challenged with both the STS and LrS had higher cell-surface receptor expression of CD74. The CD74-MIF signaling complex facilitates the activation of PI3K/AkT and ERK cell proliferation and survival cellular pathways (Lue et al., 2007; Farr et al., 2020a). However, the precise mechanism(s) involved in the induction of MIF production following LrS challenge remain unknown and warrant further study, especially in the context of polarized IECs which display vectoral secretion of certain cytokines and chemokines. Co-culture in Transwell systems provides a useful strategy to interrogate the impact of microbial products on IEC and APC interactions, including LAB-mediated attenuation of pathogen-induced inflammatory responses. The results presented here provide mechanistic insight into the ability of the LrS to modulate immune responses to STS-challenge in a context that allows for IEC and APC cell communication. The LrS was able to reverse STS-induced damage to IEC monolayer integrity, an effect potentially mediated through LrS-induced MIF production by IECs. Further experimentation using additional timepoints and secretomes derived from different LAB may reveal species-specific and time-dependent consequences of prolonged exposure to soluble components from LAB in a context which more closely mimics that which occurs in vivo. These future studies would provide further potential insights into mechanisms of gut microbe-host immune communication at the gut-mucosal interface.
All relevant data are contained within the article. The original contributions presented in this study are included in the article/Supplementary material. Further inquiries can be directed to the corresponding author.
MJ and CM carried out the experiments. MJ performed the statistical analysis and wrote the first draft of the manuscript. All authors contributed to manuscript revision, approved the submitted version, and contributed to the study design. | true | true | true |
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PMC9554751 | Chao Li,Yawei Du,Tongtong Zhang,Haoran Wang,Zhiyong Hou,Yingze Zhang,Wenguo Cui,Wei Chen | “Genetic scissors” CRISPR/Cas9 genome editing cutting-edge biocarrier technology for bone and cartilage repair | 07-10-2022 | CRISPR/Cas9,Genome editing,Bone repair,Cartilage repair | CRISPR/Cas9 is a revolutionary genome editing technology with the tremendous advantages such as precisely targeting/shearing ability, low cost and convenient operation, becoming an efficient and indispensable tool in biological research. As a disruptive technique, CRISPR/Cas9 genome editing has a great potential to realize a future breakthrough in the clinical bone and cartilage repairing as well. This review highlights the research status of CRISPR/Cas9 system in bone and cartilage repair, illustrates its mechanism for promoting osteogenesis and chondrogenesis, and explores the development tendency of CRISPR/Cas9 in bone and cartilage repair to overcome the current limitations. | “Genetic scissors” CRISPR/Cas9 genome editing cutting-edge biocarrier technology for bone and cartilage repair
CRISPR/Cas9 is a revolutionary genome editing technology with the tremendous advantages such as precisely targeting/shearing ability, low cost and convenient operation, becoming an efficient and indispensable tool in biological research. As a disruptive technique, CRISPR/Cas9 genome editing has a great potential to realize a future breakthrough in the clinical bone and cartilage repairing as well. This review highlights the research status of CRISPR/Cas9 system in bone and cartilage repair, illustrates its mechanism for promoting osteogenesis and chondrogenesis, and explores the development tendency of CRISPR/Cas9 in bone and cartilage repair to overcome the current limitations.
For the regeneration of bone and cartilage, it is crucial to promote the proliferation or differentiation of osteoblasts and chondroblasts. In the ordinary bone or cartilage defect repair, fixation and suture repair are preferred methods in clinic. While large bone defects always need autologous bone or allogeneic bone transplantation, which has numerous side effects like chronic pain, nerve injury, infection, high risk of disease transmission and immune rejection [1]. Furthermore, implantation of orthopaedic materials is another important strategy in current clinic treatment. However, long-term biocompatible problems of some widely used non-bioabsorbable biomaterials are reported frequently, such as poly-ether-ether-ketone (PEEK) and polymethyl methacrylate (PMMA), may causing some unavoidable drawbacks, such as osteolysis, secondary surgery requirement and increasing risk of postoperative complications (Table 1) [2]. Gene editing is regarded as a monumental technology in life science. The early techniques relied on site-specific identification of DNA loci based on nucleases, including Zinc Finger nucleases (ZFNs) and Transcription Activator-Like Effector nucleases (TALENs) [3]. However, the difficulties in protein design and synthesis were limited the widespread use of these nucleases [4,5]. In 1980s, a defense mechanism of some prokaryotes against the virus was found based on a sequence called Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to identify of exogenous pathogenic DNA [6]. CRISPR is guided by RNA, and is epoch-making in the current application of gene editing while thanks to the specificity and codability of RNA sequences [7]. The gene in CRISPR locus nearby was named as CRISPR-associated (Cas). After years of research, the mature CRISPR system was simplified with two parts: single guide RNA (sgRNA) and CRISPR-associated protein 9 (Cas9) nuclease. Since then, CRISPR/Cas9 technology has brought a huge impact to the life science field, and researches was recognized by the Nobel Prize in Chemistry in 2020. In bone and cartilage repair field, CRISPR/Cas9 system as a third-generation genome editing technology can overcome many shortcomings of traditional strategies. It can provide powerful ability to regulate genome sequence and gene expression, which could change or correct gene function and defects for long-term to achieve therapeutic effects at the genetic level. Usually, bone and cartilage repair are regulated by several growth factors, such as transforming growth factor (TGF-β), insulin-like growth factor-1 (IGF-1) and basic fibroblast growth factor (bFGF) [8], a), b), [9], a), b). Besides, some osteogenesis-related proteins such as alkaline phosphatase (ALP), bone morphogenetic protein (BMP) and osteocalcin (OCN) are also involved in the synthesis and mineralization of bone matrix and the value-added and differentiation of osteoblasts [10], a), b), [11]. Gene therapy for the repair of bone and cartilage defects usually involves the introduction of target gene fragments into the organism so that the relative expression products can be sustainably expressed in the subsequent repair with the aim of promoting osteogenesis. Unlike direct regulation of osteogenic-related factors, the CRISPR/Cas9 system can reprogram pluripotent stem cells and induce their differentiation towards bone or cartilage [12]. By exploiting the multifunctional differentiation properties of bone marrow mesenchymal stem cells (BMSCs), BMSCs are widely used in the treatment and repair of bone and soft tissues and are shown to be a viable approach to mediate bone regeneration [13]. Compared with the traditional gene therapies, the CRISPR/Cas9 system enables precise target gene insertion, knockout and editing. It can not only circumvent the systemic side effects of traditional surgery and conventional drugs, but also induce large amounts of phenotypic proteins at once to complete the treatment in a targeted manner, providing a promising new pathway for bone and cartilage repair (Fig. 1). In recent years, rapid advances in molecular biology and genomics greatly promote the possibility of gene editing techniques in the treatment of bone and cartilage diseases. Here, CRISPR/Cas9 system, as the most powerful genome engineering tool, benefits from programmable RNA that can rapidly generate specific sequences and easily accomplish applications [14]. In this review, we presented a comprehensive discuss of the molecular mechanisms and technical principles of the CRISPR/Cas9 system and detailly described the classification and research progress of delivery vectors. We highlighted the applications and challenges of the CRISPR/Cas9 system for promoting osteogenesis and chondrogenesis. Finally, we summarized the off-target effects and editing efficiency of CRISPR/Cas9 systems in bone and cartilage repair and discuss the direction of their subsequent development.
Generally, CRISPR consists of a leader (promoter), repeats and genome-targeting sequences (spacers) [15]. When an exogenous gene is invaded into a prokaryotic organism, the original spacer in its genome is recognized by the Cas proteins through the protospacer adjacent motif (PAM) sequence downstream of the original spacer and then cut (Fig. 2A). Cas proteins insert the clipped original spacer into the middle of the leader and the repeat to form a new spacer [16]. The A-T-rich leader contains a promoter, which is used to initiate transcription of repeat and spacer sequences. The transcribed long-stranded RNA is called precursor transcript CRISPR RNA (pre-crRNA), which is then processed into mature CRISPR RNA (crRNA) by related enzymes [17]. Cas proteins can form new Cas protein complexes together with crRNA and trans-activating crRNA (tracrRNA). The small guide RNA (sgRNA) formed by the fusion of crRNA and tracrRNA complementarily pairs with the gene in the exogenous gene and directs the Cas protein to shear the exogenous gene fragment [18]. The recognition of target DNA by the CRISPR/Cas9 system differs from traditional protein-guided gene editing techniques in that it uses small molecules of RNA sequences, which not only avoids the cumbersome protein engineering associated with DNA recognition, but also greatly improves its applicability for high-throughput genomic manipulation or screening [19]. As mentioned previously, Cas9 needs to assemble with crRNA and tracrRNA to form a new complex in order to achieve recognition and cleavage of the target DNA. sgRNA of the Cas9 complex matches the target DNA according to the principle of Watson-Crick base pairing, while localizing at a specific site [20]. PAM sequence which near this specific site is a short sequence associated with a specific Cas protein and necessary for complementary pairing [21]. Different Cas proteins often match different short sequences, for example Cas9 from Streptococcus pyogenes (SpCas9) matches 5′-NGG-3’ [22]. The relatively simple PAM sequence has a higher probability of occurring in the genome and is more conducive to the widespread use of Cas9. The sequence from staphylococcus aureus is 5′-NNGRRT-3′, and the longer PAM sequence increases the specificity of its recognition and helps prevent off-target effects at the same time [23]. Upon binding to the target gene, the complementary single strand (complementary paired with crRNA) and non-complementary single strand of the target gene are recognized and cleaved by the HNH and RuvC structural domains of Cas9 respectively, producing a double stranded break (DSB) at the flat end of the target gene [24]. There are three different Cas systems using different mechanisms. Type I and Type III require a large protein complex composed of different Cas proteins when cutting the target gene, while Type II requires only one Cas protein such as Cas9 [25]. Cas9 in the Type II CRISPR system can cleave exogenous DNA into double DSB DNA. There are two types of repair methods when a DNA double strand is cut (Fig. 2B). The first one is nonhomologous end joining (NHEJ), which urgently links the broken DNA double strands like spontaneous “SOS” (“save our souls” signal) repair in living organisms. However, this repair method is stochastic and prone to insertion or deletion mutations that can damage the target gene [26]. The other one is homology-directed repair (HDR), which is a small fragment of DNA with the same sequence at both ends and the broken sequence can be homologously recombined with the broken gene, thus completing the exact recombination of the gene [27]. The most commonly used synthetic CRISPR system is the Type II CRISPR system which uses a single cut of Cas9 protein. Its convenience and speed have given it a potential that cannot be underestimated in medical and scientific fields.
CRISPR/Cas9 changes the current status quo using a single conventional treatment in bone and cartilage tissue diseases. As a powerful gene editing tool, CRISPR/Cas9 systems are essential to be delivered to bone tissue targets such as the synovial membrane of the joint cavity or cartilage tissue, thereby allowing the long-term stable expression of a specific gene for the ultimate therapeutic purpose. Many common physical delivery methods are limited by in vivo applications while highly efficient in delivery. So far, nanotechnology-based non-viral vectors or conventional viral vectors are gaining more and more attention. Herein, delivery/transfer vectors of CRISPR/Cas9 system should be focused (Fig. 3). In order to assess the potential of conventional delivery methods for application, it is particularly important to consider the advantages and disadvantages of various methods in an integrated manner (Table 2).
Physical delivery methods include electroporation, magnetofection, microfluidics, ultrasonic, and microinjection [[28], [29], [30], [31], [32]].
Previously, electroporation has been widely used as a non-virus delivery method for cell transfection. Electroporation also called electrotransfection. Electrotransfection transiently increases the permeability of the cell membrane by applying a high-intensity electric field to the cell, thereby allowing the entry of exogenous genes or drugs into the cell [33]. And the high intensity of the electric field can reduce complications associated with targeting and immunogenicity [34]. Beyond that, electroporation has the ideal property of transfecting non-dividing cells such as nerves, cartilage or bone. It has extraordinary advantages in the field of tissue engineering repair [[35], [36], [37]]. Despite its many advantages, electroporation still has some limitations. Cells often die or have increased toxicity due to high voltages and lower cell viability is one of the main disadvantages of electroporation [38]. If in vivo transfection therapy is performed, different transmitter devices are required with high costs and varying degrees of tissue damage resulting from invasive operations [39]. Tröder et al. used a modified electroporation method to act on fertilized eggs of C57BL/6 mice to obtain CRISPR/cas9-mediated specific mutant mice [40]. Not only was the specific mutation successfully introduced without affecting embryonic development, but the live birth rate of embryos was also significantly increased. Miao et al. targeted the germ cell-specific gene nanos2 by pre-assembling sgRNA/Cas9 RNPs and electroporated fertilized eggs from mice, cattle and pigs, which stably produced mutant progeny [41]. Xu et al. reported a tubular electroporation technique and experimental results showed that the new technique could enable efficient genome editing in mammalian cells especially for human-derived stem cells that are difficult to transfect. It may be a new strategy for delivering CRISPR/Cas9 [42] (Fig. 4A).
Magnetofection technology uses the surface activity of magnetic nanoparticles like iron oxide to combine with target genes to form gene-loaded magnetic microspheres [43] (Fig. 4B). Although the magnetofection technique does not directly improve transfection efficiency, the powerful magnetic attraction capacity allows the number and speed of nucleic acid molecules to enter the cell, maximizing the use of nucleic acids [44], a), b). Different from electroporation, the magnetofection technique does not require disruption of the cell membrane and uses the endocytosis mechanism to complete uptake which effectively avoids the low activity state of cells after transfection [45]. Mykhaylyk et al. successfully constructed magnetically responsive siRNA complexes that accomplished intracellular translocation and effectively silenced the target gene [46]. Hryhorowicz et al. used polyethyleneimine-coated magnetic iron oxide nanoparticles to construct magnetic plasmid DNA complexes (PEI-Mag2) to facilitate CRISPR/Cas9 plasmid transfection of porcine fetal fibroblasts (PFFs). The transfection efficiency can be improved using PEI-Mag2, which may be due to its magnetic properties that accelerate the deposition of nucleic acids on the cell surface [47].
The microfluidic membrane deformation method exploits the deformation capacity of the cell membrane, which undergoes rapid deformation under mechanical action to produce temporary pores through which nucleic acid or protein molecules enter the cytoplasm [48]. The integrated property of microfluidics itself allows selective screening of untransfected cells or repeated transfection again by microarray to improve the gene editing activity. Han et al. first applied microfluidic membrane deformation to CRISPR/Cas9 delivery and successfully completed RNA-guided gene editing [49] (Fig. 4C and D). This rapid and high-throughput platform can provide a promising strategy for CRISPR/Cas9-mediated gene editing and gene analysis. Microfluidic membrane deformation does not depend on exogenous material, endocytosis or chemical modification of the target molecule. Transfection can be done reproducibly with only microfluidic chips [50]. Because of the limitation of microfluidic chip, it cannot be delivered in vivo which limits its clinical application potential.
Lipid bilayers are capable of directly converting acoustic energy into mechanical stress and strain at the subcellular and cellular levels [51], a), b). High-energy ultrasonic produces local shear in the extracellular fluid, inducing the formation of pores in the cell membrane and increasing the permeability to DNA or RNA [52], a), b). Ultrasonic methods can be safely used in vivo due to their non-invasive nature and are currently used in clinical cases [53]. However, its low control leads to low transfection efficiency, low success rate and high equipment requirements [54]. Ryu et al. constructed microbubble nano-liposome particles as Cas9/sgRNA nucleoprotein complex carriers and successfully transferred the protein complex into dermal papilla cells of hair follicles in male bald animals under ultrasonic activation The research validated the inhibitory effect of CRISPR/Cas9 on SRD5A2 in vivo and in vitro which finally restored hair growth [55]. To deliver CRISPR plasmids, Dong et al. developed a dual ultrasonic/magnetic responsive microdrop that can effectively deliver plasmids to cancer cells, which could be a potential strategy for clinical application of ultrasonic methods for cancer treatment [56].
Microinjection is a simple and direct non-virus transfection method that allows the introduction of DNA or RNA into the cytosol using only micron-sized pipettes. Its transfection efficiency tends to be high because the injection volume and location can be precisely controlled [57], a), b). However, due to its huge optical instrumentation requirements and the results are related to the proficiency of the technician, microinjection is only used in specific settings [58]. Ai et al. successfully completed the knockout of cotton bollworm genes using the CRISPR/Cas9 system by microinjection method, which improved the efficiency of gene editing [59]. Li et al. explored the effect of microinjection time on the embryonic developmental capacity of the CRISPR/Cas9 system and showed that microinjection time had different degrees of effect on embryonic development and gene editing rate of in vitro fertilized porcine embryos. Proper optimization of sgRNA or Cas9 concentration and precise determination of injection time could better accomplish gene editing [60] (Fig. 5A–C).
Virus vectors are the vectors of choice for gene editing and gene therapy. They are widely used not only in vitro but also in clinical settings. However, the safety of vectors is often a concern due to the specificity of viruses. To avoid recombination of lentiviral vectors in vivo, their genome is first split into multiple different structures. Secondly, the promoter or enhancer sequences in their terminal repeat sequences are deleted to avoid activation of related genes. Alternatively, the glycoprotein is wrapped around the surface of the virus vector and modified to limit the host range [61]. All these safety measures can generate inactivated vectors for safe transfer.
Lentivirus vectors are retrovirus vectors based on HIV-1 [62]. The entry of lentivirus vectors into target cells is mediated by the interaction between glycoproteins immobilized on the outer membrane and receptors on the surface of the target cells. Lentivirus vectors have a large capacity of 9 kb, which is sufficient to package the various components of CRISPR [63]. As an integrative vector, lentivirus vectors can also carry multiple genomic fractions which may be a key element in the treatment of certain diseases. In addition, lentivirus vectors can transfect cells in stationary phase whereas ordinary retrovirus vectors can only transfect cells in division. It increases the scope of application and indirectly enhancing the gene therapy effect [64]. Lentiviruses, as carriers of CRISPR/Cas9, not only have the ability to gene edit, but also take full advantage of the advantages that lentivirus vectors themselves possess [65]. Lentivirus vectors can efficiently integrate exogenous genes into the chromosomes of target cells, thus expressing target genes in a sustained manner. Lentivirus vectors are preferred for cells that are more difficult to transfect, such as primary cells or stem cells. It can significantly improve the transduction efficiency of target genes and achieve long-term and stable expression of target genes conveniently and quickly. Joung et al. selected the lentivirus as a vector for CRISPR/Cas9 by considering the insertion capacity and cell type. And gene editing was successfully completed proving that lentivirus vectors are a powerful tool for gene transduction [66].
Adenovirus vectors are double-stranded DNA viruses that enter the target cells through receptor-mediated endocytosis and can transduce different cell types without being restricted by the division phase. Likewise, adenovirus vectors do not integrate into the host cell genome, staying outside the chromosome and achieving only instantaneous expression with a high safety profile [67]. Adenovirus vectors have many unique advantages over other viral vectors. Firstly, most human cells can express adenovirus receptors, which makes adenovirus vectors have a wide range of application and high transduction efficiency. Secondly, modified adenovirus vectors can easily escape the body's intrinsic immune system defenses. Adenovirus vectors are also becoming the most commonly used vectors in clinical trials worldwide [68]. Adenovirus vectors have not only been used for vaccine development and tumor therapy, but also have potential for gene editing [69] (Fig. 5D–G). Tsukamoto et al. applied adenovirus vector-loaded AsCpf1 gene to primary culture of humanized mouse hepatocytes and showed that the adenovirus vector-mediated CRISPR/AsCpf1 system provides a useful tool for genome editing of human hepatocytes [70].
The development of nanocarriers as an alternative to traditional physical transfection methods and viral delivery methods has been very rapid. Non-viral vectors are more secure and easier to mass-produce than viral vectors. Both dendrimers and liposomes offer extraordinary advantages in terms of targeting, high encapsulation and low immunogenicity. More and more nanocarriers are taking the stage for bone or cartilage gene therapy.
Dendrimers are macromolecules with a dendritic structure, consisting of oligomers repeatedly and linearly linked by dendritic units. Due to the controllability of its monomer, the physicochemical properties of dendrimers can be precisely controlled and personalized preparation can be accomplished. Meanwhile, the dendrimers contain a cavity structure inside, forming a dense three-dimensional sphere structure that can be perfectly used for gene encapsulation. Also, many functional groups are exposed on its surface which can be modified to accomplish better performance optimization thanks to the spherical structure [71] (Fig. 6A and B). Farbiak et al. developed a dendrimer-based lipid nanoparticle in order to accomplish CRISPR/Cas9-mediated HDR while avoiding the NHEJ error-prone mechanism. The team encapsulated Cas9 mRNA, sgRNA and donor ssDNA (single-stranded DNA) in nanoparticles with low cytotoxicity and no charge at neutral pH. At the appropriate ratio, the nanoparticles are able to complete HDR. This may be related to the simultaneous delivery of three nucleic acids [72]. Liu et al. reported a boric acid-containing dendrimer that can deliver Cas9 protein with high efficiency. Not only that, it can also be used for protein delivery with different isoelectric points or sizes without chemical modification, overcoming the problem of difficulty in forming stable complexes with proteins [73].
Liposomes are bilayer vesicles that mimic cell membranes and show promise in the delivery field because of their efficient delivery capacity and good biocompatibility [74]. Cationic lipids are a key component of liposomes and play an important role in nucleic acid encapsulation and cellular delivery. Pre-liposomes as siRNA delivery vectors have difficulty in encapsulating large molecules of Cas9 protein and sgRNA. To overcome this obstacle, Rosenblum et al. developed a liposome system for CRISPR/Cas9 gene editing [75]. The results showed that the system successfully delivered Cas9 mRNA and sgRNA into tumor cells and led to apoptosis of tumor cells and improved survival. Han et al. prepared a series of liposomes containing Cas9 mRNA and modified sgRNA using microfluidic technology. The end-modified sgRNA could achieve 85% encapsulation rate, and this liposome-mediated gene editing became a new safe therapeutic method [76] (Fig. 6C). Unlike viral vectors for in vivo delivery, Kenjo et al. reported a liposome that can be repeatedly injected into skeletal muscle tissue [77] (Fig. 6D). It was injected into the gastrocnemius muscle of mice and maintained stable levels in vivo for close to 100 days. Its low immunogenicity and repeatable administration are important features for the future use of liposomal carriers for bone or cartilage repair.
Micelles are ordered aggregates of molecules that begin to form in large numbers after the surfactant concentration reaches a certain value in an aqueous solution [78]. The micelles rely mainly on hydrophobic and electrostatic interactions for nucleic acid loading [79]. Abbasi et al. explored polymorphic micelles (PMs) prepared from polyethylene glycol (PEG)-poly(cationic block copolymers) for delivery of CRISPR/Cas9 components. It was found that loading Cas9 mRNA and sgRNA together into 1 p.m. significantly improved the stability of sgRNA compared to loading sgRNA alone. The team reported the successful co-encapsulation of Cas9 mRNA and sgRNA in PM and the successful completion of gene editing [80]. Self-assembled micelles consisting of quaternary ammonium terminated poly(propylene oxide) (PPO–NMe3) and amphiphilic Pluronic F127 were designed. Lao et al. optimized micelle performance to target the HPV18-E7 oncogene. While assessing gene silencing capacity, the micelles demonstrated strong protection and delivery capabilities [[81], a)]. So far, although there are numerous methods of gene delivery, none of them is perfect. We should consider the scope of applicability and the advantages and disadvantages of various delivery vectors or methods, and reasonably assess their potential for introduction into clinical applications. Some elements that may determine the efficiency or biosafety of gene transfer such as carrying capacity [81b], immunogenicity [81c] and economic cost [81c], are the key conditions that we should examine comprehensively.
The basis of bone repair is the formation of bone scabs by osteoblasts and osteoclasts in response to various cytokines. Gene editing technique based on CRISPR/Cas9 demonstrates a great potential to be translated into clinical applications for bone repairing [82]. Currently, long bone fractures are self-healing with strong internal fixation, but healing is often less optimistic due to many factors such as osteoporosis or advanced age. In the face of segmental defects with a defect length of more than twice the diameter of the diaphysis, non-healing of the broken end often occurs [83]. Conventional autologous bone grafts, allogeneic bone grafts and material implants are more or less subject to adverse reactions such as pain, infection or immune rejection. Nowadays, the concept of introducing one or more osteogenic genes into a non-healing patient with the expectation of modifying the healing pattern of the organism through gene editing has become very attractive (Table 3). There are two main strategies of gene editing for the treatment of bone defects. First, the gene-loaded vector is applied directly to the defect site, or it can be combined with a scaffold before implantation. Second, suitable tissues such as bone or muscle tissue are collected in vivo, edited and modified in vitro and then reimplanted in vivo [84]. In either strategy, the ultimate goal is to promote osteogenesis and healing, using gene editing to complete the treatment of bone defect diseases. Bone repair and reconstruction consists of resorption of old bone by osteoclasts and formation of new bone by osteoblasts [85]. If osteoclasts are deficient, the fracture ends are atrophied on both sides, the bone marrow cavity is closed or sclerosis of the bone ends occurs, often resulting in non-healing consequences. ELMO1 promotes enhanced osteoclast activity and increases bone resorption activity. Arandjelovic et al. deleted the ELMO1 gene in Hoxb8 macrophages via CRISPR/Cas9 and sgRNA. Then the transfected macrophages developed functional defects [86] (Fig. 7A and B). To further explore whether ELMO1 can control other signaling markers in osteoblasts, the group continued to target proteins that may play a role such as athepsin G (Ctsg) and myeloperoxidase (Mpo). The results showed that this macrophage reduced the degradation function after knocking down the mRNA of this protein using CRISPR/Cas9, indicating that ELMO1 is a key part of the functional network regulating bone degradation in osteoclasts. However, targeting the resorptive activity of osteoclasts is often more beneficial than the quantity. A rational selection of target genes could help find new breakthroughs in bone repair. BMP2 is known as a regulator of bone and cartilage formation and is a potent osteoinductive growth factor, but its clinical application is limited due to its high cost because of the high dosage required for its efficacy [87]. High expression of BMP2 upregulates the expression of osteogenic genes and induces differentiation of stem cells into osteoblasts. However, bone precursor cells express a Noggin protein in response to BMP2 stimulation to antagonize the biological activity of BMP2 [88]. Noggin can bind BMP2 and prevent its docking with stem cell surface receptors, thereby inhibiting stem osteogenic differentiation. Therefore, inhibition of Noggin expression may reduce the antagonistic effect of Noggin on BMP2 and indirectly promote osteogenesis. Hsu et al. fused Cas9 with transcriptional repressors such as VPR to generate dCas9-VPR that binds to specific sgRNA, and performed in vitro gene editing using baculovirus as a vector targeting Noggin. The results showed that Noggin gene was knocked out and BMP2 was overexpressed, which could effectively promote osteogenic differentiation of adipose stem cells and promote bone healing [89] (Fig. 7C–F). BMP9 induces differentiation of stem cells to osteoblasts by activating Smad-dependent signaling pathways and has a higher osteogenic potential compared to BMP2 [90,91]. To evaluate the role of BMP9 in promoting bone defect repair in vitro and in vivo, MSCs were genetically edited to overexpress BMP9 using the CRISPR/Cas9 system [92]. Osteogenic markers, such as Runx2, Sp7, ALP and Oc, were increased to varying degrees. In vivo experiments showed accelerated new bone formation and increased bone density in rats injected with gene edited stem cells. This is the first demonstration that CRISPR-edited MSCs overexpressing BMP9 can successfully promote bone formation, providing a new option for the application of gene therapy in the field of bone defects. Until now, healing of large segmental bone defects remains difficult. Truong et al. attempted to improve it by stimulating cartilage formation through implantation of stem cells [93]. The group constructed a Cas9, sgRNA-based CRISPR activation/repression (CRISPRai) system and verified that Cas9 synergizes with sgRNAa (activator) to activate the mCherry activator and with sgRNAi (inhibitor) to activate the d2EGFP repressor. Mesenchymal stem cells from rats introduced via baculovirus were simultaneously assayed for the blocking effect of Sox9 and PPAR-γ. Sox9 and PPAR-γ act as major transcription factors for cartilage and adipose formation respectively, and PPAR-γ inhibits the action of Sox9 [94]. Therefore, activation of Sox9 while inhibiting PPAR-γ promotes bone healing. The CRISPRai system was constructed using the large capacity of the baculovirus vector. It was demonstrated that CRISPRai could be combined to stimulate tissue regeneration for bidirectional regulation for the first time and provided a more flexible tool. The osteogenic differentiation capacity of BMSCs needs to be tightly regulated. Too little bone formation may not complete repair, but too much bone formation may lead to ectopic ossification or osteosclerosis. MSX1 balances the level of protein degradation during normal osteogenesis. In the present study, Kaushal et al. used the CRISPR/Cas9 system to screen for deubiquitinating enzymes (DUBs) that regulate MSX1 protein and identified the Ubiquitin carboxyl-terminal hydrolase 11 (USP11) as a regulator of MSX1 [95]. USP11 overexpression enhances the expression of osteogenic factors in BMSCs. Also, it affects calcification and ALP activity if USP11 is lacking. The group selected 50 sgRNAs of USP family genes and validated the selected USP11. There are no functional reports on the interaction of USP11 with MSX1 in BMSCs, and the group demonstrated a novel role of USP11 in the osteogenic differentiation process. The Wnt signaling pathway is a central regulator of bone development and repair. And the Wnt pathway is an attractive therapeutic target that plays an important role in the osteogenic differentiation of BMSCs [96]. Wnt16 is a ligand that affects stem cell proliferation, differentiation and migration through the Wnt pathway [97]. McGowan et al. generated stable Wnt16 −/− mutant zebrafish lines using CRISPR/Cas9 technology to study their effects on bone tissue using tissue mineral density (TMD) as an observation [98] (Fig. 8A). Bone defects were subsequently induced in the caudal fin of Wnt16−/− zebrafish. Compared to wild-type zebrafish, Wnt16 mutants exhibit delayed bone mineralization during bone repair. Osteoblast recruitment was also significantly delayed in Wnt16 mutants after bone defect. This study effectively demonstrates that Wnt16 may regulate Wnt activity through Runx2a to promote osteoblast differentiation and bone matrix deposition. Appropriate treatment targeting Wnt16 may prevent fractures and promote bone repair. The function of some osteogenic transcription factors can be enhanced by the specific AT-rich sequence binding protein 2 (Satb2). Deletion of Satb2 may result in incomplete expression of osteogenic genes or poor skeletal development [99]. To further explore the molecular mechanism of Satb2-mediated osteogenic function, Dowrey et al. used the CRISPR/Cas9 system to induce mutations in the Satb2 gene in MC3T3-E1 cells [100] (Fig. 8B–D). When Satb2 expression is reduced, the growth rate of osteoblasts is slowed down. In addition, Satb2 mutations lead to nuclear abnormalitie. And the osteoblast value-added process, in which Satb2 is involved, can help to demonstrate the genetic background for the repair of bone defects.
Cartilage has no nerves or blood vessels and therefore lacks the ability to heal itself. The repair of cartilage defects remains a great challenge at this time. Traditional methods include microfractures, cartilage grafts or scaffold implants, but these methods do not fully restore the natural cartilage tissue. Current research is exploring the potential of MSCs in cartilage repair, and CRISPR/Cas9 is an excellent tool for this purpose. As the preferred tool for gene editing, how to promote cartilage regeneration is an important direction for its development (Table 4). LncRNA DANCR was reported to induce differentiation of human synovial-derived stem cells and synovial-derived MSCs toward cartilage [101]. Nguyen et al. packaged dCas9-VPR and its corresponding gRNA into a baculovirus for gene transfection and compared four dCas9-VPRs derived from different bacteria, showing that SadCas9-VPR derived from Staphylococcus aureus successfully induced DANCR activation in rat adipose stem cells [ 2] (Fig. 9A–C). Activation of DANCR significantly promotes the differentiation of adipose stem cells to chondrocytes and enhances cartilage formation in vitro. Activation of DANCR with CRISPR/Cas9 can dramatically upregulate the expression of Smad3 and enhance bone defect repair, which is expected to be a novel therapeutic target for future cartilage repair. Seidl et al. reconstructed human articular chondrocyte populations using a CRISPR/Cas9-mediated gene editing strategy that stably reduced MMP13 expression in cartilage [103] (Fig. 9D–F). Reduction of total MMP13 secretion by CRISPR/Cas9 indirectly reduces degradation of the extracellular matrix. Firstly, a 3D tissue model was established to simulate the natural environment of cells and tissues. Next, the level of collagen type 2 (Col2) was detected to determine whether the secretion and activity of MMP13 was successfully inhibited. Tissues like cartilage which lack vascularization and have low self-proliferative activity are good candidates for gene editing and are well protected from migration of other accidental edits from cartilage tissue. This approach would greatly improve the efficacy of current cell-based cartilage repair. Similar to the previous approaches, stem cell therapy has been demonstrating a central role in clinical regenerative therapy. Whether it is exogenous implantation of stem cells or re-induction of differentiation using growth factors, etc., the aim is to precisely control protein expression and enhance the activity of target cells. To address the uncontrollable in vivo environment, Farhang et al. used the dCas-VPR CRISPR gene activation system to upregulate aggrecan (ACAN) and Col2 [104]. By RNA-seq analysis, Col upregulation was found to mediate broader cartilage gene expression. Besides, dual overexpression of ACAN and Col2 resulted in deposition of sGAG and Col2. As a major component of the ECM, collagen not only provides mechanical support but also controls the growth and differentiation of cells [105]. In conclusion, the dCas-VPR CRISPR system serves as a method to up-regulate endogenous ECM proteins which can well regulate the cell phenotype. Metatropic dysplasia caused by mutations in the TRPV4 (transient receptor potential vanilloid 4) gene is a form of congenital skeletal dysplasia. Nonaka et al. repaired single base mutations in TRPV4 using CRSIPR/Cas9. The results showed that in the presence of TRPV 4-specific agonists, the mutant group showed significantly accelerated cartilage differentiation at early stages and upregulated Sox9 mRNA expression [106]. In brief, a mutation in TRPV 4 is a functional mutation that can lead to an increase in intracellular calcium ion levels. Currently, most clinical cartilage repair involves upregulation of a gene or correction of a mutation. This study provides a new direction for prompting a mutation in a gene to treat cartilage injury. Osteoarthritis is a degenerative disease of cartilage, often resulting from disruption of cartilage integrity or subchondral bone plate lesions [107]. Previous studies have found high levels of transmembrane protein connexin43 (Cx43) expression in osteoarthritic cartilage [108]. Varela-Eirín et al. found that Cx43 maintains the presence of various immature cells present in cartilage by increasing the expression of Twist-1 and MMPs [109] (Fig. 10A). Next, Cx43 also upregulated p16INK4a and NF-κB to cause senescence and apoptosis in cells such as chondrocytes. In the present study, the investigators used CRSIPR/Cas9 to downregulate Cx43 expression and successfully slowed cartilage degeneration. Cx43 is a specific mechanism for chondrocytes towards senescence. Controlling chondrocyte plasticity and apoptosis through targeted treatment of Cx43 is a new approach to treat cartilage diseases. This could also be a potential candidate for promoting cartilage repair in regenerative medicine. Liu et al. designed a therapeutic protocol using modified mesenchymal stem cells (MSC) as implants for cartilage repair [110]. MSC not only contribute structurally to cartilage repair, but also have potent immunomodulatory activity. It can interact with macrophages to coordinate tissue repair in rheumatoid arthritis [111]. The research team selected human synovial-derived MSC to further improve the chondrogenic ability of MSC by modifying the target gene via CRISPR/Cas9. The target gene modified MSC would then become a novel therapeutic option for chronic diseases of cartilage damage like rheumatoid arthritis. Although pluripotent stem cells currently have multiple chondrogenic differentiation options, incomplete differentiation and cellular heterogeneity remain major barriers to cartilage formation [112,113]. MSCs expressing CD105, CD166 and CD146 have been reported to have a higher chondrogenic potential [[114], [115], [116]]. Dicks et al. used CRISPR-Cas9-edited COL2A1-GFP knock-in human pluripotent stem cells [117] (Fig. 10B–F). The aim was to identify cell surface markers of true chondroprogenitor cell populations. Single cell RNA sequencing was then used to analyze the different subpopulations. The results showed that the CD146+/CD166+/PDGFRβ+/CD45- subpopulation of chondrogenic progenitor cells possessed more powerful chondrogenic ability. Or purification by identifying surface markers would greatly improve chondrogenic efficiency.
The establishment of several bone disease models will help to further explore new models of the role of CRISPR/Cas9 in bone repair. Conventional mechanisms of bone repair such as osteoclast-osteoblast homeostasis, matrix mineralization, and scab plasticity are represented in common bone disease models. Osteogenesis imperfecta (OI) is an autosomal dominant disorder that often causes fragility fractures and recurrent fractures [118]. OI is a rare genetic disease and various treatment modalities have failed to achieve good outcomes [119]. With the development of induced pluripotent stem cell (iPSC) strategies, gene editing techniques are gradually being applied in the study of OI. CRISPR/Cas9 can correct patient genes, correct genetic mutations, and repair pathophysiological changes in a comprehensive manner across all processes. The main pathogenic factor of OI originates from impaired type I collagen synthesis. Mutations in COL1A1 and COL1A2 are the direct cause of impaired type I collagen α-chain synthesis [120]. As an important component of the bone matrix, collagen causes impaired bone mineralization and osteoporosis. Jung et al. isolated iPSCs from patients with COL1A1 mutation, and osteogenic induced differentiation resulted in lower than normal collagen type I levels as expected [121]. Increased osteoblast differentiation potential and improved collagen levels after correction of the mutant gene COL1A1 by CRISPR/Cas9. Rauch et al. successfully generated a type V OI mouse model using CRISPR/Cas9 [122]. Type V OI is mainly caused by the MALEP-BRIL mutation in the chromosome-producing IFITM5 gene. The modeling results showed reduced cranial mineralization, curved and shortened long bones and increased rib fragility. The histological findings also showed no formation of primary ossification centers and less cortical bone. The expression of relevant osteogenic markers and angiogenic factors was reduced by monitoring the genetic level of the model. Low level of MALEP-BRIL expression may affect the induced differentiation of osteoblasts.
CRISPR/Cas9 is a powerful gene editing tool with low cost and high efficiency. It has been widely used in biomedical fields and opened a new avenue for regenerative medicine research. However, off-target effects remain one of the non-negligible drawbacks of the CRISPR/Cas9 system [123]. The first step in editing by CRISPR/Cas9 system is to select a target region thus determine the sequence of the target sgRNA. As mentioned earlier, Cas9 cuts the DNA and then completes further modification of the site after the sgRNA recognizes the PAM of the target genome. However, many Cas9 complexes can also bind to non-target regions and accomplish unexpected gene modifications called off-target effects [124]. Off-target effects often result in unwanted sequence mutations or deletions and can even activate oncogenes or cause cell death [125]. This potential side effect of CRISPR/Cas9 greatly limits its application in in vivo translational medicine research and poses a high risk to clinical treatment. If stem cells are edited using CRISPR/Cas9, off-target effects can cause irreversible apoptosis or transdifferentiation of stem cells. The original osteoblasts or chondrogenic cells may become osteoclasts or fibroblasts, which is detrimental to bone or cartilage repair. How to increase the efficiency of precision editing and reduce the off-target rate has become another challenge for researchers. It is well known that the editing efficiency of CRISPR/Cas9 is influenced by the recognition efficiency of sgRNA and PAM, and more than three mismatches between the target sequence and sgRNA may lead to off-target effects [126]. The human genome tends to be many times smaller than the bacterial genome. CRISPR/Cas9 derived from the natural immune system of bacteria tends to have poor specificity in humans and a higher probability of off-target effects than in bacteria [127]. The efficiency of gene editing would be improved if the off-target effects could be detected or quantified by some method in vitro or in vivo. First, the design of sgRNA is crucial. Scientists have developed algorithms based on computer simulation prediction models to detect off-target effects. A computerized prediction program called Cas-OFFinder is not limited by the number of mismatches and allows PAM changes to find potential off-target sites. It is now freely accessible [128] (Fig. 11A). Similar to Cas-OFFinder, CRISPOR (http://crispor.org) is an off-target site scoring tool that allows for better off-target prediction and saves time for researchers' screening [129] (Fig. 11B). The sgRNA is considered to be a key factor for target specificity. Designing a low off-target sgRNA is a challenging task [130]. To reduce off-target effects, scientists have used strategies such as adjusting GC content and sgRNA length. sgRNAs with GC content between 40% and 60% possess a low off-target rate because higher GC content stabilizes the DNA/RNA duplex and reduces binding to non-target regions [131]. Not only that, repetitive bases (a continuous stretch of identical bases) are also associated with new DNA synthesis. Four adjacent guanines are most strongly correlated with low CRISPR activity, which can lead to sgRNAs that do not bind easily to the target sequence [132]. Ren et al. found that the sgRNA GC content of six PAM proximal nucleotides (PAMPNs) was positively correlated with editing efficiency which may provide a more optimal modification [133] (Fig. 11C and D). Interestingly, the length of sgRNAs also affects off-targeting. Fu et al. found that sgRNAs with 17 or 18 nucleotide fragments usually function more specifically than longer sgRNAs [134]. Appropriate shortening of the length of sgRNA might allow for a more efficient CRISPR/Cas9 system. The remaining modifications such as the incorporation of 2ʹ-O-methyl-3ʹ-phosphonoacetate in sgRNA [135] (Fig. 11E), modification of the 5ʹ-end hairpin structure [136], improvement of non-virus delivery methods [137] or selection of Cas variants [138] can reduce the off-target effect to some extent. Rational improvement of some of the factors affecting off-target can help to complete bone or cartilage repair safely and efficiently.
CRISPR/Cas9 editing efficiency often refers to the percentage of target genes that are inserted, replaced or deleted. A higher editing efficiency not only costs less but also accomplishe the desired effect better. Appropriate improvement of editing efficiency is crucial for the application of CRISPR/Cas9 in bone and cartilage repair. Bone and cartilage repair is often accompanied by a longer healing period. Lower editing efficiency may require repeated implantation and testing, or increase cytotoxicity thereby reducing efficacy and prolonging recovery time. Currently, the editing efficiency is mainly improved by optimizing CRISPR/Cas9 sequences, improving delivery systems or changing gene repair strategies. Ma et al. improved gene editing efficiency by optimizing plant codons [139]. However, gene editing in plants and animals is slightly different. The same methods may not be reproducible, but it points to a potential direction. Not only that, the team also suggested that the editing efficiency of CRISPR/Cas9 is also related to the Cas9 expression level, the composition of the target sequence (GC content) and the secondary structure of the sgRNA. This matches the factors associated with the efficiency of animal editing. Similarly, Farboud et al. designed an sgRNA with a GC sequence at the 3’ end. This simple design induced efficient editing [140]. The order of bases determines the specificity of codons and even genes [141]. During the sequence modification or optimization of sgRNA, there are some tricks that may help to improve the editing efficiency. Firstly, guanine will perform better at positions −1 and −2 [142]. Secondly, thymine is not preferred at the four positions close to the PAM. Finally, the −3 position is preferred for cytosine and −5 to −12 for adenine [143]. Consistent with the previous findings, nucleotides downstream of the PAM influence the efficiency of sgRNA more than nucleotide sequences upstream [144]. For CRISPR/Cas9, the mechanisms of NHEJ- and HDR-mediated repair are very different and the editing efficiency varies greatly from cell to cell [145]. In the current study, HDR repair is predominant which acts preferentially in the S or G2 phase and is slightly slower [146]. In contrast, mutations induced by NHEJ are more frequent which acts throughout the cell cycle. This competing repair relationship inspired scientists. Ma et al. mixed Scr7 (DNA ligase IV inhibitor) into the Cas9 protein complex to inhibit NHEJ [147]. The HDR-mediated precision modification was enhanced by inhibiting NHEJ to improve the efficiency of gene editing. Conversely, focusing solely on HDR strategies may also lead to inefficiencies. He et al. integrated the promoterless ires-eGFP fragment into the GAPDH locus and were able to highly express GFP in somatic cells [148]. NHEJ-based editing may be more effective than HDR. For bone and cartilage repair, the differentiation ability of pluripotent stem cells determines the timing and efficiency of repair. Rapid completion of the corresponding editing and significant reduction of healing time are what we need to consider. These results provide a valuable pathway for human stem cell editing. Currently, there is an increasing number of methods to chemically modify Cas9 proteins to improve editing efficiency. Modification of Cas9 proteins by azide-containing noncanonical amino acids (ncAA) has also been reported [149] (Fig. 12A–C). Such a modification allows the recruitment of donor DNA templates to the Cas9 complex. Hemphill et al. designed a light-controlled Cas9, aiming to achieve precise spatiotemporal control by light-regulated Cas9 function [150] (Fig. 12D). The caged Cas9 protein has a specific site for incorporation into photocaged lysine, which is inactivated prior to UV irradiation. It can be restored to normal levels by irradiation at 365 nm for 120 s. This light-activated CRISPR/Cas9 system can edit genes with high precision and also artificially reduce the toxicity of mutations that occur at certain time points. These methods greatly improve the efficiency of HDR-mediated editing and show great potential in the treatment of bone or cartilage damage.
Since CRISPR/Cas9 technique emerged, it has been perfected by many scientists and been playing a major role in several fields of life sciences, agriculture, and bioengineering. Undoubtedly, orthopaedic researchers also endeavored to apply this transgenerational tool in their relevant area, solving the challenges of treating severe bone or cartilage defects, along with bringing new treatment models and promising cures to clinicians. Compared to traditional gene editing techniques that rely on protein guidance, the CRISPR/Cas9 system relies mainly on sgRNA for the recognition of target DNA. This particular mechanism grants the CRISPR/Cas9 system the possibility of high-throughput operation and higher matching precision, and avoids the tedious and costly upfront protein construction engineering. Not only that, Type II CRISPR/Cas9 can accomplish more precise HDR after cutting exogenous DNA. This has a non-underestimated application potential in the balance of human NHEJ-based repair mechanism. The ideal CRISPR/Cas9 delivery methods should be characterized by high efficiency and low toxicity. The commonly used physical or biological delivery methods have been extensively investigated, but physical delivery methods mainly electroporation are limited in clinical applications. Generally, CRISPR/Cas9 for bone or cartilage gene therapy is applied in three main routes. First, the CRISPR/Cas9 gene editing is performed in vitro on osteoblasts or chondroblasts, and then the edited cells are reimplanted in vivo for treatment. Second, gene editing is performed on the reproductive or embryonic cells, by this means to obtain healthier offspring for patients with genetic diseases. However, gene editing for reproductive purposes is the most controversial route which is still an absolute research no-go area. Third, editing happens in vivo after delivery of CRISPR/Cas9 systems to the body via virus or non-viral carriers to complete relevant repairs in vivo. Since all CRISPR/Cas9 clinical trials conducted at this stage are mainly in vitro experiments, the cells need to be isolated from the patients' bodies, edited and then infused back into the patients. This makes CRISPR/Cas9 delivery heavily dependent on viral carriers or nanocarriers. The long-term stability of viral carriers and the modifiability of nanocarriers have demonstrated powerful bone or cartilage repair capabilities in the field of smart delivery. As of now, the gene editing produced by CRISPR/Cas9 is similar to natural mutation in that it does not produce foreign genes, but only involves modifications based on the original genes. In addition, the gene editing tools represented by CRISPR/Cas9 are able to converge more precisely to a purpose that benefits the organism. In the face of many common orthopaedic diseases such as fractures, osteoarthritis, cartilage injuries and bone tumors, relevant vectors were used rationally to knock out disease-causing genes or overexpress antagonistic genes to accomplish fundamental cures from the transcriptional level. Degenerative diseases such as osteoarthritis (OA) are often accompanied by many pathological features involving the upregulation of many genes in the joint tissue. Changes in MMPs or some inflammatory cytokines play an important role in the pathophysiological process of OA. Blockade of certain cytokines by CRISPR/Cas9 will provide new ideas for safe and effective treatment of OA. Also for rheumatoid arthritis (RA) or osteoporosis, CRISPR/Cas9 can target specific sites for editing. Gene therapy can significantly improve the efficacy of inflammatory or immune diseases, and obtaining specific phenotypes by knockdown warrants further attempted studies. Although orthopaedic diseases are influenced by many factors, the relevant target factors are relatively mature and stable. While known loci are studied, relevant effects due to mutations continue to be explored. For orthopaedic diseases, stem cell editing, osteogenic targeting or chondrogenic targeting editing has become a new therapeutic direction. Theoretically, the edited stem cells can be implanted into the body to play a corresponding osteogenic or chondrogenic role, otherwise, the CRISPR/Cas9 components also can be delivered to osteoblasts or chondrogenic cells via vectors. At present, CRISPR/Cas9 technology in orthopaedics is still applied in a single direction, stagnating in the overexpression or silencing of the corresponding mature targets. In the future, we should focus on other cells such as macrophages or fibroblasts, and pay attention to the dynamic process of osteogenesis-osteolysis, and deeply investigate the mechanism of extracellular matrix mineralization. Rational use of CRISPR/Cas9 tools at different entry points to accomplish better orthopaedic applications. Significant breakthroughs have been made in CRISPR/Cas9 technology, but there are still some issues worth discussing in the future. 1. Off-target effects remain the biggest limitation for the development of CRISPR/Cas9 systems at present. Mutations caused by off-targeting may reduce the repair effect. In severe cases, they may alter the phenotype and even trigger inflammatory storms or death. It is not only a matter of editing success rate, but also a matter of safety. Altering the original normal genes or triggering unnecessary mutations can cause irreversible and permanent damage to humans. While improving the way of detecting mutations, the research on the causes of off-targeting should be strengthened. Optimize the conditions of various parameters to ensure safety as much as possible. 2. The efficiency of CRISPR/Cas9 editing can have a direct impact on bone or cartilage therapeutic outcomes. Whether it is improving delivery vectors or modifying sgRNA sequences, these efforts stop at the level of a single cell or a single disease. In the face of frequent bone or cartilage defects, how to maintain the high efficiency editing level is the future direction of development. It is hoped that single cell sequencing technology, microfluidic technology, and microarray screening technology will all be involved in the application of CRISPR/Cas9 editing efficiency enhancement. 3. Faster advancement of human clinical trials based on completion at the cellular and animal levels. Although CRISPR/Cas9 is still quite some time away from being used in the clinic, we cannot stop moving forward. As mentioned earlier, there are very few clinical trials completed and they are mostly oncology related. In the future, more therapeutic modalities such as stem cell editing, mutation gene knockout, etc. are expected in the field of orthopaedics. The challenge of bone or cartilage defects can be faced in a shorter time and with better rehabilitation results. 4. We need to pay attention not only to the efficacy of CRISPR/Cas9 applications, but also to the ethical issues of CRISPR/Cas9-based gene editing therapies. Some side effects of CRISPR/Cas9 such as off-target effects may cause more serious harm to patients. On the other hand, the emergence of gene editing may permanently change the sequence of the human genome and cause irreversible reproductive catastrophe. We need to consider a combination of potential risks, cultural, ethical, regulatory, policy, and public outreach issues. The rational use of this powerful tool can benefit humanity. But how to avoid the risks and maximize the research and development of CRISPR/Cas9 is a question that deserves our consideration.
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PMC9555066 | Kelly L. Sams,Chinatsu Mukai,Brooke A. Marks,Chitvan Mittal,Elena Alina Demeter,Sophie Nelissen,Jennifer K. Grenier,Ann E. Tate,Faraz Ahmed,Scott A. Coonrod | Delayed puberty, gonadotropin abnormalities and subfertility in male Padi2/Padi4 double knockout mice | 12-10-2022 | PAD2,PAD4,Citrullination,Hormone signaling,Estrogen receptor,Androgen receptor,Delayed puberty | Background Peptidylarginine deiminase enzymes (PADs) convert arginine residues to citrulline in a process called citrullination or deimination. Recently, two PADs, PAD2 and PAD4, have been linked to hormone signaling in vitro and the goal of this study was to test for links between PAD2/PAD4 and hormone signaling in vivo. Methods Preliminary analysis of Padi2 and Padi4 single knockout (SKO) mice did not find any overt reproductive defects and we predicted that this was likely due to genetic compensation. To test this hypothesis, we created a Padi2/Padi4 double knockout (DKO) mouse model and tested these mice along with wild-type FVB/NJ (WT) and both strains of SKO mice for a range of reproductive defects. Results Controlled breeding trials found that male DKO mice appeared to take longer to have their first litter than WT controls. This tendency was maintained when these mice were mated to either DKO or WT females. Additionally, unsexed 2-day old DKO pups and male DKO weanlings both weighed significantly less than their WT counterparts, took significantly longer than WT males to reach puberty, and had consistently lower serum testosterone levels. Furthermore, 90-day old adult DKO males had smaller testes than WT males with increased rates of germ cell apoptosis. Conclusions The Padi2/Padi4 DKO mouse model provides a new tool for investigating PAD function and outcomes from our studies provide the first in vivo evidence linking PADs with hormone signaling. Supplementary Information The online version contains supplementary material available at 10.1186/s12958-022-01018-w. | Delayed puberty, gonadotropin abnormalities and subfertility in male Padi2/Padi4 double knockout mice
Peptidylarginine deiminase enzymes (PADs) convert arginine residues to citrulline in a process called citrullination or deimination. Recently, two PADs, PAD2 and PAD4, have been linked to hormone signaling in vitro and the goal of this study was to test for links between PAD2/PAD4 and hormone signaling in vivo.
Preliminary analysis of Padi2 and Padi4 single knockout (SKO) mice did not find any overt reproductive defects and we predicted that this was likely due to genetic compensation. To test this hypothesis, we created a Padi2/Padi4 double knockout (DKO) mouse model and tested these mice along with wild-type FVB/NJ (WT) and both strains of SKO mice for a range of reproductive defects.
Controlled breeding trials found that male DKO mice appeared to take longer to have their first litter than WT controls. This tendency was maintained when these mice were mated to either DKO or WT females. Additionally, unsexed 2-day old DKO pups and male DKO weanlings both weighed significantly less than their WT counterparts, took significantly longer than WT males to reach puberty, and had consistently lower serum testosterone levels. Furthermore, 90-day old adult DKO males had smaller testes than WT males with increased rates of germ cell apoptosis.
The Padi2/Padi4 DKO mouse model provides a new tool for investigating PAD function and outcomes from our studies provide the first in vivo evidence linking PADs with hormone signaling.
The online version contains supplementary material available at 10.1186/s12958-022-01018-w.
Peptidylarginine deiminases (PADs or PADIs) are a family of calcium-dependent enzymes that post-translationally convert positively-charged arginine residues to neutrally-charged citrulline in a process called citrullination or deimination. The loss of charge on target arginine residues following citrullination can significantly alter the target protein’s tertiary structure and affect protein-protein and protein-DNA/RNA interactions [1]. There are five PAD family members (PAD1–4 and 6), with each of the isoforms showing some degree of substrate and tissue specificity [2]. Functional roles for PADs in mammalian physiology and pathology are diverse and include cellular differentiation, nerve growth, apoptosis, inflammation, early embryonic development, and gene regulation [3]. While PAD activity is most closely associated with autoimmune disease [4], previous studies have found that PAD2 and PAD4 are expressed in reproductive epithelial tissues (ie. uterus, luminal breast tissues, endometrium, leydig and sertoli cells) and that their expression is regulated by steroid hormone signaling [5–8]. Steroid hormones are essential mediators of many physiological events including reproduction and development [9]. These hormones carry out their effects by binding to their cognate nuclear receptors which, in turn, bind to hormone response DNA elements and regulate transcription via interaction with a wide range of co-regulators and the basal transcriptional machinery. Given the potential links between PADs and steroid hormones and that histones were found to be targeted by PAD4 for citrullination [10], we previously tested whether PAD2 and PAD4 may play a role in estrogen signaling in breast cancer cells by facilitating ER target gene expression via histone citrullination at ER binding sites. Results from our studies found that PAD4 is recruited to the TFF1 promoter (a canonical ERα binding site) in MCF7 cells following E2 treatment leading to citrullination of histone H4 arginine 3 [11]. Additionally, we found that PAD2 interacts with ER in an estrogen-dependent manner and that estrogen (E2) treatment activates PAD2 leading to citrullination of histone H3 arginine 26 (H3Cit26) at ER binding sites [12, 13]. We then demonstrated by ChIP-Seq that ~ 95% of ER binding sites throughout the genome are citrullinated at H3Cit26 within 5–10 minutes of E2 treatment [14]. We also found that PAD inhibitors potently blocked ER binding at Estrogen Response Elements (EREs) and prevented ER target gene activation [13]. Regarding a potential role for PADs in hormone signaling in males, another group recently found that PAD2 plays a role in androgen receptor (AR) signaling by facilitating nuclear import of AR and promoting AR target gene activation via histone citrullination at AR binding sites in castration resistant prostate cancer cell lines (CRPC; LnCaP and VCaP) [12]. This finding suggests that the role of PADs in regulating hormone-mediated transcription may be broader than we had previously realized. Recent studies have already begun to document the presence of PAD2 in the testis. For example, Tsuji-Hosokawa et al. showed that PAD2 appears to play an important role in testis development and is specifically expressed in fetal Sertoli cells, and that this expression is regulated by SOX9 a critical mediator of sex determination [15]. Another recent study used PCR, western blotting, and IHC to show that Padi2 is expressed in sperm during the first wave of spermatogenesis and appears to localize to the acrosomal region of the sperm head [16]. There are currently no reports of PAD4 localization to the testes, however, IHC analysis of the testis from the Human Protein Atlas (proteinatlas.org) does show anti-PAD4 staining (moderate intensity) specifically in Leydig cells [6]. Importantly, to date, there have not been any published reports linking PADs to hormone signaling in animal models and this lack of in vivo data has likely limited research into this area. To address this gap in knowledge, we began testing for links between PADs and hormone signaling in vivo by determining whether Padi2 and Padi4 single knockout (SKO) mouse lines displayed overt reproductive defects. Initial observations with these mice found that both Padi2 and Padi4 SKO mice appear normal with no overt reproductive defects. Given that the amino acid sequence in PAD family members is 59–70% identical, and that Padi genes are closely clustered together at chromosome 1p35–36 in humans and chromosome 4E1 in mice [3, 17], we predicted that the lack of a conspicuous phenotype in the SKO lines was due to genetic compensation by other Padis. In order to test this hypothesis, we generated a Padi2/Padi4 double knockout mouse (DKO) line by deleting Padi4 from our existing Padi2 knockout (P2KO) mouse line using CRISPR/CAS9 technology. We demonstrate that, as opposed to the SKO lines, the Padi2/Padi4 DKO mice display a range of reproductive defects. Outcomes from our studies focusing on the DKO males show that they display a reduced pup and weanling weight, delayed puberty, reduced testis size, increased rates of apoptosis during spermatogenesis, and altered circulating hormone levels. Our results provide the first in vivo evidence that PADs play a role in male reproduction, potentially via their role in hormone signaling.
All mice used in this work were on an FVB/NJ background and were maintained as inbred homozygous lines. The mice were housed in an AAALAC certified facility, with 12 hours on/off light cycle, temperature control and food and water ad libitum. All procedures were approved by Cornell University’s Animal Care and Use Committee (IACUC) and in compliance with the US National Research Council’s Guide for the Care and Use of Laboratory Animals [18]. Breedings were recorded and lineages tracked with Softmouse Colony Management Software [19]. Euthanasia was performed by CO2 inhalation in accordance with American Veterinary Medical Association approved practice.
Padi2-null mice (FVB/NJ background) were generated using gene trap technology at the Texas A&M Institute for Genomic Medicine [20]. For the gene trap, 163 nucleotides of exon 1 in Padi2 (from the ATG initial codon to intron 1–2) were replaced by the LacZ and Neomycin coding sequence. These mice are genotyped in a multiplex mixture using Padi2 WT and KO specific primers (Table 1). Padi4-null mice (FVB/NJ background) were generated using Regeneron’s VelociGene technology. The genomic sequence of Padi4 from the ATG initial codon to approximately 100 bp downstream of the TGA stop codon was replaced in frame (with respect to the Padi4 initiation codon) with a Lox-flanked LacZ and neomycin coding sequence. These mice are genotyped using Padi4 primers shown in Table 1.
Padi2-null mice were used for IVF and CRISPR/Cas9 RNA injection was performed at Cornell’s Stem Cell & Transgenic Core Facility. Cas9 mRNA and Padi4 sgRNA targeting Exon 1 of the Padi4 gene were injected into the pronucleus of Padi2 KO embryos and the embryos were cultured to the two-cell stage and transferred into pseudopregnant recipient FVB/NJ female mice [21, 22]. Thirty-nine founders were produced and 13 edited founders were then identified by heteroduplex PCR [23]. Briefly, genomic DNA was extracted from punched ear tissue and evaluated by PCR using the Padi4 primer set noted above. Standard PCR conditions for GoTaq (Promega) were used as follows: 95 °C for 5 min; 94 °C for 30 s, 59 °C for 30 s, 72 °C for 30s for 35 cycles; 72 °C for 5 min followed by 5 minutes of denaturation at 95 °C. PCR products were loaded onto a 12% polyacrylamide gel. Positive heteroduplex bands were purified and subjected to TA cloning for Sanger sequencing. All 13 edited founders were found to be heterozygous mutants, with 7 founders being identified as having a frameshift mutation either by insertion or deletion. One heterozygous founder with a four-nucleotide deletion was back-crossed to the background Padi2 knockout mice, and their heterozygous offspring were then paired to create a homozygous DKO line (Fig. 1).
Total RNA was extracted from mouse salivary glands using Tri-Reagent (Molecular Research Center #TR118) and cDNA was created with a High Capacity RNA-to-cDNA Kit (Applied Biosystems #4387406) according to manufacturers’ instructions. PCR amplification was accomplished under standard cycling conditions with GoTaq (Promega #M3001) using primers listed in Table 1. PCR products were run on a 2% agarose gel to confirm the presence or absence of Padi transcripts (Fig. 2a,d; Additional File 1).
Genomic DNA was isolated from ear-punch tissue samples and the Padi4 locus was amplified under standard GoTaq conditions using primers listed in Table 1. PCR products were run on a 2% Agarose gel to confirm the presence or absence of the Padi4 gene (Fig. 2b).
Tissue lysate was prepared from splenic tissue and resolved by SDS-PAGE followed by transfer to a PVDF membrane. The membranes were incubated overnight with primary antibodies diluted in 1% BSA-TBST at 4 °C using the following concentrations: anti-PAD4 (1:1000; Abcam; ab214810), anti-PAD2 (1:1000, Proteintech, 12,110–1-AP) and anti-actin (1:1000, Abcam, ab-8227). The primary antibodies were detected with HRP-conjugated secondary antibodies and were exposed to ECL reagents to determine the presence or absence of PAD2 and PAD4 proteins (Fig. 2c).
Seven-week old virgin mice were paired in the following ‘male x female’ matings: DKOxDKO, DKOxWT, WTxDKO or WTxWT (n = 5–6 pairs per group). Pairs were monitored daily for 63 days and birth dates, litter sizes, sex ratios, 2-day old pup weights, and weanling weights were recorded. Statistical analyses were carried out using Microsoft Excel and Social Science Statistics calculators for unpaired Student’s t-test, ANOVA, 𝟀2 and Goodness of Fit tests with significance set at P = 0.05 [24].
Male weanlings were housed singly (to avoid intra-cage dominance issues), weighed and monitored daily for preputial separation as previously described [25]. Growth curves are provided in Supplemental Fig. S2 (Additional file 2). Mice were euthanized for tissue harvest at ages 46, 48, 50 and 90 days old. At each of these time points, five mice were euthanized by CO2 inhalation and blood was collected by cardiac puncture, allowed to clot at room temperature for 90 minutes, spun at 2000 g for 15 minutes, and the serum was snap frozen and saved for hormone analysis. Serum testosterone, Follicle Stimulating Hormone (FSH), and Lutenizing Hormone (LH) levels were quantified in duplicate by ELISA at the University of Virginia Ligand Assay Core. Testes, epididymis, vas-deferens, seminal vessicles and spleen were harvested and one testis was immediately snap frozen for RNA analysis. The remaining tissues were fixed in 10% formalin for preliminary histological evaluation. Results were analyzed with unpaired t-tests with significance set at P = 0.05.
Testis, epididymis, vas deferens, seminal vesicle and splenic tissues were collected at 90 days from 5 animals from each of the following strains: Wild-type (WT, FVB/NJ), P2KO, P4KO, and DKO. Collected tissues were fixed in 10% formalin solution, embedded in paraffin, sectioned at 5 μm, and stained with hematoxylin and eosin (H&E). Initial evaluation revealed epididymis, vas deferens, seminal vesicles, and spleen within normal limits based on previously published observations [26, 27], therefore, only testis sections were evaluated further. The noted changes were scored on a scale of 0 to 3 according to the following criteria: 0 = absent to affecting less than 5% of the tissue; 1 = mild change, affecting 5–25% of the tissue; 2 = moderate change, affecting 25–50% of the tissue; 3 = severe change, affecting > 50% of the tissue (Table S1, Additional file 3).
Mouse testes were dissected from four-month old mice, two per strain (WT, P2KO, and DKO), and snap-frozen immediately following euthanasia. Total RNA extraction was performed using TRI reagent (Molecular Research Center, Inc. OH) according to the manufacturer’s protocol. The RNA concentration and purity were measured by Nanodrop and Qubit (Thermo Scientific, USA). RNA-seq experiments were performed in the Transcriptional Regulation & Expression Facility (TREx) at Cornell University. RNA integrity was confirmed on a Fragment Analyzer (Agilent) and RNAseq libraries were prepared using the NEB Ultra II Directional RNA library Prep kit (New England Biolabs), with 1 μg total RNA input and initial poly(A) selection. Illumina sequencing was performed on a NovaSeq to generate at least 20 M 2 × 150 paired end reads per sample. The raw fastq reads were first processed with the Trim Galore package to trim for low quality reads, noisy short fragments, and adapter sequence [28]. The filtered reads were then aligned to the GRCm38 reference genome (mm10) with ENSEMBL annotations via STAR using parameters [−-outSAMstrandField intronMotif, −-outFilterIntronMotifs RemoveNoncanonical, −-outSAMtype BAM SortedByCoordinate, −-quantMode GeneCounts] [29]. Differential gene expression analysis was performed by DESeq2 [30, 31], with an FDR cut-off of 0.05 and a Benjamini-Hochberg adjusted P value (p-adj) < 0.05 to establish significance. A heatmap and hierarchical clustering dendrogram of differentially expressed genes was produced using Morpheus [32]. Venn diagrams were produced with BioVenn [33]. Gene ontology classification analysis was performed using DAVID v6.8, a web-based bioinformatics resource for functional genomics analysis to identify biological processes, molecular functions, and cellular components [34, 35]. Two hundred and forty-six genes were identified as uniquely upregulated in DKO testes compared to WT. Two hundred and thirty-eight of these genes were identified in the DAVID database and used for subsequent analysis.
Our strategy for generating the Padi2/Padi4 DKO mouse line is shown in Fig. 1a. Padi2-null males and females were bred to generate Padi2-null zygotes and these embryos were then injected with a Padi4 sgRNA construct and transferred to wild type (FVB/NJ) recipient females to generate founder pups. The Padi4 sgRNA construct was designed to target Exon 1 of the Padi4 gene (Fig. 1b). In total, 39 founders were born, with 13 CRISPR-edited founders being identified by heteroduplex PCR, subcloning, and Sanger sequencing. All of the edited founders were heterozygous mutants, with seven of these founders having a frame-shift mutation. Following back breeding to P2KO, crossing the heterozygous F1 offspring, and genotyping successive generations, one homozygous DKO strain was established and selected for further characterization. This mutant mouse line contained a four-nucleotide deletion in Exon 1 of Padi4 (Fig. 1c) and a predicted premature stop codon (Fig. 1d). Validation of the DKO mutant line is shown in Fig. 2. We first confirmed that P2KO and DKO mice lacked Padi2 transcripts by RT-PCR analysis of salivary gland (Fig. 2a). We next tested whether the Padi4 sgRNA targeted site in DKO mice contained a deleted sequence by performing PCR analysis of genomic DNA and then separating the DNA fragments on high percentage polyacrylamide gels. Results showed that the DKO amplicon displayed a reduced molecular weight when compared to the P2KO and WT amplicons (Fig. 2b), suggesting that DKO mice contained the targeted deletion, as was shown by Sanger sequencing of the Padi4 locus (Fig. 1c). As expected, no amplicon was observed in P4KO mice. The above results suggested that DKO mice lacked both Padi2 and Padi4 transcripts. We then performed Western blot analysis of WT, P2KO, P4KO and DKO spleen lysates to test if the DKO mice also lacked PAD2 and PAD4 protein. We probed the protein lysates with anti-PADI2 antibodies and found that, while the antibody was reactive with appropriately sized ~ 75 kDa bands in the WT and P4KO lysates, the antibody did not react with similarly sized bands in the P2KO and DKO mice (Fig. 2c, Additional file 1). Likewise, the anti-PADI4 antibody was reactive with ~ 75 kDa bands in the WT and P2KO lysates but was not reactive with similarly sized bands in the P4KO and DKO lysates (Fig. 2c, Additional file 1). These results indicate that the Padi2/Padi4 DKO strain does not express mature PAD2 and PAD4 proteins. Lastly, we found by RT-PCR that the transcripts of Padi1 and Padi3 continue to be expressed in our DKO mice, indicating that the observed phenotype was due to the disruption of Padi2 and Padi4 and that the other Padi loci remain intact (Fig. 2d).
In order to begin testing for links between PADs and reproductive function, we first performed a controlled breeding trial to test whether a range of reproductive parameters were affected by DKO. Seven-week old mice were paired in 4 mating categories (WTxWT, DKOxDKO, DKOxWT and WTxDKO) and monitored daily for 63 days. Results showed that, although not statistically significant, DKOxDKO pairs tend to lag behind WTXWT pairs in the time taken to have their first litter (Fig. 3a). To identify which sex may be responsible for this reproductive delay, we bred DKO males with WT females and DKO females with WT males, and the trend towards decreased fertility remains more apparent for DKO males than for females (Fig. 3a). With respect to the offspring produced during the breeding trials in this report, we found that the sex ratio of homozygous DKO offspring was skewed (0.85 male:female) but did not deviate significantly from the expected equal ratio (𝝌2 test, n = 243, P = 0.22), and that the average DKO litter size was the same as WT mice (two-tailed t-test, n = 4, P = 0.5). We also observed that unsexed 2-day old DKO pups from these same litters weighed significantly less than WT pups (Fig. 3b, n = 4 litters per strain, P = 0.004) and that DKO male weanlings weighed significantly less than WT (Fig. 3c-d, n = 21,45, P = 0.003; Fig. S2, Additional file 2). Taken together, results from these studies suggest that loss of both PAD2 and PAD4 suppresses fertility and affects offspring weight. Previous studies have shown that pup weight is also commonly reduced in sub-fertile mouse strains, including androgen receptor knockout (ARKO) mice [36] which is relevant to the research reported here. Given the growing links between PADs and hormone signaling, we predicted that the effect of DKO on both fertility and pup weight was due to disrupted hormone signaling in these mice.
Pubertal onset is thought to be primarily driven by increased testosterone production in males and one well-established external marker of pubertal development in rodents is preputial separation (PS) [25, 37, 38]. Therefore, as a further test of the hypothesis that hormone signaling is disrupted in DKO males, we next documented the timing of PS. Results show that DKO males took an average of 3.6 days longer than WT or SKO males to undergo PS (31.2 vs 27.6 days: ANOVA, P < 0.0001, Fig. 4a,b). Given that the timing of pubertal onset has been repeatedly, yet inconsistently, linked with obesity [39, 40], and been shown to differ between sexes within the same species/strain [41], we asked whether the delayed puberty in DKO males could be a side-effect of their smaller size at weaning. This does not appear to be the case, as DKO males are significantly heavier than WT and SKO at time of PS (ANOVA, P = 0.0002, Fig. 4c), and the mean weight of males, regardless of strain, was the same at day 27, which is the average day of PS in WT and SKO (ANOVA, P < 0.0001, Fig. 4d). Preputial separation is known to be an androgen-dependent process [38, 42], strongly linked to hormone signaling along the hypothalamic-pituitary-gonadal (HPG) axis [43, 44]. These results further support the hypothesis that hormone signaling may be altered in DKO males. Additionally, these observations suggest that PAD2 and PAD4 play an important role in androgen-driven sexual development in males.
As a more direct test of the hypothesis that hormone levels are altered in DKO mice, we next measured serum testosterone (T), luteinizing hormone (LH), and follicle stimulating hormone (FSH) in WT and DKO males. Results showed that levels of T, LH, and FSH differed significantly between DKO and WT at multiple timepoints (n = 5 per time point). Although highly variable, serum testosterone levels were lower in DKO males than WT males at all time-points, most significantly at day 48 (P = 0.05, Fig. 5). In contrast, FSH and LH levels were statistically similar between DKO and WT at the earlier time points, but at day 50 both hormones were significantly higher in DKO sera (P < 0.03). Although it is difficult to infer signaling responses from this data due to use of serum from different individual mice at each timepoint rather than sequential levels from the same mice across time,we were encouraged by the observation that serum T levels were consistently lower in DKO mice regardless of age, and that LH and FSH differed significantly between strains. Importantly, studies with ARKO mice also found that serum T levels are lower in mutant mice compared to WT mice [36]. Given this observation, our findings lend support to the prediction that PAD enzymes play a role in androgen signaling in vivo.
Hormone signaling within the HPG axis not only regulates pubertal onset, but also regulates body growth [41] and testis size [45, 46]. As a further test for potential associations between PADs and hormone signaling, we next investigated whether the total body weight and testis weight was altered in 90-day old adult DKO mice. Results showed that, while there was no difference in total body weight between the WT (m = 27.4 g) and DKO (m = 27.4 g, n = 5,2-tailed t-test, P = 1), both absolute testis weight (P = 0.002) and the gonadosomatic index (testis weight as a percent of body weight) (P = 0.037) were significantly lower in DKO mice (Fig. 6a,b). Yeh et al. found that both pup size and testis weight are reduced in AR knockout mice [36], and our finding that DKO testes are significantly smaller than WT testes in adults fits well with the hypothesis that PADs play a role in androgen signaling in males.
The observation that DKO testes are smaller than WT testes raised the possibility that testicular histology may also be defective in DKO males. To test this hypothesis, FFPE sections of adult testes were stained with H&E and scored for cellular morphology by a board-certified pathologist (Table S1, Additional file 3). Results of this analysis found that there were variable degrees of germ cell apoptosis in the DKO testes when compared to WT testes, with spermatogonia and spermatocytes being the most significantly affected (Fig. 6c-f). More specifically, apoptosis (mild/moderate grade) in spermatocytes (Fig. 6d) was noted in 5 out of 5 DKO mice compared to only 2 out of 5 WT samples. Apoptosis (mild grade) of spermatogonia (Fig. 6e) was noted in 4 out of 5 DKO mice testes compared to only 1 out of 4 WT mice. All five DKO testes also displayed moderate grade residual bodies (Fig. 6f) when compared with WT testes, which only displayed mild grade residual bodies. Sertoli, Leydig cells and interstitium were overall unremarkable. The increased rate of apoptosis and residual bodies did not appear to result in a decrease in sperm production with the lumen of most tubules being lined with histomorphologically unremarkable elongated spermatids and spermatozoa. Interestingly, in ARKO mice, spermatogenesis was arrested at the pachytene stage of meiosis and there was an increase in apoptotic-like bodies within the tubules [36] suggesting that androgen signaling is critical for normal spermatogenesis. Taken together, these results support the hypothesis that PAD2/4 signaling may play a role in androgen signaling-mediated spermatogenesis.
In order to begin investigating whether PADs are associated with specific signaling pathways in the testis, and to more directly test the hypothesis that PAD2/4 play a role in regulating AR target gene expression, we next carried out RNA-Seq analysis of adult WT, P2KO, and DKO testes. Results show that 22 genes were upregulated and 19 genes were downregulated in P2KO samples when compared to WT samples (FDR cut-off 0.05, p-adj < 0.05). Additionally, we found that 263 genes were upregulated and 140 genes were down-regulated in the DKO samples compared to WT samples (FDR cut-off 0.05, p-adj < 0.05). Seventeen of the 22 genes that were significantly upregulated in the P2KO samples were also upregulated in the DKO samples. A comparison of upregulated genes is shown in Fig. 7a, with the complete lists of differentially expressed genes (DEGs) provided in Tables S2 andS3 (Additional files 4 and 5). Two hundred and forty-six genes that were uniquely upregulated in DKO testes were then subjected to DAVID gene ontology analysis. Of the 246 genes, 238 were identified in the mouse database and these genes were categorized into three domains: Cellular Components, Molecular Functions, and Biological Processes (Table S4, Additional file 6). Analysis of the Biological Processes domain finds that a majority of the DEGs are involved in reproductive functions (Fig. 7b), thus supporting the phenotypic traits we observed. In addition, analysis of the Molecular Function domain finds that nearly all of the DEGs appear to be involved in either nucleic acid binding or protein phosphorylation (Fig. 7c), thus further supporting the hypothesis that PADs play a role in regulating gene transcription. We next generated a hierarchical dendrogram and heatmap showing the top 100 most significantly up- and downregulated genes using summary counts over all pairwise tests of WT, P2KO, and DKO samples (FDR cut-off 0.05, p-adj < 0.05; Fig. 8; Table S5, Additional file 7). Results show that there is a good correlation in gene expression levels between replicates for each experimental group. Additionally, the gene expression profile for the DKO samples is distinctly different from that of the WT samples, while there are some overlapping expression patterns when comparing the DKO and P2KO samples. We next narrowed this pool down to 41 transcripts that showed at least a 2-fold difference between strains for further investigation of their known activities. For this analysis, we used The Jackson Laboratory’s Mouse Genome Informatics (MGI) databases [47, 48] and we reveiwed the current literature. Of these 41 transcripts, 15 were identified as lncRNAs, 20 were from protein coding genes, and 6 were undescribed or pseudogenes. lncRNAs are generally known to be involved in transcriptional regulation through either binding DNA directly or changing methylation patterns on chromatin. Alternatively lncRNAs can directly interact with other chromatin modifiers to recruit or deflect their action on transcription [49, 50]. One lncRNA worth mentioning here, Snhg12, has been linked to regulation of the cell cycle and promotion of the Epithelial-Mesenchymal Transition in embryogenesis [51]. In addition, Snhg12 has been shown to promote cell proliferation and inhibit apoptosis in multiple cancers [52], including testosterone-sensitive prostate cancer [53]. Although we do not propose a mechanism, the almost 3-fold decrease in Snhg12 levels in our DKO mice suggests loss of this factor may have played a significant role in the increased apoptosis and atypical residual bodies that are seen in Fig. 6. The 20 protein coding genes showing more than a 2-fold change in expression between DKO and WT included multiple members of two important gene families. First, the Kallikreins are a family of serine peptidases, many of which have been linked to AR expression and progression of androgen sensitive prostate cancer cells [54]. Perhaps the best-known member of this family is prostate-specific antigen (KLK3), whose expression is mainly induced by androgen and is transcriptionally regulated by the androgen receptor [55]. Additionally, the kallikrein gene locus is highly responsive to steroid hormones, having at least 14 functional HREs in this region. In fact, many researchers use kallikreins as markers of hormone receptor activity [56]. In our DKO mice, Klk21, Klk24 and Klk27 are increased 3-fold compared to WT, and these three kallikreins have been shown to be expressed exclusively in Leydig cells and be responsive to testosterone [57]. Additionally, these 3 kallikreins are upregulated in the FOXa3 KO mouse model which shows severe testicular degeneration, increased gonadal apoptosis and decreased fertility [57]. The second over-represented group in our DKO mice are Zinc-finger proteins, a diverse family generally known as regulators of gene expression. Six Zinc-finger proteins are differentially expressed in our DKO mouse testes, two of which are of particular interest here. Zfp982 has previously been shown to be involved in cell lineage differentiation in embryogenesis [58] and the 12-fold decrease in levels of this factor in our DKO mice may have significantly disrupted developmental processes. Zfp979 (also known as Ssm1b) initiates DNA methylation and inhibits transcription in undifferentiated embryonic stem cells as well as in adult murine germ cells [59]. The 20-fold decrease of Ssm1b seen in our DKO testes could allow expression of a multitude of proteins detrimental to early development and germ cell maturation. Within the remaining differentially expressed coding genes, several stand out as relevant to our discussion for their potential roles in steroid signaling and the HPG axis. Runx3 is decreased 6-fold in our DKO testes. This factor has been shown to regulate steroidogenesis and gonadal development in female mice [60]. Whether it acts similarly in male mice is currently unknown. Mutations in Spry4, which is upregulated 3-fold in our DKO testes, have been implicated in incomplete sexual maturation and infertility due to decreased GnRH activity in human males [61]. Sdc3 (upregulated 12-fold) is considered a regulator of obesity and has been proposed as a modulator of gonadal steroid function [62]. And finally, altered levels of Mrto4 in Balb/C mice (upregulated 3 fold in our DKO) have been linked to disruptions in spermatogenesis, fertility and testosterone levels in mice [63]. These findings further support our hypothesis that PADs play an important role in regulating gene expression in the testis, and more specifically, in regulating AR-mediated gene expression.
Our previous work with PAD2 and PAD4 in breast cancer cell lines has found that both of these PAD isozymes appear to regulate ER target gene expression via citrullination of histone residues at ER binding sites. More recent studies have shown that PAD2 also appears to facilitate androgen receptor target gene expression in prostate cancer cells via similar mechanisms. Together, these observations suggest that PAD2 and PAD4 may represent key mediators of hormone signaling in mammals. While these in vitro findings are intriguing, an important next step in linking PADs with hormone signaling is demonstrating that the phenomenon also occurs at the organismal level. While our Padi2 and Padi4 SKO mouse models have failed to show a reproductive phenotype, outcomes from our Padi2/Padi4 DKO studies provide a series of clear associations between PADs and hormone signaling and, to our knowledge, this study is the first to make such genetic links using animal models. We predict that the phenotypic effects of DKO that we have observed in this study are due to the lack of PAD2 and PAD4 activity in the testis. Our DKO mice described here exhibit several phenotypic traits (delayed puberty, small offspring and decreased serum testosterone) that are characteristic of other sub-fertile strains, including a number of AR knockout mouse models [64]. Since PAD2 and PAD4 have previously been implicated in interactions with estrogen and androgen receptors, it is not unexpected to see reproductive defects in these mice. However, our additional finding of abnormal serum testosterone, LH and FSH levels indicates a wider reaching disruption of the HPG axis with implications for more than just reproductive fitness.
Additional file 1: Fig. S1. Full PCR gels and membranes for authentication of DKO mice.Additional file 2: Fig. S2. Growth curves of WT, SKO and DKO mice.Additional file 3: Table S1. Histological scoring of cellular abnormalities in 90-day old WT and DKO testes.Additional file 4: Table S2. Significantly differentially expressed genes in 4-month old DKO testes compared to WT (FDR < 0.05 and Benjamini-Hochberg p-adj < 0.05).Additional file 5: Table S3. Significantly differentially expressed genes in 4-month old P2KO testes compared to WT (FDR < 0.05 and Benjamini-Hochberg p-adj < 0.05).Additional file 6: Table S4. DAVID results of gene ontology categories over-represented in 4-month old DKO testes compared to WT.Additional file 7: Table S5. Top 100 most up- and downregulated genes from 4-month old testes (FDR < 0.05 and Benjamini-Hochberg p-adj < 0.05), ranked by Fold Change and used to create the heatmap in Fig. 8. | true | true | true |
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PMC9555114 | Haein Ji,Tae Won Kim,Woo Joo Lee,Seong Dong Jeong,Yong Beom Cho,Hyeon Ho Kim | Two circPPFIA1s negatively regulate liver metastasis of colon cancer via miR-155-5p/CDX1 and HuR/RAB36 | 12-10-2022 | Colorectal cancer,Liver metastasis,circPPFIA1,miR-155-5p,CDX1,HuR,RAB36 | Background Circular RNAs (circRNAs) play a critical role in colorectal cancer (CRC) progression, including metastasis. However, the detailed molecular mechanism is not fully understood. Methods Differentially expressed circRNAs between primary KM12C and liver metastatic KM12L4 colon cancer cells were identified by microarray. The expression of circRNAs was measured by semi-quantitative (semi-qPCR) and real time-quantitative PCR (RT-qPCR). Metastatic potential including invasive and migratory abilities, and liver metastasis were examined by transwell assays and intrasplenic injection, respectively. CircPPFIA1-associated microRNA (miRNA) and RNA-binding protein (RBP) were screened by an antisense oligonucleotide (ASO) pulldown experiment. The effects of circPPFIA1 on target gene expression were evaluated by RT-qPCR and western blot analyses. Results By analyzing circRNA microarray data, we identified two anti-metastatic circRNAs generated from PPFIA1 with different length, which named circPPFIA1-L (long) and -S (short). They were significantly downregulated in liver metastatic KM12L4 cells compared to primary KM12C cells. The knockdown of circPPFIA1s in KM12C enhanced metastatic potential and increased liver metastasis. Conversely, overexpression of circPPFIA1s weakened metastatic potential and inhibited liver metastasis. circPPFIA1s were found to function as sponges of oncogenic miR-155-5p and Hu antigen R (HuR) by an ASO pulldown experiment. circPPFIA1s upregulated tumor-suppressing CDX1 expression and conversely downregulated oncogenic RAB36 by decoying miR-155-5p and by sequestering HuR, respectively. Conclusion Our findings demonstrate that circPPFIA1s inhibit the liver metastasis of CRC via the miR-155-5p/CDX1 and HuR/RAB36 pathways. Supplementary Information The online version contains supplementary material available at 10.1186/s12943-022-01667-w. | Two circPPFIA1s negatively regulate liver metastasis of colon cancer via miR-155-5p/CDX1 and HuR/RAB36
Circular RNAs (circRNAs) play a critical role in colorectal cancer (CRC) progression, including metastasis. However, the detailed molecular mechanism is not fully understood.
Differentially expressed circRNAs between primary KM12C and liver metastatic KM12L4 colon cancer cells were identified by microarray. The expression of circRNAs was measured by semi-quantitative (semi-qPCR) and real time-quantitative PCR (RT-qPCR). Metastatic potential including invasive and migratory abilities, and liver metastasis were examined by transwell assays and intrasplenic injection, respectively. CircPPFIA1-associated microRNA (miRNA) and RNA-binding protein (RBP) were screened by an antisense oligonucleotide (ASO) pulldown experiment. The effects of circPPFIA1 on target gene expression were evaluated by RT-qPCR and western blot analyses.
By analyzing circRNA microarray data, we identified two anti-metastatic circRNAs generated from PPFIA1 with different length, which named circPPFIA1-L (long) and -S (short). They were significantly downregulated in liver metastatic KM12L4 cells compared to primary KM12C cells. The knockdown of circPPFIA1s in KM12C enhanced metastatic potential and increased liver metastasis. Conversely, overexpression of circPPFIA1s weakened metastatic potential and inhibited liver metastasis. circPPFIA1s were found to function as sponges of oncogenic miR-155-5p and Hu antigen R (HuR) by an ASO pulldown experiment. circPPFIA1s upregulated tumor-suppressing CDX1 expression and conversely downregulated oncogenic RAB36 by decoying miR-155-5p and by sequestering HuR, respectively.
Our findings demonstrate that circPPFIA1s inhibit the liver metastasis of CRC via the miR-155-5p/CDX1 and HuR/RAB36 pathways.
The online version contains supplementary material available at 10.1186/s12943-022-01667-w.
Colorectal cancer (CRC) is the third most common type of malignant tumor and the second leading cause of cancer-related death [1]. Despite advances in treatment, the prognosis of CRC patients is poor, and the mortality rate of CRC continues to rise. The main cause of high mortality is liver metastasis of CRC [2, 3]. Twenty percent of patients with CRC present with metastasis at the time of diagnosis, and approximately 50% eventually develop liver metastasis [4]. Moreover, the overall 5-year survival rate of patients with liver metastasis is only 14% [5]. Recent CRC research on the development of diagnostic and therapeutic targets has gradually expanded from protein-coding genes to non-coding RNAs, such as microRNAs (miRNAs), antisense transcripts, long intergenic non-coding RNAs, and circular RNAs (circRNAs) [6, 7]. Although they are recognized as splicing error, circRNAs have been actively investigated as a means of controlling gene expression [8]. CircRNAs are predominantly generated by back-splicing and are characterized by a covalently-closed loop structure without a 5’ cap and 3’ poly-A tail [9]. Due to their special structure, circRNAs have a higher tolerance to exonucleases, making them remarkably stable. Although their biogenesis is largely unknown, circRNAs are a powerful tool in the diagnosis and treatment of cancer [10–12]. Several circRNAs are reported to influence metastatic potential by acting as sponges of microRNA (miRNA) and RNA-binding protein (RBP) in CRC [13–15]. For example, two miR-145-5p-sponging circRNAs, circRUNX1 and circPVT1, promote CRC metastasis by upregulating target expression [16, 17]. Circ_0001178 enhances metastatic potential of CRC by hindering ZEB1-targeting miR-382/587/616 [18]. Conversely, circITGA7 inhibits the lymphatic metastasis of CRC through miR-370-3p/NF1 [19]. Here, we aimed to identify novel circRNAs that can control the liver metastasis of CRC. Through a circRNA microarray, two circPPFIA1s were found to be downregulated in liver metastatic CRC. Transwell assays and intrasplenic injection mouse experiments revealed that circPPFIA1s negatively regulated metastatic potential and liver metastasis of CRC. Furthermore, we found that circPPFIA1s exhibited anti-metastatic effects by sponging oncogenic miR-155-5p, thereby increasing caudal type homeobox 1 (CDX1) expression, and decreasing the expression of RAB36 via the sequestration of an oncogenic RBP, Hu antigen R (HuR). Taken together, we demonstrated that circPPFIA1s are promising therapeutic targets for treatment for liver metastatic CRC.
All tissues were collected from CRC patients who had undergone surgery at Samsung Medical Center (Seoul, Korea). Six pairs of primary CRC tumor tissues and corresponding liver metastatic tumor tissues were obtained from surgical resections of CRC patients without any radiotherapy or chemotherapy before surgery. The samples were pathologically confirmed and stored in liquid nitrogen after surgery until use. All human specimens were approved by the Institutional Review Board of the Samsung Medical Center (IRB approval No. 2010-04-004 and 2019-03-054). Written informed consent was obtained from all patients.
The expression levels of circPPFIA1-L and -S in tissues were assessed by BaseScope Assay (Advanced Cell Diagnostics, Newark, CA, USA). Basescope probes for circPPFIA1-L and -S were designed to target the junction sequences of circPPFIA1-L and -S. BaseScope assays were performed using BaseScope Detection Reagent Kit-RED (ACD, Cat. No. 322,900) in accord with the manufacturer’s protocol. Fast RED followed by counterstaining with hematoxylin (Cancer Diagnostics, Inc. USA). The images were visualized using ScanScope AT turbo (Aperio, CA) and analyzed by ImageScope (Aperio, CA).
Primary and liver metastatic CRC cells (KM12C and KM12L4, respectively) and colorectal cancer cells (DLD1 and RKO) were cultured with Dulbecco’s modified Eagle’s medium (Gibco, Grand Island, NY, USA). All cell lines were free of mycoplasma contamination and verified by STR analysis (Supplementary Table S1). Cells were transfected with small interfering RNAs (siRNAs) and miRNAs using Lipofectamine 2000 (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s protocol. Detailed information on transfection was shown in Supplementary methods.
Total RNA was isolated from KM12C and KM12L4 cells using TRIzol reagent (Invitrogen, Thermo Fisher Scientific) as described by the manufacturer’s protocol. The circRNA microarray was performed by Arraystar (Arraystar, Rockville, MD, USA). The differentially expressed circRNAs were analyzed with the criteria of p < 0.05 and fold-change > 2.0 (Supplementary Figure S2).
The circular structure of circPPFIA1-L and -S was confirmed by testing the stability via RNase R resistance and actinomycin D treatment. To verify the divergent region of circPPFIA1-L and -S, Sanger sequencing was carried out. Detailed information on experimental procedures was shown in Supplementary methods.
The RIP assay was performed using Dynabeads® Protein G (Thermo Fisher Scientific) as described in a previous report [20]. Briefly, the beads were coated with IgG or the indicated antibody (Ago2 antibody, Sigma, St. Louis, MO, USA or HuR antibody, Santa Cruz Biotechnology, Dallas, TX, USA). After equal amounts of PEB lysate were incubated with antibody-coated Dynabeads for 4 h, the beads were washed several times with NT2 buffer (Supplementary Table 4). Following treatment with DNase I (Ambion) and protease K (Bioneer), RNA was isolated by precipitation with absolute ethanol. The level of mRNA in RIP was quantified by RT-qPCR.
To identify circPPFIA1-associated miRNAs and RBPs, an ASO pull-down assay was performed using non-overlapping biotinylated ASOs recognizing the convergent region of each circPPFIA1. Three and two ASOs were prepared for circPPFIA1-L and -S, respectively (Supplementary Figure S14). PEB lysates were incubated with 1 µg of biotinylated ASOs at 4 °C for 2 h. After incubation, 40 µl of pre-washed streptavidin-coupled Dynabeads™ (Invitrogen) were added for 4 h at 4 °C. LacZ ASO was used as a negative pulldown control (Supplementary Figure S15C). The RNA was isolated from the pull-down materials using TRIzol, and RT-qPCR or western blot analysis was performed to check the level of miRNA or RBP, respectively.
Six- to seven-week-old female BALB/c nude mice (Orient Bio, South Korea) were anesthetized with a mixture of ketamine (#7001, Seoul, South Korea) (30 mg/kg) and xylazine (Rompun®, Bayer, Leverkusen, Germany) (10 mg/kg) via intraperitoneal injection. A small left abdominal flank incision was made, and the spleen was exteriorized for intrasplenic injection. For the preparation of the cells to be injected, KM12C and KM12L4 cells were transfected with circPPFIA1 siRNA or the overexpression vector, respectively. An equal number of transfected cells (2.0 × 106 cells) were suspended in 50 µl of Hanks’ Balanced Salt Solution (Gibco) and injected into mouse spleens with a 30-gauge needle. After 4 weeks, we examined the liver metastasis with magnetic resonance imaging (MRI) and sacrificed the mice to obtain liver tissues. The animal experiments were performed in a specific pathogen-free animal experiment center at the Samsung Medical Center. Ethics approval for animal use was obtained from the Samsung Medical Center Laboratory Animals Committee (approval number: 20,200,410,002).
To search for metastasis-associated circRNAs, a previously established cell line model was used: primary colon cancer KM12C cells and its liver metastatic derivative KM12L4 cells (Supplementary Figure S1A) [21]. The high metastatic potential of KM12L4 cells was verified by comparing their invasive and migratory abilities with those of parental KM12C cells. Transwell invasion and migration assays revealed that KM12L4 cells showed a higher number of invaded and migrated cells compared to KM12C cells, indicating that KM12L4 cells have a higher metastatic potential than KM12C cells (Fig. 1 A). To examine the degree of liver metastasis in vivo, KM12C and KM12L4 cells were injected into the spleen and the degree of liver metastasis was determined by visual counting and MRI. As expected, more liver metastases were found in mice injected with KM12L4 cells than in those injected with KM12C cells (Fig. 1B; Supplementary Figure S1B). A circRNA microarray was conducted to identify differentially expressed circRNAs between KM12C and KM12L4 cells. Twenty-nine circRNAs were differentially expressed more than two-fold. Nine circRNAs showed decreased expression in KM12L4 cells compared to KM12C cells. In contrast, the expression of 20 circRNAs was increased (Supplementary Figure S2A, B). Among them, hsa_circRNA_100873 (hsa_circ_0003429) showed the most significant decrease in expression. hsa_circRNA_100873 is an exonic circRNA generated from five exons (exons 17–21) of PTPRF interacting protein alpha 1 (PPFIA1) (Fig. 1E). Interestingly, another PPFIA1-originated circRNA, hsa_circRNA_100872 (hsa_circ_0000337), was found in the list of differentially expressed circRNA (Fig. 1C,D). The spliced length of hsa_circRNA_100872 generated from three exons (exons 17–19, 419 bp) is shorter than that of hsa_circRNA_100873 (702 bp). Hence, we named them circPPFIA1-L (long) and circPPFIA1-S (short), respectively (Fig. 1E; Supplementary Figure S2B). According to the circBase database (www.circbase.org), 37 circRNAs are possibly generated from PPFIA1 (Supplementary Figure S3). However, there are very few circRNAs generated from PPFIA1 whose action mechanisms and roles have been identified. To validate the microarray data, the expression levels of circPPFIA1-L and -S were determined by RT-qPCR and semi-qPCR (Supplementary Figure S4A,C). RT-qPCR analyses using specific primers recognizing their divergent region showed a considerable decrease in both circPPFIA1-L and -S in KM12L4 cells (Fig. 1F; Supplementary Figure S4B). However, linear PPFIA1 mRNA levels were almost same. Similarly, semi-qPCR analyses revealed that KM12L4 expressed less of both circRNAs compared to KM12C cells without a significant change in linear mRNA levels (Fig. 1G). Similar to the results in the model cell lines, the expression of circPPFIA1 in the tissues of colon cancer patients showed a decrease compared to normal tissues, although significant results were not obtained due to the small sample size (Supplementary Figure S5). In addition, we also checked the expression levels of circPPFIA1-L and -S in primary colon cancer tissues and matched liver metastatic colon cancer tissues by RT-qPCR (Fig. 1H) and semi-PCR (Fig. 1I). Both PCR analyses showed a significant decrease in circPPFIA1-L and -S in liver metastatic tissues.
The stability of circPPFIA1s was assessed by semi-qPCR or RT-qPCR after RNase R and actinomycin D treatment. Whereas RNase R degraded linear PPFIA1 mRNA, circPPFIA1-L and -S were highly resistant to RNase R (Fig. 2A). Additionally, linear PPFIA1 mRNA was almost degraded at 24 h post-treatment with actinomycin D. However, neither circPPFIA1s was degraded (Fig. 2B; Supplementary Figure S6A). These results indicate that circPPFIA1-L and -S are highly stable, which is a typical property of circRNAs. To verify the junction sequence of circPPFIA1-L and -S, genomic DNA (gDNA) and cDNA were used for the PCR analysis with convergent and divergent primers. Whereas PCR products of the convergent primers were observed for gDNA and cDNA templates, the divergent primers generated PCR products only from cDNA (Fig. 2 C for circPPFIA1-L, 2E for circPPFIA1-S). In cDNA and gDNA, GAPDH was amplified only by the convergent primer (Supplementary Figure S6B). The back-spliced junction was amplified and verified by Sanger sequencing (Supplementary Figure S4D). We observed head-to-tail splicing between exons 17 and 21 in circPPFIA1-L and exons 17 and 19 in circPPFIA1-S, indicating that they have a circularized structure (Fig. 2D, F; Supplementary Figure S6C). To assess the localization of circRNA, a cellular fractionation assay was conducted. The level of α-tubulin and lamin B was determined to verify appropriate fractionation. Both circPPFIA1-L and -S were abundantly expressed in the cytosol (Fig. 2G), which suggests that circPPFIA1s could function as molecular sponges of miRNA or RBP.
To investigate whether the knockdown of circPPFIA1-L and -S regulated the metastatic potential of KM12C cells, we designed siRNAs targeting the divergent junctions of circPPFIA1-L and -S (Supplementary Figure S7A for circPPFIA1-L and S7C for circPPFIA1-S). All designed siRNAs showed an efficient decrease in corresponding circRNAs, but barely influenced the expression of linear PPFIA1 (Fig. 3 A, C; Supplementary Figure S7B and D). An increase in invasive and migratory abilities was observed in circPPFIA1-L- and circPPFIA1-S-silenced KM12C cells (Fig. 3B and D). The increased metastatic potential was observed with each siRNA. However, the knockdown of PPFIA1 mRNA did not influence the metastatic potential of KM12C cells (Supplementary Figure S8A,B). To exclude the possibility that the increased number of invaded and migrated cells observed after circPPFIA1s knockdown is attributed to increased cell growth, we examined the proliferation rate of circPPFIA1s-silenced KM12C cells. Neither circPPFIA1-L nor circPFIA1-S affected cell growth (Supplementary Figure S8C), demonstrating that circPPFIA1s inhibit the metastatic potential of KM12C cells without affecting cell growth. Notably, metastatic properties, including invasion and migration, were further increased when both circPPFIA1-L and -S were simultaneously silenced (Fig. 3E, F; Supplementary Figure S7E). To investigate whether knockdown of circPPFIA1-L and -S increased the liver metastasis of CRC in vivo, a splenic injection mouse model was used. An approximate four-fold increase in liver metastasis was observed in the mice injected with circPPFIA1-L-silenced KM12C cells (Fig. 3G; Supplementary Figure S9A, B). The intrasplenic injection of circPPFIA1-S-silenced KM12C cells showed a more than four-fold increase in liver metastasis (Fig. 3 H; Supplementary Figure S9C, D). Based on these results, we confirmed that the knockdown of both circPPFIA1-L and -S potentiates metastatic potential and enhances the liver metastasis of CRC. To examine whether the circPPFIA1s suppressed the metastatic potential of KM12L4 cells, we constructed overexpression vectors expressing each circRNA. Both vectors induced a significant increase in circPPFIA1-L and -S without any change in the linear PPFIA1 mRNA (Fig. 4 A, C). Increased expression of the circPPFIA1s resulted in the inhibition of the invasive and migratory properties of KM12L4 cells (Fig. 4B and D). Overexpression of circPPFIA1-L dose-dependently suppressed the invasive ability (Supplementary Figure S10A), and similar results were obtained in all overexpressing cells (Supplementary Figure S10B–D). We also confirmed that the reduction in metastatic abilities did not result from the inhibition of cell growth (Supplementary Figure S10E). The intrasplenic injection experiments revealed that KM12L4 cells with high levels of circPPFIA1s showed a decrease in liver metastasis (Fig. 4E). The incidence of liver metastasis and the number of nodules were decreased in mice injected with circPPFIA1-overexpressing KM12L4 cells (Supplementary Figure S11). To confirm that the inhibitory effects of circPPFIA1s on metastatic properties can be applied to other colon cancer cells, DLD1 and RKO colon cancer cells were used. Similar to the results in KM12C cells, the knockdown of circPPFIA1-L or -S caused an increase in metastatic abilities (Supplementary Figure S12A,B). Conversely, the increased expression of either circPPFIA1-L or -S diminished the number of invaded and migrated cells (Supplementary Figure S12 C, D). Thus, we demonstrate that circPPFIA1-L and -S negatively regulates liver metastasis in CRC.
Increasing evidence suggests that circRNAs act as miRNA sponges, thereby interrupting the inhibitory functions of miRNA. The cellular fractionation assays revealed that circPPFIA1-L and -S were abundantly located in the cytosol (Fig. 2G), suggesting that they might function as competing endogenous RNAs (ceRNAs). Four bioinformatic prediction algorithms (ArrayStar, https://www.arraystar.com; circInteractome, https://circinteractome.nia.nih.gov; Starbase, http://starbase.sysu.edu.cn; and RNA22, https://cm.jefferson.edu/rna22) were used to search for circPPFIA1-interacting miRNAs. The only common prediction in all algorithms was miR-155-5p (Fig. 5 A; Supplementary Figure S13). To verify that miR-155-5p interacts with circPPFIA1, an ASO pulldown experiment was performed. First, we designed ASOs targeting the divergent sequences of circPPFIA1-L or -S. All designed ASOs for circPPFIA1-L and -S worked efficiently and miR-155-5p bound to circPPFIA1s (Supplementary Figure S14A, B). Repeated ASO pulldown experiments were conducted by the mixture of corresponding ASOs, and the level of miR-155-5p in pulldown materials was determined by RT-qPCR. To confirm the interaction between cirPPFIA1s and miR-155-5p, an Argonaute 2 immunoprecipitation (Ago2 IP) experiment was performed. The introduction of pre-miR-155-5p into KM12C cells increased the enrichment of circPPFIA1-L and -S in Ago2 IP material compared to the control IgG (Fig. 5 C). Interestingly, the RT-qPCR results indicated that circPPFIA1-S was more enriched than circPPFIA1-L, assumingly due to the higher cytosolic levels of circPPFIA1-S. In addition, the direct interaction between circRNAs and miR-155-5p was examined by a luciferase assay. Two miR-155-5p MREs were found in exon 18, which is present in both circRNAs (details in Supplementary Figure S15A), and therefore, we constructed two luciferase vectors containing the wild-type or mutated sequence of miR-155-5p MRE (Supplementary Figure S15B). Luciferase activity was inhibited by overexpression of miR-155-5p in both vectors containing wild-type MRE. However, the luciferase expression was not affected in the case of mutated vectors (Fig. 5D). Although we confirmed that circPPFIA1s and miR-155-5p were bound, the knockdown of circPPFIA1-L, -S, or both did not affect the level of miR-155-5p (Fig. 5E). Overexpression of miR-155-5p by introducing pre-miRNA into KM12C cells did not influence the expression of circPPFIA1s (Fig. 5F). Similarly, the downregulation of miR-155-5p by anti-miRNA in KM12L4 cells did not result in the reduction of circPPFIA1s (Fig. 5F). These results indicate that the circPPFIA1s and miR-155-5p did not affect each other’s expression. The effect of changes in ceRNA on the level of sponging miRNAs has not been fully elucidated. Due to their structural characteristics, circRNAs are not thought to be affected by their sponging miRNAs. Next, we examined the regulation of metastatic potential by miR-155-5p. The overexpression of miR-155-5p in KM12C cells caused an increase in the number of invaded and migrated cells compared to the control miRNA (Fig. 5G). In contrast, the inhibition of miR-155-5p suppressed the metastatic potential of KM12L4 cells (Fig. 5 H). The regulatory effect of miR-155-5p was confirmed in DLD1 and RKO cells. As observed in KM12C and KM12L4 cells, the metastatic potential was increased depending on the expression level of miR-155-5p (Supplementary Figure S16A for DLD1 and S16A for RKO). To verify the role of miR-155-5p in circPPFIA1s-mediated regulation of metastatic potential, a rescue experiment was conducted using a mixture of siRNAs targeting circPPFIA1-L and -S. As expected, the metastatic potential of KM12C cells was potentiated by the knockdown of circPPFIA1s. However, the inhibition of miR-155-5p reversed the increase in the invasive and migratory abilities of KM12C cells, indicating that an increase in liberated miR-155-5p is responsible for the function of circPPFIA1s (Fig. 5I). Rescue experiments using each circPPFIA1-L and -S siRNA also showed similar results (Supplementary Figure S17).
By screening targets of circPPFIA1/miR-155-5p using prediction algorithms, six genes were identified (Supplementary Figure S18). CDX1, a tumor-suppressor, was selected by RT-qPCR validation and reference search for further studies (Fig. 6A). Western blot and RT-qPCR assays revealed that CDX1 was highly expressed in KM12C cells compared to KM12L4 cells (Fig. 6B). Similarly, the expression level of CDX1 in liver metastatic colon cancer tissues was lower than that in primary colon cancer tissues (Fig. 6C). The effect of miR-155-5p on the expression of CDX1 was tested using pre- and anti-miR-155-5p in KM12C and KM12L4 cells, respectively. The overexpression of miR-155-5p decreased CDX1 protein and mRNA expression levels in KM12C cells. Conversely, CDX1 was upregulated by decreasing miR-155-5p in KM12L4 cells (Fig. 6D). Direct interaction between CDX1 mRNA and miR-155-5p was assessed by Ago2 RIP and luciferase experiments. The enrichment of CDX1 mRNA in Ago2 IP material was enhanced by the overexpression of miR-155-5p and was lowered by the inhibition of miR-155-5p compared to the control (Fig. 6E). One MRE of miR-155-5p in the sequence of the 3’UTR of CDX1 mRNA was found (Supplementary Figure S19). To confirm the binding of miR-155-5p to CDX1 mRNA, luciferase vectors containing the wild-type or mutated sequence of the miR-155-5p binding site were manufactured. The overexpression of miR-155-5p significantly decreased luciferase activity; in contrast, the mutation of the binding sequence blocked the miR-155-5p-mediated inhibition of luciferase activity (Fig. 6 F). We found that circPPFIA1s associated with miR-155-5p and mitigated its inhibitory function. Therefore, we tested whether circPPFIA1s regulated CDX1 expression. The knockdown of circPPFIA1-L or -S decreased the expression level of CDX1 protein and mRNA in KM12C cells (Fig. 6G). Ago2 RIP and luciferase experiments were carried out to verify that miR-155-5p was required for the regulation of CDX1 by circPPFIA1s. The knockdown of circPPFIA1-L and -S increased the enrichment of CDX1 mRNA in Ago2 IP materials (Fig. 6 H) resulting from an increase in liberated miR-155-5p via a decrease in the level of circPPFIA1 as a ceRNA (Fig. 6 H). Increased levels of functional miR-155-5p due to the knockdown of circPPFIA1-L and -S also lowered luciferase expression in the wild-type but not in the mutant vector (Fig. 6I). These results indicate that the inhibitory effect of miR-155-5p on CDX1 expression is enforced by the knockdown of circPPFIA1s. We also tested whether the overexpression of circPPFIA1s can upregulate CDX1 expression. The expression levels of CDX1 protein and mRNA were increased by the overexpression of circPPFIA1s (Fig. 6J), and as expected, the enrichment of CDX1 mRNA in Ago2 IP was lowered in circPPFIA1-overexpressing cells (Fig. 6 K). The above results indicated that the inhibition of miR-155-5p by anti-miR reversed the increased metastatic potential due to the knockdown of circPPFIA1s (Fig. 5I). Accordingly, we assessed the expression level of CDX1 in the same samples. Decreased CDX1 expression due to the knockdown of circPPFIA1s was restored by introducing anti-miR-155-5p into KM12C cells (Fig. 6L). To examine whether CDX1 is associated with metastatic potential, the invasive and migratory abilities of CDX1-silenced KM12C cells were assessed. We found that siRNA that targets CDX1 mRNA efficiently decreased the expression of CDX1 (Fig. 6 M). Transwell assays revealed that the knockdown of CDX1 enhanced invasive and migratory abilities (Fig. 6 N). These results indicate that liberated miR-155-5p by the knockdown of circPPFIA1s suppressed CDX1 by directly binding to its mRNA.
By predicting circPPFIA1s-associated RBPs using three algorithms (circInteractome, RBPDB, and StarBase), HuR was identified as a putative sponging RBP of circPPFIA1s (Fig. 7 A; Supplementary Figure S20A). Moreover, the association of HuR with circPPFIA1s was confirmed by a computational prediction (RBPmap, http://rbpmap.technion.ac.il). To verify the direct interaction between circPPFIA1s and predicted RBPs, ASO pulldown was followed by western blot analysis (Supplementary Figure S20B). Among them, we observed that HuR was significantly bound to both circPPFIA1-L and -S, whereas another RBPs showed weakly or barely bound to circPPFIA1s (Fig. 7B; Supplementary Figure S20C). In addition, the association of HuR with circPPFIA1s was examined by HuR RIP experiments. Semi-qPCR results showed that circPPFIA1s were more enriched in HuR IP than in IgG IP. These results indicate that HuR, as a sponging RBP of circPPFIA1s, is closely implicated in the anti-metastatic function of circPPFIA1s. Next, the expression of HuR was compared in KM12C and KM12L4 cells. Interestingly, the western blot results revealed that the expression level of HuR in both cells was almost similar (Fig. 7D). Moreover, the cellular localization of HuR did not differ between cells (Fig. 7E). We investigated the effect of the circPPFIA1s on HuR expression and vice versa. When circPPFIA1-L and -S were silenced in KM12C cells, the expression level and cellular localization of HuR were unchanged (Fig. 7 F,G). Moreover, the knockdown of HuR by two independent siRNAs did not cause notably altered expression levels of circPPFIA1-L and -S in KM12L4 cells (Fig. 7H). Based on these results, we assumed that circPPFIA1s may affect the regulatory functions of HuR, such as stabilization or translational activation of its target mRNA, without any change in the expression and localization of HuR. To test whether HuR can regulate metastatic potential, the invasive and migratory abilities of KM12L4 cells were examined by transwell assays. The knockdown of HuR dramatically decreased the number of invaded and migrated cells (Fig. 7I). We also determined whether HuR is required for the increased metastatic potential of KM12C cells by lowering the expression of circPPFIA1s. Increased metastatic potential by the knockdown of circPPFIA1s was reversed through HuR silencing (Fig. 7J). This indicated that HuR is required for the increase in metastatic ability due to the knockdown of circPPFIA1s. As expected, when the expression level of HuR was lowered, the metastatic potential was decreased, and when circPPFIA1s were silenced, KM12C cells showed high metastatic potential. However, the knockdown of both HuR and circPPFIA1s decreased the invaded and migrated cell number compared to those of circPPFIA1-silenced cells.
By comparing and analyzing the HuR CLIP-sequencing results with the list of genes upregulated under the three described conditions, 48 out of 62 genes (approximately 77% of the total merged genes) were found to be putative HuR target genes (Supplementary Figure S21). Among these genes, RAB36 was selected as a HuR target gene using the reference investigation (Fig. 8A). To verify that RAB36 is a HuR target, an HuR RIP experiment was conducted. The level of RAB36 mRNA was more enriched in HuR IP compared to IgG IP (Fig. 8B). Western blot and RT-qPCR analyses indicated that the expression levels of RAB36 protein and mRNA were higher in KM12L4 cells (Fig. 8C). Similar to what was observed in cells, RAB36 was highly expressed in liver metastatic colon cancer tissues compared to primary colon cancer tissues (Fig. 8D). Moreover, the knockdown of HuR by two independent siRNAs downregulated RAB36 protein and mRNA, indicating that RAB36 is a novel target of HuR (Fig. 8E). As an oncogene, the main mechanism of HuR is the stabilization of target mRNA by directly binding to its 3’UTR, which results in the upregulation of the target gene. Therefore, we determined whether HuR increased the stability of RAB36 mRNA. The decreased expression of RAB36 by knockdown of HuR was confirmed using the mixture of HuR siRNAs (Fig. 8F). The knockdown of HuR induced a more rapid decrease in RAB36 mRNA compared to that in the control (Fig. 8F). The estimated half-lives of RAB36 mRNA in the control and HuR-silenced KM12L4 cells were 5.4 h and 3.1 h, respectively. Next, we investigated the functional role of circPPFIA1s in HuR-mediated RAB36 regulation. The knockdown of circPPFIA1-L and -S increased the expression level of RAB36 protein and mRNA (Fig. 8G). The HuR RIP experiment indicated that the knockdown of circPPFIA1s enhanced the interaction between HuR and RAB36 mRNA, which allowed HuR to stabilize RAB36 mRNA (Fig. 8H). Although the estimated half-lives of RAB36 mRNA in the control was approximately 3.1 h, it increased to 5.8 h and 5.6 due to the knockdown of circPPFIA1-L and -S, respectively (Fig. 8I). Conversely, the overexpression of circPPFIA1-L and -S induced a decrease in RAB36 protein and mRNA (Fig. 8J) and lowered the enrichment of RAB36 mRNA in HuR IP materials (Fig. 8K). We assessed the expression level of RAB36 in the same samples, because RAB36 was identified as a HuR target. Increased level of RAB36 by the knockdown of circPPFIA1s was lowered by HuR silencing (Fig. 8L). This indicates that the liberation of HuR by decreasing the levels of circPPFIA1s is required for highly metastatic phenotypes. We also tested whether RAB36 is involved in the invasive and migratory abilities of KM12L4 cells. Introducing a siRNA that targets RAB36 mRNA efficiently decreased the expression of RAB36 protein and mRNA in KM12L4 cells (Fig. 8M). The metastatic potential was also diminished by the knockdown of RAB36 (Fig. 8N). Our findings are summarized by a schematic illustration in Fig. 9. Briefly, two circPPFIA1s, generated from the exons of the PPFIA1 gene, are downregulated in the liver metastasis of CRC. They are mainly present in the cytosol, which allows them to function as molecular sponges. As tumor suppressors, circPPFIA1-L and -S negatively control the metastatic potential of CRC via two pathways: as a sponge of miR-155-5p, upregulating CDX1 expression; and as a sponge of HuR, downregulating RAB36 expression.
Emerging evidences indicate that circRNAs are closely associated with various diseases, especially with cancers. Their unique nature and specificity made them a new hotspot in the field of biomedical research in recent years. In this study, we identified two circRNAs, circPPFIA1-L and -S, downregulated in liver metastatic KM12L4 cells compared to primary KM12C cells through circRNA microarray. Functionally, circPPFIA1s carry anti-metastatic roles in CRC by sponging oncogenic miR-155-5p and HuR. Thus, our finding suggests that two circPPFIA1s may be used for potential clinical diagnosis of CRC. CircRNAs play a critical role in the progression of CRC. According to the circRNA profile of CRC, approximately 75–80% of differentially expressed circRNAs (DECs) are derived from exons [22, 23]. Most exon-containing circRNAs are predominantly located in the cytosol, generally functioning as molecular sponges [24]. Tumor-suppressive circRNAs (for example circ_001988, circ_0009361, and circ_0021977), like other tumor suppressors, are downregulated in CRC, which enhances the inhibitory effect of oncogenic miRNAs and accordingly suppresses the tumor-suppressing target genes [25–27]. Here, we found that two circPPFIA1s (circPPFIA1-L and -S), generated from the exons of PPFIA1, are downregulated in liver metastatic colon cancer cells and tissues. Liprin-α1, encoded by PPFIA1, interacts with the leukocyte common antigen-related family of tyrosine phosphatases and plays an important role in axon guidance and mammary gland development [28]. In addition to its function in neuronal cells, liprin-α1 is associated with the proliferation, migration, and invasion of cancer cells [29, 30]. According to the circBase database (www.circbase.org), 37 circRNAs are generated from PPFIA1 (Supplementary Figure S3). Here, we identified two anti-metastatic circRNAs generated from PPFIA1. There are several reports on the function of PPFIA1-generated circRNAs in cancer. CircPPFIA1 enhances the metastatic potential of laryngeal squamous cell carcinoma via miR-340-3p/ELK1 [31]. Despite shared nomenclature, they are different circRNAs. CircPPFIA1 is circ_0023326, but the circPPFIA1-L and -S reported here are circ_0003426 and circ_0000337, respectively. circPPFIA1-L and -S, previously reported under the names circRNA_100873 [32] and circ_0000337 [33], are associated with the lymphatic metastasis of esophageal squamous cell carcinoma. However, its detailed action mechanism is not fully understood in CRC. Accumulating evidences shown that circRNAs exerted diverse biological functions by serving as sponges for miRNAs. As competing endogenous RNA (ceRNA), circRNAs regulate miRNA function by inhibiting binding of miRNAs to 3’UTR of their targets. For example, circHIPK3 promotes CRC progression and metastasis by sponging miR-7 [34]. CircSAPRC enhances metastatic potential of CRC through miR-485-3p/JAK2 [35]. Herein, we found that circPPFIA1s inhibit CRC metastasis by mitigating the inhibitory function of miR-155-5p. MiR-155-5p, a well-known oncogenic miRNA, promotes oral cancer progression by suppressing the chromatin remodeling gene ARID2 [36]. Additionally, miR-155-5p is associated with the anti-tumor effect of cetuximab, cisplatin, and 5-FU in breast cancer, hepatocellular carcinoma cells (HCCs), and CRC, respectively [37–39]. In our study, based on analysis of RNA-seq data and bioinformatic tools, CDX1 is identified as a target of circPPFIA1s/miR-155-5p. CDX-1, an intestine-specific gene, is generally downregulated in CRC [40, 41] and acts as a tumor-suppressor by hindering the transcriptional activity of β-catenin/T-cell factor [42]. CDX1 induction also alters the transcript expression of genes related to cell adhesions for EMT and angiogenesis [40]. As miR-155-5p sponge, circPPFIA1s increase the expression of CDX1 by blocking the interaction of mIR-155-5p with CDX1 mRNA, resulting in lowered metastatic potential of CRC. There has been controversy over whether circRNA can regulate the expression of miRNA. However, emerging evidences have revealed that circRNA as a ceRNA could not affect the level of miRNA since they do not degrade their sponging miRNA. CircTLK1 did not influence the expression level of miR-136-5p but inhibited its inhibitory effect on CBX4 expression as a miRNA sponge [43]. Moreover, a well-known circRNA, CDR1as which contains 63 conserved MREs for miR-7 suppressed its activity without affecting the expression of miR-7 [44]. CircFOXK2 was found to hinder the function of miR-942 without the alteration of its expression level [45]. The circular RNA circRIP2 was also reported to regulate the suppressing effect of miR-1305 but not its expression [46]. Our data demonstrate that circPPFIA1s act as tumor suppressors by sponging the oncogenic miR-155-5p. In addition to miRNA sponge, circRNAs also affect the function of RBP as a RBP sponge. For example, circPTPRA suppresses bladder cancer progression by blocking the interaction between IGF2BP1 and its target mRNAs [47]. For exploring the additional function of circPPFIA1s on RBP, we searched for circPPFIA1s-associated RBP with the bioinformatic tools and found that ELAV-like protein HuR is a binding partner of circPPFIA1s. HuR is closely related to malignant phenotypes of CRC mainly through the stabilization of its target mRNA [48]. Our findings demonstrated that increased metastatic potential by knockdown of circPPFIA1s was attenuated through HuR silencing, thus hypothesizing that circPPFIA1s is responsible for blocking oncogenic effects of HuR in CRC. Several tumor-suppressing circRNAs function as HuR sponges. CircRHOBTB3 suppresses CRC metastasis by hindering the HuR-mediated stabilization of polypyrimidine tract-binding protein 1 (PTBP1) mRNA [49]. CircDLC1, a prognostic marker of hepatocellular carcinoma (HCC), inhibits the motility of HCC by sequestering HuR from matrix metalloproteinase-1 (MMP1) mRNA [50]. By a similar action mechanism, circPPFIA1s can influence HuR targets by sponging it. We found that RAB36 is the downstream effector molecule of circPPFIA1s. RAB36, a member RAS oncogene family, is upregulated in various types of cancers and may be closely related with tumor development and metastasis. In bladder cancer, it promotes cancer progression and invasion [51]. Accordingly, RAB36 is a target of circPPFIA1s/HuR.
We searched for metastasis-associated circRNAs using KM12C CRC cells and its liver metastatic derivative KM12L4. Using a circRNA microarray, we identified several circRNAs downregulated in KM12L4 cells compared to KM12C cells. Two circPPFIA1s, generated from PPFIA1, were significantly downregulated in liver metastatic cells. The circular structure of circPPFIA1s was verified by RNase R resistance and Sanger sequencing. Using in vitro transwell assays and in vivo intrasplenic injection mouse experiments, we found that circPPFIA1s negatively regulated the liver metastasis of CRC. Mechanistically, an ASO pulldown assay revealed that both circPPFIA1-L and -S function as sponges for oncogenic miR-155-5p and HuR. circPPFIA1s upregulate tumor-suppressing CDX1 by decoying CDX1-targeting miR-155-5p and downregulate oncogenic RAB36 by sequestering HuR. Taken together, circPPFIA1s, as a metastasis suppressor, are a promising therapeutic target for the treatment of the liver metastasis of CRC.
Additional file 1: Supplementary Table S1. Verification of cell lines used in this study by STR analysis. Supplementary Table S2. PCR primers and siRNAs used in this study. Supplementary Table S3. List of antibodies used in this study. Supplementary Table S4. Composition of buffers used in this study. Supplementary methods. Supplementary Figure S1. Comparison of metastatic potential of primary (KM12C) and liver metastatic colorectal cancer cells (KM12L4). A Schematic illustration of the establishment of the liver metastatic colorectal cancer cell model. KM12C was originally obtained from a human specimen and KM12L4 was generated through the fourth selection-isolation of intrasplenic injection. B Liver metastases were examined using in vivo intra-splenic injection. At four weeks post-injection, optical and MRI images were obtained. The degree of liver metastasis (n = 5) was calculated by giving scores in arbitrary units (0–3). Supplementary Figure S2. Analyses of circRNA microarray data. A A heat map analysis of circRNA microarray. B A volcano plot of circRNA microarray data showing a list of the upregulated and downregulated circRNAs. C Detailed information on circPPFIA1-L and -S. Supplementary Figure S3. List of PPFIA1-originated circRNAs. circRNAs that are generated from the PPFIA1 gene are listed in a public circRNA database (circBase, http://www.circbase.org). Supplementary Figure S4. Primer sequences used in this study. A Schematic illustration and sequences of RT-qPCR primers detecting circPPFIA1-L, circPPFIA1-S, and linear PPFIA1. B Validation of the expression of circPPFIA1-L and -S by RT-qPCR using the above primer sets. C Schematic illustration and sequences of semi-qPCR primers detecting circPPFIA1-L, circPPFIA1-S, and linear PPFIA1. D Schematic illustration and sequences of primers for Sanger sequencing. Supplementary Figure S5. Comparison of circPPFIA1-L and -S expression between adjacent normal and tumor tissues of CRC patients. Tumor tissues and their matched normal tissues were obtained from 14 CRC patients at the Samsung Medical Center. Among the 14 patients, seven did not exhibit metastasis while the other seven patients showed liver metastasis. All samples were collected with the informed consent of patients under institutional review board-approved protocols and stored at -80°C until use. The expression level of circPPFIA1-L and -S was determined by RT-qPCR (n = 38 for circPPFIA1-L, n = 28 for circPPFIA1-S). Supplementary Figure S6. Characterization of circPPFIA1-L and -S. A The stability of circPPFIA1s and linear PPFIA1 was examined by RT-qPCR using total RNA isolated from actinomycin D-treated KM12C cells. B Schematic illustration of divergent and convergent semi-qPCR primers for circPPFIA1-L and -S. Semi-qPCR analysis was conducted using genomic (gDNA) and complementary (cDNA) DNA. GAPDH was used as a negative control. C Sanger sequencing results of circPPFIA1-L and -S. Supplementary Figure S7. Design and validation of siRNAs targeting circPPFIA1-L and -S. (A, C) Schematic illustration and sequences of circPPFIA1-L siRNAs (A), and -S (C). (B, D) Each siRNA efficiently decreases the expression level of circPPFIA1-L (B) and -S (D). (E) For a cotransfection experiment, KM12C cells were simultaneously transfected with siRNAs targeting circPPFIA1-L and -S. The expression levels of circPPFIA1s and GAPDH were determined by semi-qPCR. Supplementary Figure S8. Potentiation of metastatic properties by knockdown of circPPFIA1-L and -S in KM12C cells. (A, B) KM12C cells were transfected with the indicated siRNA (shown in Supplementary Figure S7), and transwell assays were performed to determine invasive (A) and migratory (B) abilities. (C, D) Cell proliferation of KM12C cells transfected with individual or a mixture of siRNAs targeting circPPFIA1-L (C) or -S (D) was determined by counting the number of viable cells. Supplementary Figure S9. Increase in liver metastasis in vivo by knockdown of circPPFIA1s. The effect of circPPFIA1-L and -S on liver metastasis in vivo was examined through intrasplenic injection of KM12C cellstransfected with circPPFIA1s siRNAs. (A, C) The expression level of circPPFIA1-L (A) and -S (C) was determined by semi-qPCR. (B, D) Liver metastases were examined using in vivo intrasplenic injection. At four weeks post-injection, optical and MRI images were obtained. The degree of liver metastasis (n = 7) was calculated by giving scores in arbitrary units (0–3). Supplementary Figure S10. Suppression of metastatic potential by overexpression of circPPFIA1-L and -S in KM12L4 cells. (A-C) By introducing the circPPFIA1-L overexpression vector into KM12L4 cells, three independent clones (#1–#3) were generated and were used to investigate the effect of circPPFIA1-L on metastatic potential. Invasive ability was examined by transwell invasion assays, and the expression levels of circPPFIA1-L and PPFIA1 mRNA were measured by RT-qPCR. (D) In the same way as above, two clones (#1 and #2) in which circPPFIA1-S was overexpressed were generated, and invasive and migratory abilities were determined by transwell invasion and migration assays. (E) The effect of circPPFIA1 overexpression on cell proliferation was examined by counting the number of viable cells. Supplementary Figure S11. Decrease in liver metastasis in vivo by overexpression of circPPFIA1s. The effect of circPPFIA1-L and -S on liver metastasis in vivo was examined via intrasplenic injection of KM12L4 cells, wherein circPPFIA1-L or -S was overexpressed. (A, C) The expression levels of circPPFIA1-L (A) and -S (C) were determined by semi-qPCR. (B, D) Liver metastases were examined via in vivo intrasplenic injection of circPPFIA1-L (B) or -S (D) overexpressing KM12L4 cells. At four weeks post-injection, optical and MRI images were obtained. The degree of liver metastasis (n = 7) was calculated by giving scores in arbitrary units (0–3). Supplementary Figure S12. Negative regulation of invasive and migratory abilities via circPPFIA1-L and -S in DLD1 and RKO cells. (A, B) Following transfection of DLD1 (A) and RKO (B) cells with indicated siRNA, transwell assays were conducted to measure invasive and migratory abilities. The expression levels of circPPFIA1-L, -S, and PPFIA1 mRNA were determined by semi-qPCR. GAPDH was used as a loading control. (C, D) For overexpression of circPPFIA1-L and -S, DLD1 (C) and RKO (D) cells were transfected with indicated vector. The number of invaded and migrated cells was assessed using transwell assays. The expression levels of circPPFIA1-L, -S, and PPFIA1 mRNA were determined by semi-qPCR. GAPDH was used as a loading control. Supplementary Figure S13. Venn diagram for selecting putative interacting miRNAs with circPPFIA1. By prediction of circPPFIA1-interacting miRNAs using four prediction algorithms (ArrayStar, RNA22, circInteractome, and Starbase), miR-155-5p was selected for further studies. Supplementary Figure S14. Schematic illustration and design of antisense oligonucleotide (ASO) for the pulldown experiments. (A, B) ASOs for pulldown were designed to bind to the divergent region of circPPFIA1-L (A) or -S (B). circPPFIA1-L and -S were captured using three and two ASOs, respectively. The enrichment of the corresponding circRNA in pulldown materials was assessed by semi-qPCR. (C) The sequences of ASOs for pulldown experiments. LacZ was used as a control ASO. Supplementary Figure S15. Construction of luciferase vectors harboring wild-type (WT) or mutant (MT) sequences of miR-155-5p miRNA recognition element (MRE) in circPPFIA1-L and -S. (A) Two miR-155-5p MREs (#1 and #2) were predicted by bioinformatics approaches in the sequence of exon 18 of PPFIA1. (B) Dual-luciferase vectors harboring wild-type (WT) or mutant (MT) sequences of each miR-155-5p MRE were manufactured. Supplementary Figure S16. Regulation of metastatic potential by miR-155-5p in DLD1 and RKO cells. DLD1 (A) and RKO (B) cells were transfected with pre-miR-155-5p or anti-miR-155-5p. Invasive and migratory abilities were assessed using transwell invasion and migration assays. Supplementary Figure S17. Rescue experiment for proving that miR-155-5p is required for the increase in metastatic potential by knockdown of circPPFIA1. KM12C cells were simultaneously transfected with circPPFIA1 siRNA and anti-miR-155-5p. Invasive and migratory abilities were examined using transwell invasion (A) and migration (B) assays. Supplementary Figure S18. Venn diagram for screening common target genes that are regulated via circPPIFIA1s/miR-155-5p. By comparing the lists of downregulated genes obtained from RNA sequencing data, and miR-155-5p target genes predicted by miRDB and TargetScan, six genes (ETS1, CDX1, TCF4, TP53INP1, MAFB, and BDNF) were identified as putative targets. Supplementary Figure S19. Schematic of dual-luciferase reporter vectors harboring wild-type or mutant sequences of miR-155-5p MRE in CDX1 mRNA. Supplementary Figure S20. Prediction and validation of circPPFIA1-interacting RNA-binding proteins. (A) Venn diagram for selecting circPPFIA1-interacting RBPs using three prediction algorithms (circInteractome, Starbase, and RBPDB). (B) The levels of predicted RBPS in ASO pulldown materials were assessed by western blot analyses using the indicated antibodies. (C) ASO pulldown followed by western blot analysis was conducted to verify the interaction of HuR with circPPFIA1s (left, circPPFIA1-L; right, circPPFIA1-S). Supplementary Figure S21. High proportion of common target genes harbor the HuR-binding motif.Upregulated common target genes were screened based on the following three criteria: (i) genes upregulated genes by knockdown of circPPFIA1-L, (ii) genes upregulated genes by knockdown of circPPFIA1-S, (iii) genes upregulated in KM12L4 compared to KM12C. By comparing and analyzing the public data of HuR CLIP-seq with the selected common target genes, we observed that 77% (48 genes out of 62 genes) of selected target genes have HuR-binding motifs in their 3’-UTRs. | true | true | true |
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PMC9555214 | Xun Zhang,Mingpeng Luo,Jiahang Zhang,Bize Guo,Shreya Singh,Xixi Lin,Hanchu Xiong,Siwei Ju,Linbo Wang,Yulu Zhou,Jichun Zhou | The role of lncRNA H19 in tumorigenesis and drug resistance of human Cancers 10.3389/fgene.2022.1005522 | 27-09-2022 | lncRNA H19,drug resistance,tumorigenesis,miRNA,chemotherapy,endocrine therapy,targeted therapy | Systemic therapy is one of the most significant cancer treatments. However, drug resistance often appears and has become the primary cause of cancer therapy failure. Regulation of drug target, drug metabolism and drug efflux, cell death escape (apoptosis, autophagy, et al.), epigenetic changes, and many other variables are complicatedly involved in the mechanisms of drug resistance. In various types of cancers, long non-coding RNA H19 (lncRNA H19) has been shown to play critical roles in tumor development, proliferation, metastasis, and multiple drug resistance as well. The efficacy of chemotherapy, endocrine therapy, and targeted therapy are all influenced by the expression of H19, especially in breast cancer, liver cancer, lung cancer and colorectal cancer. Here, we summarize the relationship between lncRNA H19 and tumorigenesis, and illustrate the drug resistance mechanisms caused by lncRNA H19 as well. This review may provide more therapeutic potential targets for future cancer treatments. | The role of lncRNA H19 in tumorigenesis and drug resistance of human Cancers 10.3389/fgene.2022.1005522
Systemic therapy is one of the most significant cancer treatments. However, drug resistance often appears and has become the primary cause of cancer therapy failure. Regulation of drug target, drug metabolism and drug efflux, cell death escape (apoptosis, autophagy, et al.), epigenetic changes, and many other variables are complicatedly involved in the mechanisms of drug resistance. In various types of cancers, long non-coding RNA H19 (lncRNA H19) has been shown to play critical roles in tumor development, proliferation, metastasis, and multiple drug resistance as well. The efficacy of chemotherapy, endocrine therapy, and targeted therapy are all influenced by the expression of H19, especially in breast cancer, liver cancer, lung cancer and colorectal cancer. Here, we summarize the relationship between lncRNA H19 and tumorigenesis, and illustrate the drug resistance mechanisms caused by lncRNA H19 as well. This review may provide more therapeutic potential targets for future cancer treatments.
Cancer is a global public health epidemic and is predicted to be the leading cause of death in 2018 according to the World Health Organization (WHO). As a result, research on cancer treatment has gained growing attention (World Health Organization, 2018). Systemic therapy is an important way of treating cancer, among many treatment interventions. However, drug resistance has become a major problem in current cancer recurrence and clinical treatment failure (Holohan et al., 2013), (Chen et al., 2017a). Two forms of drug resistance (intrinsic and acquired) can significantly influence the efficacy of systemic therapy. Intrinsic resistance means that the resistance-mediating factors pre-exist in the bulk of tumor cells before systemic therapy is received (Longley and Johnston, 2005). Acquired drug resistance can be caused by mutations and other adaptive responses, such as the increased expression of therapeutic targets and the activation of alternative compensatory signaling pathways during treatment (Longley and Johnston, 2005). As tumors are increasingly recognized to be highly heterogeneous, drug resistance can occur through therapy-induced selection of a small subpopulation of resistant cells in the original tumor, and tumor cells can acquire cross-resistance to a wide variety of drugs (Kartal-Yandim et al., 2016). Long noncoding RNAs (LncRNAs) are defined as a class of non-coding RNAs which consist of more than 200 nucleotides (Huarte, 2015). They do not encode any proteins but can be transcribed by RNA polymerase II like mRNAs (Mirzaei et al., 2021). As research deepen, more evidence has revealed the various functions of lncRNAs at chromatin, transcriptional and post-transcriptional levels (Mirzaei et al., 2022). According to the locations where lncRNAs function, they can be divided into nuclear lncRNAs and cytoplasmic lncRNAs. The nuclear lncRNAs participate in chromatin remodeling and modification, chromosomal looping, transcriptional modulation, and RNA processing; while cytoplasmic lncRNAs usually interact with mature mRNA and/or protein (Wang et al., 2017a). Based on the mechanisms above, lncRNAs have been identified to participate in a series of cellular processes including cell growth, proliferation, apoptosis, invasion, metastasis, and the regulation of gene expression, etc., Therefore, disturbances or impairment in lncRNA expression leads to emergence of pathological events, especially cancer (Ashrafizaveh et al., 2021). In different types of cancer cells, more and more lncRNAs like lncRNA H19 (here after, referred as H19), have been verified to engage in tumor development and drug resistance of systemic therapy (Qu et al., 2015). In this review, we focus on the relation between H19 and tumorigenesis. Then we identify the drug resistant roles played by H19 in various cancers, such as breast cancers, hepatocellular carcinoma, bladder cancers, lung cancers, etc., Meanwhile, the possible association between H19 and various types of drugs is summarized. Finally, we address the functions performed by H19 in different forms of cell death and the possible directions of further research relevant to H19.
H19 was the first discovered lncRNA; it was firstly reported in 1991 by Bartolomei et al. (1991) and was shown to lack a common open reading frame (ORF). The H19 gene is a well-known imprinted oncofetal gene, which locates on human chromosome 11p15.5 and encodes for a processed 2.3 kb RNA (Pachnis et al., 1984). As an imprinting gene, H19 is maternally expressed and shares a common enhancer region with IGF2 (Insulin-like growth factor 2) gene which expresses the paternal allele (DeChiara et al., 1991). Without relevant encoding protein expression, H19 can be highly expressed in extraembryonic tissues, the embryo proper and most fetal tissues, but not expressed in most tissues postnatally (Matouk et al., 2007a). H19 has been described to be located in both cytoplasm and nucleus, although it was reported mainly in cytoplasm before (Schoenfelder et al., 2007), (Seidl et al., 2006). Recent evidence shows that the expression of H19 can be reactivated during regeneration and tumorigenesis in adult tissue, indicating that H19 is probably related to the development and progression of tumor (Gabory et al., 2010). Further study demonstrates that H19 displays a cell-dependent and/or tumor type-dependent function. However, it is found that H19 also shows a tumor suppressor function in teratocarcinomas and pituitary tumors (Yoshimizu et al., 2008), (Wu et al., 2018). Therefore, it remains unclear whether H19’s functional role is tumor suppressive or oncogenic. The function of H19 is largely dependent on the type of cancer, the stage of tumor formation, and the level of molecular signaling pathway (Matouk et al., 2007b). There are several cancers with abnormal expression of H19: breast cancers, pancreatic cancers (Ma et al., 2014), choriocarcinomas (Arima et al., 1997), hepatocellular carcinomas (Ye et al., 2019), ovarian cancers (Tanos et al., 1999), and so on (Ariel et al., 2000a). Furthermore, it is shown that the poor prognosis of patients is correlated with overexpressed H19, especially in higher grades and invasive transitional cell carcinomas (Ariel et al., 2000b), (Ariel et al., 1995), (Gao et al., 2018). The molecular mechanisms between H19 and tumorigenesis, as shown in Figure 1, largely depend on the partners that H19 interacts with.
As reviewed by Callum Livingstone, the expression of IGF2 is associated with the development of various cancers (Livingstone, 2013). H19 and IGF2 are demonstrated to compete each other for binding enhancer. Thus, H19 could regulate the progression of cancer by changing the expression of IGF2 (Schmidt et al., 1999). What’s more, in bladder cancer, H19 has been found to interact with polycomb repressive complex 2 (PRC2) by associating with enhancer of zeste homolog 2 (EZH2), which leads to the silencing of the E-cadherin gene (Luo et al., 2013). In this way, increasing expression of H19 could downregulate E-cadherin (repressor of cell invasion and metastasis) and Nkd1 (inhibitor of Wnt/β-catenin signaling), causing the progression of cancer cells (Zhang et al., 2017) (Figure 1①).
Our previous study suggested that H19 could bind to SAHH (S-Adenosylhomocysteine Hydrolase) and inhibit it, so as to catalyze SAH hydrolysis (Zhou et al., 2015) (Figure 1②). SAH affects cellular DNA methylating, which means that H19 may alter the methylation of DNA and lead to distinct tumorigenesis. (Martinez-leal et al., 2008). Besides, MBD1 (Methyl-CpG–Binding Domain Protein 1), the partner protein of H19, can induce methylation at H3K9me3 (lysine 9 of histone H3) to differentially methylated regions (DMRs) of correlated imprinted genes like IGF2, SLC38A4 (tumor suppressor in hepatocellular carcinoma) and PEG1 (Monnier et al., 2013), (Li et al., 2021).
LncRNA 91H is a novel H19 antisense RNA which was first revealed by Berteaux et al. (2008) LncRNA 91H contributes to the expression of IGF2, showing its oncogenic role in breast cancer cells. HOTS (H19 opposite tumor suppressor), an H19 antisense transcript, is confirmed to inhibit tumor growth in rhabdomyosarcoma and choriocarcinoma (Onyango and Feinberg, 2011) (Figure 1③).
As the protein encoded by tumor suppressor gene TP53, p53 is reported to repress the expression of H19 by binding to H19 promoter (Lottin et al., 1998). E2F1 is a transcription activator of E2F family which helps to carry out cell cycle. Berteaux et al. (2005) elucidated that E2F1 could also bind to H19 promoter, resulting in G1/S transition and cell proliferation of breast cancers. Moreover, by recruiting and directly binding to eIF4A3 (an RNA-binding protein), H19 promotes the growth of colorectal cancer. Similarly, hypoxia-inducible factor 1-alpha (HIF1α) can physically interact with H19, inducing smooth muscle cell apoptosis and abdominal aortic aneurysm development (Li et al., 2018). However, the tumorigenesis pathway influenced by the interaction between H19 and different kinds of protein is still under exploration (Han et al., 2016) (Figure 1④).
The regulation of miR-675 by H19 is illustrated to be responsible for limiting placental growth before birth and the progression of different Cancers (Keniry et al., 2012) (Figure 1⑤). As Matouk et al. (2015) have summarized, H19 derived miR-675 can induce epithelial mesenchymal transition (EMT) and promote tumorigenesis in many cancer types. In detail, H19 serves as the precursor of miR-675 and promotes it to directly target c-Cbl and Cbl-b mRNA so as to decrease their expression, leading to sustained activation of AKT and ERK pathways as well as enhanced cell proliferation and migration in breast cancers both in vitro and in vivo (Vennin et al., 2015). Other targets of miR-675 in tumors contain: Retinoblastoma protein (RB, a tumor suppressor) in colorectal cancer (Tsang et al., 2010), Twist 1 (a key mediator in epithelial-mesenchymal transition) in hepatocellular cancer (Hernandez et al., 2013), Runt Domain Transcription Factor1 (RUNX1, a tumor suppressor) in gastric cancer (Zhuang et al., 2014), Cadherin 13 (a member of cadherin subfamily) in glioma (Shi et al., 2014a), G protein-coupled receptor (GPR55) in non-small cell lung cancer (He et al., 2015), early growth response protein1 (EGR1) in human liver cancer (Li et al., 2015). MiR-675 is also found to modulate p53 level during bladder cancer cell growth and colorectal tumor metastasis, though p53 is not a direct target of miR-675 (Liu et al., 2016), (Cen et al., 2019).
H19 can also function as ceRNA (competing endogenous RNAs) by antagonizing miRNAs (Angrand et al., 2015) (Figure 1⑥). As a molecular sponge, H19 modulates the function of let-7 family miRNA to promote the development of cancers such as pancreatic ductal adenocarcinoma (Kallen et al., 2013). Moreover, there are many other miRNAs which can be sponged by H19: 1) miR-200 family to suppress metastasis of hepatocellular carcinoma (Zhang et al., 2013), 2) miR-200a and miR-138 to promote EMT in colon cancer (Zhang et al., 2013), 3) miR-200b/c to mediate EMT and MET in breast cancer (Zhou et al., 2017a), 4) miR484 and miR29b-3p to promote cell viability and EMT in lung cancer (Zhang et al., 2018), (Liu et al., 2019), 5) miR‐130a‐3p and miR‐17‐5p to develop cardiac cancer (Jia et al., 2019), 6) miR-106a-5p to promote the growth of melanoma by upregulating E2F3 (a member of the E2F transcription factor family) expression (Luan et al., 2018).
Resistance to drug therapy has always been a great barrier to overcoming cancer. Each antitumor agent interacts with cancer cells in its own specific way, and each tumor has its own specific characteristics that determine its tumor progression. Numerous drug-resisting mechanisms has arisen as the result of the interactions between different tumors and drugs (Vasan et al., 2019). Generally, by acting on the surface or entering the cells, curative drugs can function within the tumor cells and alter the micro-environment at the same time. Some tumors are intrinsically resistant to specific drug damage. As reviewed, the tumor intrinsic factors affecting drug resistance are mainly derived from the genetic, transcriptional or functional characteristics of tumor cells themselves (Kalbasi and Ribas, 2020). For example, some cancers overexpress multi-drug resistance protein1 (MDR1) without previous exposure to chemotherapeutic agents, thus possessing intrinsic drug resistance (Thomas et al., 2003). As for acquired drug resistance, the mechanisms can be split into five components at the cellular level. Firstly, regulating drug uptake and efflux is an important way to establish drug resistance (Gottesman, 2002). ATP-binding cassette (ABC) family, including P-glycoprotein (P-gp), multi-drug resistance-associated protein1 (MRP1) and breast Cancer resistance protein (BCRP/ABCG2), is an important membrane transporter family. It can not only transport nutrients and other molecules, but also mediate the release of drugs (Fletcher et al., 2016). Secondly, compartmentalization of clinical cytotoxic agents apart from their cellular/tissue targets in lysosomes, autophagosomes, and other intercellular vesicles, will promote drug resistance in cancer (Feng et al., 2014). Thirdly, changes in drug targets and enhanced inactivation of drugs by affecting cell metabolism also play important roles in drug resistance (Bar-Zeev et al., 2017). Moreover, because the ultimate targets of many chemotherapeutic drugs are nuclear DNA, the repair of these DNA becomes one of the most well-known mechanisms of drug resistance in cancer. Nucleotide excision repair system (NER) and homologous recombination repair mechanisms (RRM) are two major DNA repair systems, which can be impaired by gene mutation and epigenetic silence (Mansoori et al., 2017). Finally, blocking cell death pathways has been found to possibly result in drug resistance (Pistritto et al., 2016). Since apoptosis is the main pathway of cell death induced by most anticancer drugs, the anti-apoptotic signaling pathways are always overactive in drug-resistant cells (Wong, 2011).
H19 has been shown to be involved in and expressed in almost every form of human cancers at all stages of tumorigenesis (Raveh et al., 2015). Chemotherapy, as well as endocrine therapy and targeted therapy, is one of the most effective approaches for the treatment of human cancers. Unfortunately, once drug resistance is established, these anti-cancer drugs cannot always kill tumor cells (Szakács et al., 2006). Although there are various molecular mechanisms for MDR, as shown in Figure 2, the pathways relevant to H19 still remain unclear in the occurrence of MDR. Researchers have so far confirmed several important roles that H19 plays in drug resistance of various cancers (Ghafouri-Fard et al., 2021), (Du et al., 2020). The role of H19 in the therapeutic resistance of human cancers are summarized in Table 1.
Breast cancer is one of the most prominent and aggressive cancers in women (Israel et al., 2018). Female breast cancer has become the first commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%) in 2020 (Sung et al., 2021). H19 is involved in breast cancer cell growth, metastasis, and multiple drug resistance in different ways (Si et al., 2019), (Malhotra et al., 2017). A schematic illustration of the mechanisms by which H19 is involved in breast cancer therapy resistance is presented in Figure 2. In Tamoxifen-treated or Fulvestrant-treated estrogen receptor-alpha positive (ERα+) breast cancer tumors, high H19 expression is associated with increased drug resistance. H19 acts as an estrogen receptor modulator to promote the expression of ERα protein in endocrine therapy resistance (ETR) cells (Basak et al., 2018). Gao et al. (2018) found that knockdown of H19 could elevate tamoxifen sensitivity via Wnt/β-catenin pathway and EMT process in ER + breast cancers in vitro. Generally, tumors enhance autophagy activity to promote their metabolism and survival, to survive under microenvironmental stress, and to facilitate proliferation and aggressiveness (White, 2015). H19 activates autophagy via the downregulation of methylation in the promoter of Beclin1 by H19/SAHH/DNMT3B axis (SAHH and DNMT3B are two different sequences involved in tumor progression (Tan et al., 2017), (Sowińska et al., 2007). This process contributes to tamoxifen resistance (TAMR) in breast cancer (Wang et al., 2019). Moreover, N-acetyltransferase 1 (NAT1) was notably downregulated in MCF7/TAMR cell lines, but significantly elevated when knockdown H19. So it was possible that H19 conferred tamoxifen resistance via the mediation of NAT1 promoter methylation (Sun et al., 2022). Through analysis of gene functional groups, the expression of H19 is markedly higher in MCF7/TAMR cell lines (GSE26459). H19 has a positive correlation with heat shock protein family B (small) member 8 (HAPB8). And over-expression of HSPB8 may induce ETR through the regulation of autophagy (Gonzalez-Malerva et al., 2011). In another study with high H19 in BT474/TAMR (GSE112883), high exportin1 (XPO1) expression correlated with high ERα protein level, and high level of Akt signaling expression to help the tumor cell survive (Kulkoyluoglu-Cotul et al., 2019). MiR-200 family was found to be sponged by H19 in several cancers, such as hepatocellular carcinoma (Zhang et al., 2013). Genomic analysis indicates that decreased miR-200b/c is associated with increased ZEB1 protein and the promotion of EMT in MCF7 cisplatin resistant cells (MCF7/CDDP). As reviewed above, H19 may sponge miR-345 to inhibit its expression, which upregulates MRP1 to promote cisplatin efflux in MCF7/CDDP (Pogribny et al., 2010). Apart from cisplatin, doxorubicin is another common drug tends to develop resistance to chemotherapy in breast cancer (Abe, 2005). It was reported that H19 induced 95-kilodalton membrane glycoprotein (p-95) expression to develop doxorubicin resistance in MCF-7 cells (Doyle et al., 1996). A new research revealed that H19 took part in the downregulated expression of Poly (ADP-ribose) polymerase (PARP)-1 to induce doxorubicin resistance both in vitro and in xenograft models (Wang et al., 2020a). Another study has also confirmed the H19 is over expressed in doxorubicin-resistant breast cancer cell subline compared with the matching parental cells. Additionally, H19 could be transferred from resistant cells to sensitive cells through exosomes, facilitating the chemoresistance of doxorubicin (Wang et al., 2020b). Upregulation of H19 has also enabled the chemoresistance of paclitaxel and anthracyclines analogues like doxorubicin in MCF-7 cells through H19-CUL4A-ABCB1/MDR1 (CUL4A, an ubiquitin ligase component; ABCB1, a member of the ATP-binding cassette family, which encodes MDR1) and ABCC4/MRP4 pathway (Zhu et al., 2017). In paclitaxel resistant cell line, the expression of ERα protein has a tight linkage with H19, suggesting that H19 is a downstream target of ERα. Associated with EZH2, H19 can downregulate the pro-apoptotic gene BIK and NOXA to inhibit apoptosis in ERα+ breast cancers (Si et al., 2016). Similarly, the over-expression of H19 has also been confirmed as an underlying therapeutic target in paclitaxel-resistant breast cancer cell subline. By binding with miR-340-3p, H19 subsequently regulates YWHAZ and potentiates the Wnt/β-catenin signaling. Such regulation can promote breast cancer cells’ proliferation, metastasis, and EMT features while inhibiting their apoptosis (Yan et al., 2020). Besides, H19 can also mediate Akt signaling pathway and inhibit apoptosis to make triple negative breast cancer (TNBC) resist to paclitaxel (Han et al., 2018). Another gene-expression group analysis shows high H19 in MCF7 methotrexate-resistant (MTXR) cell line and low H19 in MDA-MB-468/MTXR (GSE16080). In this study, over-expression of UGT1As was confirmed to induce methotrexate resistance in both breast cancer cell lines (Selga et al., 2009). More information about H19 expression in epirubicin-resistant breast cancer cell lines is summarized in Supplementary Table S1. Human epidermal growth factor receptor 2 (HER2)-positive breast cancer is another common breast cancer subtype, which can be treated by targeted drugs such as trastuzumab (Cameron et al., 2017). It was hypothesized that trastuzumab resistant HER2-positive breast cancer cells might be formed by downregulating Cbl through H19-derived miR-675 (Sun et al., 2019a).
According to the Global Cancer Statistics 2020, primary liver cancer is now the sixth most commonly diagnosed cancer and the third leading cause of cancer death worldwide. HCC accounts for 75%–85% of all cases of liver cancer (Sung et al., 2021). During the progression of hepatocellular carcinoma, the expression level of H19 transcripts is found imbalanced high (Iizuka et al., 2004). It was reported that knockdown of H19 suppressed MDR1 expression and its transcript P-glycoprotein via regulating MDR1 promoter methylation. This regulation resulted in the increased doxorubicin accumulation level and sensitized doxorubicin toxicity in R-HepG2 cells (Tsang and Kwok, 2007). Similarly, another study showed that the downregulation of H19 might block MAPK/ERK signaling pathway by inhibiting drug resistance genes MDR1 and (glutathione-s-transferase-π) GST-π. H19 was shown to facilitate cell apoptosis and reduce the response of CD133+ HuH7 cells to chemotherapeutic drugs like methotrexate (MTX) (Ding et al., 2018). Moreover, in gemcitabine-resistant HepG2 cell line, H19 showed a close association with high expression of CD44, CD90, and CD133. These three proteins are HCC stem cell markers and predict worse prognosis of HCC (ZJ, 2019). Additionally, Ma et al. (2018) demonstrated that restrained expression of H19 and over-expression of miR-193a-3p enhanced the survival rate of hepatoma cell line when they were tolerant to chemotherapeutic agents [Doxorubicin, paclitaxel, vinorelbine, 5-fluorouracil (5-Fu)]. By targeting H19/miR-193a-3p axis, high expression of presenilin 1(PSEN1) increased γ- H2AX and Rad51 expression, and inducted radio-resistance to single-dose X-ray in HCC cells. Moreover, sorafenib was confirmed to induce apoptosis in HCC, which can be inhibited by potentiating anti-apoptotic member Bcl-xL expression. In human HCC tissues and cell line, low let-7 microRNA can enhance the expression of Bcl-xL and apoptosis (Shimizu et al., 2010). This finding suggests that the effect of sorafenib may be inhibited through high expression of H19 by sponging miR-let-7. Furthermore, it was newly found that upregulated H19/miR-675 expression could elevate sorafenib resistance by promoting EMT in HCC tissue samples and cells (Xu et al., 2020). However, the role of H19 in the therapy of HCC is not completely elucidated. In contrast, in chemo-resistant cells, over-expression of H19 can reverse the drug resistance to doxorubicin, so that suppressing hepatocarcinogenesis and hepatoma cell growth (Schultheiss et al., 2017). Therefore, H19 has a dual effect on therapy resistance in HCC. Figure 3 shows the mechanisms of H19 in the therapy resistance of liver cancer.
Lung cancer is the second most commonly diagnosed cancer and remains the leading cause of cancer death in 2020 (Sung et al., 2021). Currently, the impact of H19 on resistance to therapeutic option is mainly focused on non-small cell lung cancer (NSCLC). Such patients can benefit from the inhibitors of the epidermal growth factor receptor tyrosine kinase (EGFR TKIs), like gefitinib and erlotinib. (Kris et al., 2003). Lei et al. (2018) have proved that gefitinib resistance in NSCLC cells can be induced by packaging the H19 into exosomes and transferring it to these non-resistant cells. Zhou et al. (2017b) testified that miR-200c could enhance sensitivity of drug-resistant NSCLC to gefitinib by decreasing phosphorylated-Akt signaling and Bcl-2 expression. So it can be speculated that high expression of H19 induce gefitinib resistance through sponging miR-200c and inhibiting apoptosis. Similarly, it is proposed that the cooperation between PI3K/Akt pathway and connexin 26 (Cx26) can induce EMT and confer the gefitinib resistance of NSCLC cells (Yang et al., 2015). Thus, H19 silencing has been confirmed to increase the anticancer impacts of gefitinib in NSCLC through upregulation of PTEN and PDCD4 (both are tumor suppressors) and inhibition of nuclear factor I/B (NFIB) (Zhou and Zhang, 2020). Besides, H19 could also confer resistance to gefitinib via miR-148b-3p/dimethylarginine dimethylaminohydrolase-1 (DDAH1) axis in lung adenocarcinoma (Huang et al., 2019). Furthermore, unlike the usual correlation between high H19 expression and drug resistance, it is demonstrated that knockdown of H19 results in the resistance to erlotinib in vivo and in vitro by upregulating pyruvate kinase isoform muscle 2 (PKM2) expression and enhancing the phosphorylation of AKT (Chen et al., 2020). In contrast, upregulated H19 in erlotinib-resistant cells can sponge miR-615-3p to promote autophagy. Packaged exosomal H19 can also facilitate erlotinib resistance through miR-615-3p/ATG7 axis in NSCLC sensitive cells (Pan and Zhou, 2020). H19 mediates the regulation of cisplatin resistance in human lung adenocarcinoma cells through apoptosis inhibition. Consistent with the results in vitro, over-expression of H19 is associated with worse clinical outcomes of patients who receive cisplatin-based therapy (Wang et al., 2017b). From other point, it has been discussed that H19 may promote gene GST-π expression in hepatocellular carcinoma (Ding et al., 2018). In another research, GST-π expression is reported to be positively correlated with the resistance to cisplatin in lung cancer cell lines, which means H19 may affect the lung cancer drug resistance through H19/ GST-π pathway (Wang et al., 2011). Figure 4 shows the mechanisms of H19 in the target therapy and chemotherapy resistance of lung cancer.
Colorectal cancer is the third most commonly diagnosed cancer and the second most common cause of cancer-associated mortality over 185 countries (Sung et al., 2021). As reviewed, 1,25(OH)2D3 (the most active form of vitamin D in the human body) and its analogs have positive anti-tumor effect in colorectal cancer (Dou et al., 2016).S. Chen et al. have found that colon cancer cells show different resistance to the treatment of 1,25 (OH) 2D3 both in vitro and in vivo when H19 is overexpressed. They also discovered that H19 is able to downregulate the expression of Vitamin D receptor (VDR) by transcribing miR-675-5p, indicating the important role of H19 underlying the development of resistance to 1,25 (OH) 2D3 treatment in advanced colon cancer cells (Chen et al., 2017b). Besides, chemotherapeutic resistance is a mainly formidable challenge in the treatment of colorectal cancer (Figure 5). Methotrexate (MTX) is one of anti-metabolite and anti-folate chemotherapeutic agents for various cancers including CRC, and it is revealed that H19 can mediate MTX resistance by activating Wnt/β-catenin signaling in colorectal cancer cell line HT-29 (feng Wu et al., 2017). Through integrative bioinformatics analysis, H19 is observed to play key roles in the process of oxaliplatin or irinotecan resistance in colorectal cancer (Sun et al., 2019b). Meanwhile, H19 shows lower expression in oxaliplatin- and irinotecan-resistant CRC cell lines compared with the parental cells (GSE42387, Supplementary Table S1) (Jensen et al., 2015). Moreover, the exosomes derived from carcinoma-associated fibroblasts (CAFs) have been found to transfer H19 to CRC cells and induce oxaliplatin resistance in vitro and in vivo. Upregulated H19 can activate the Wnt/β-catenin pathway and promote the stemness of CRC cells through sponging miR-141 (Ren et al., 2018). What’s more, it was concluded that many lncRNAs including H19 could act as regulators of autophagy and participate in CRC drug resistance (Bermúdez et al., 2019). Wang et al. (2018a) confirmed that H19 could sponge miR-194-5p to promote autophagy via NAD-dependent deacetylase sirtuin-1(SIRT1), so that to enhance 5-Fu chemoresistance in CRC cells. H19 silencing decreased the expression of MDR1, MRP1, and BCRP, which could reverse the sensitivity to 5-Fu in CRC (Wang et al., 2018b). In 5-Fu resistant rectal cancer cells, H19 was linked with downregulation of RB and p27kip1 (p27, a tumor suppressor) (Yokoyama et al., 2019). In addition, miR-200c was found to reduce the expression of JNK2(a set of enzymes in response to a plethora of stress signals) gene and ABCB1 mediated P-gp; this sensitized the MDR colorectal cancer cells to chemotherapeutic drugs, like cisplatin, 5-FU, pirabucin (Sui et al., 2014). According to previous studies, H19 can potentially sponge miR-200c to regulate the process of MDR in CRC.
The incidence and mortality of gastric cancer (GC) have been both increasing dramatically in most countries worldwide during recent 30 years (Etemadi et al., 2020). Over-expression of H19 has been confirmed to be associated with anti-apoptotic and metastatic properties in gastric cancer, leading to multi-drug resistance of tumor (Li et al., 2014). Cisplatin-resistant gastric cancer cell line SGC7901 showed high expressions of H19/miR-675 and low expression of Fas-associated death domain (FADD), which suppressed caspase8 and caspase3 dependent apoptosis (Yan et al., 2017). What’s more, down-regulation of H19 was shown to reduce doxorubicin 50% inhibition concentration (IC50) and alleviate chemoresistance in GC cells. In this study, H19 can promote the expression of IGF2BP3(IGF2 mRNA binding protein 3) and PEG10 (Paternally Expressed 10) (Ishii et al., 2017). The miR-200 family can be divided into miR-200bc/429 cluster and miR-200a/141 cluster, and these two clusters function specifically on different cell types. In GC cell lines, miR-200bc/429 cluster could target X-linked inhibitor of apoptosis protein (XIAP) and BCL2 to modulate apoptosis, promoting the formation of vincristine (VCR) resistance (Dehghanzadeh et al., 2015), (Zhu et al., 2012).
H19/miR-675 signaling plays a critical role in glioma progression (Shi et al., 2014b). It is the major determinant conferring oncogenic properties to the glioma cells. As reported, the over-expression of H19 can promote temozolomide (TMZ) resistance in glioma cell lines. Compared to the TMZ-sensitive tumors, the major drug resistance genes such as MDR, MRP, and ABCG2 and their expressed mRNA and protein are found to upregulate in the TMZ-resistant (TMZR) glioma cell lines (Jiang et al., 2016). Through gene expression analysis between glioblastoma LN229 cell line and LN229/TMZR, H19 shows a lower expression in resistant cell line (GSE113510). The researchers focused on increased MGMT (O6-methylguanine-DNA methyltransferase) expression regulated by lncRNA TALC (temozolomide-associated lncRNA in glioblastoma recurrence) in TMZR cells (Wu et al., 2019a). Similar study in other temozolomide resistant glioma cells shows that H19 can confer temozolomide resistance by modulating MGMT expression (Xu et al., 2017). Additionally, via integrated bioinformatics analyses, Xiao et al. (2020) have found that H19’s copy number variations could affect the infiltration level of glioma immune cells. Consequently, H19 may be future target to the immunotherapy for glioma.
Recently, it was shown that the expression of H19 was enhanced in cisplatin-resistant ovarian cancer cells. H19 can confer cisplatin resistance to ovarian cancer cells via regulating glutathione metabolism in vitro and in vivo (Zheng et al., 2016). Sajadpoor et al. (2018) confirmed that valproic acid (VPA) could negatively regulate the H19 and EZH2 expression in ovarian cancer A2780 cisplatin-resistant cells, which subsequently lead to cell apoptosis. Therefore, H19 could increase cisplatin resistance in ovarian cells by targeting EZH2/p21/PTEN pathway. Another research revealed that EMT transcription factors snail and slug contributed to cisplatin resistance in ovarian cancer, indicating the potential new mechanism between H19 and cisplatin resistance (Haslehurst et al., 2012). Downregulation of H19 can inhibit EMT, migration and sensibility of cisplatin in these cells (Wu et al., 2019b). Another studies about gene expression difference in ovarian cancer also showed high H19 expression in cisplatin and oxaliplatin resistant ovarian cancer cells (GSE28648) (Zeller et al., 2012). The role of miR-483-3p and modulated protein kinase C α(PKCα) was focused on the occurrence of drug resistance (GSE58472) (Arrighetti et al., 2016).
Moreover, H19 promotes the cisplatin resistance in seminoma, resulting from the increasing expression of TDRG1 (testis developmental related gene 1) by sponging miRNA‐106b‐5p (Wei et al., 2018). H19 targeting miR‐130a‐3p and miR‐17‐5p could increase overall survival of cardiac cancer cells treated with cisplatin, doxorubicin, mitomycin, and 5‐fluorouracil (5-FU), leading to the establishment of chemoresistance for cardiac cancer (Jia et al., 2019). H19 is also related to the drug resistance of choriocarcinoma (CC). The resistance of CC cells to MTX and 5-FU could be reduced after H19 is depressed. By knocking out gene H19, the proliferative, migratory, and invasive ability can be decreased and the apoptosis can be increased in MTX/5-FU treated CC cells (Yu et al., 2019). Besides, H19 over-expression would induce bortezomib resistance in multiple myeloma by targeting MCL-1 via miR-29b-3p (Pan et al., 2019). Laryngeal squamous cell carcinoma (LSCC) is a highly aggressive malignancy, accounting for approximately 90% of all laryngeal cancer (Siegel et al., 2015). Notably, expression of H19 has been shown to be increased in LSCC tissues and drug-resistant cells. The resistance to cisplatin is mediated via H19/miR-107/HMGB1 axis and subsequent autophagy (Chen et al., 2021). In nasopharyngeal carcinoma, knockdown of H19 in drug-resistant cells significantly increases their chemoresistance through apoptosis promotion. When combined with paclitaxel, silencing H19 could enhance tumor inhibition in vivo (Zhu, 2020). Neuroendocrine prostate cancer (NEPC) is a highly lethal subtype of prostate cancer with high expression of H19. By binding to PRC2, H19 induces epigenetic changes and promotes the association of H19 with EZH2. Knockdown of H19 was testified to re-sensitize NEPC to enzalutamide (Singh et al., 2021).
The three primary types of anti-tumor systemic treatment are chemotherapy, endocrine therapy, and targeted therapy. According to the mechanism of action on cancer cells, the chemotherapy drugs we commonly use are divided into four categories: Antimetabolites (like MTX, 5-FU), DNA alkylators (like cisplatin, oxaliplatin, temozolomide), Tubulin/microtubule inhibitors (like paclitaxel, vincristine), and DNA topoisomerase inhibitors (like doxorubicin, mitomycin, pirabucin) (Bailly et al., 2020). Endocrine therapy drugs can be divided into three types: Hormone replacement drugs (like 1,25(OH)2D3), Hormone elimination drugs, and Anti-hormone drugs (like fulvestrant, tamoxifen). Small molecule-targeted therapy drugs (such as sorafenib, gefitinib, bortezomib) and monoclonal antibody (such as trastuzumab) are typical targeted therapy drugs. Many of the above-mentioned drugs may develop tolerance when used in certain cancers (Table 2). In chemoresistance, sponging miR-200b/c, miR-345, miR-340-3p to regulate the expression of membrane protein are important mechanisms of H19. Apoptosis intervention usually confers chemoresistance, while autophagy regulation often confers endocrine therapy resistance. H19-mediated Wnt/β-catenin and EMT signaling pathways show important roles in chemoresistance, endocrine therapy resistance and targeted therapy resistance. Particularly, encoding miR-675 shows targeted resistance phenotype in breast cancer and liver cancer. As the summary of potential mechanisms associated with H19 and different anti-tumor drugs, three common ways to promote MDR through H19 are proposed: gene methylation and nuclear epigenetic changes, miRNA control in cytoplasm, and direct association with certain protein/transcription factors (TFs) (Wang et al., 2020c).
The research of cell death has always been closely interrelated with drug resistance research. Until now, the most widely-used classification of programmed cell death is consisted of apoptosis, necrosis, autophagy-associated cell death and ferroptosis (Tang et al., 2019). In previous studies, apoptosis is demonstrated to be the most common form of cell death in the regulation of H19. Gene methylation, miRNA regulation and direct protein interaction all play irreplaceable roles in apoptosis inhibition. Because most of the clinical therapeutic drugs induce cell death through apoptosis, silencing H19 will become a non-negligible method to increase drug efficacy or/and inhibit MDR. As another form of cell death reported frequently, autophagy can also be regulated by gene methylation and miRNA sponge. However, the researches of necrosis and ferroptosis in systemic therapy are scarce. In heart disease, necrosis is the main form of cardiomyocyte death. The miR-103/107-Fas-associated protein with death domain (FADD) pathway is demonstrated to induce necrosis in cardiac cell line H9c2. Consequently, H9c2 cells can be protected from necrosis by upregulating the expression of H19 (Wang et al., 2015). Although this finding was irrelevant to tumorigenesis and drug resistance, it revealed the possible relationship between H19 and cell necrosis. As a new recognized regulated cell death first reported in 2012, ferroptosis gives rise to more and more researches, including those in anti-tumor therapy (Dixon et al., 2012). A recent study reported that inhibition of PI3K-AKT-mTOR signaling axis could sensitize breast cancer cells (BT474 and MDA-MB-453) to ferroptosis induction (Yi et al., 2020). Therefore, H19 may indirectly participate in ferroptosis by activating PI3K-AKT-mTOR signaling. Besides, the expression of iron storage protein ferritin is specifically dependent on H19/miR-675 expression levels. Moreover, the interactive mechanism between ferritin and H19 differs in different cancer cells. It was found that the amounts of ferritin were negatively correlated with H19/miR675 levels in K562 cells (the first human established myelogenous leukemia cell line), but positively related in breast cancer cell line MCF7 cells (Di Sanzo et al., 2018). These researches develop a new level of interactive complexity between iron metabolism and H19 or some miRNAs expression. By regulating iron metabolism, ferroptosis will be broadly discussed in the cell death induction of H19.
Systemic therapy is one of the most important treatments for cancer patients. However, drug resistance has become the most urgent problem hampering our treatment. Along with the development of relevant studies, H19 has been testified to function in the tumorigenesis and drug resistance in human cancers via different mechanisms. Hence, increasing drug sensitivity and decreasing cancer cells drug resistance might be realized by targeting H19. Diphtheria toxin A-chain (DT-A)-H19 has shown anti-cancer effect by suppressing tumor growth in ovarian cancer (Mizrahi et al., 2009). DTA-H19 is a DNA plasmid that contains H19 gene regulatory sequences that drive the expression of an intracellular toxin. As an individualized DNA-based approach, DTA-H19 can be used in the tumors with high H19 expression. A phase 1/2a clinical trial for superficial bladder cancer has proved the therapeutic effect of intravesical DTA-19 (Sidi et al., 2008). Similar to H19, IGF2 is also highly active in various human cancers. The use of double promoter toxin vector H19-DTA-(IGF2)-P4-DTA exhibited superior inhibition towards pancreatic cancer, ovarian cancer, glioblastoma and HCC (Amit and Hochberg, 2012). Nevertheless, more gene editing studies on H19 are still preclinical and are much needed. The regulation of cell death by H19 exerts a wide prospect of molecular research and clinical drug application. In the future, more attention needs to be paid to the additional functions and pathways related to H19, tumorigenesis and cells drug resistance. The research of H19 may provide us with a safer and more effective target to treat MDR and to enrich its function in genetics and molecular biology. | true | true | true |
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PMC9556174 | Polina V. Kniazkova,Viktoriia Yu. Harbuzova,Vladyslav V. Pokhmura | The Link between ANRIL Gene RS4977574 Polymorphism and Common Atherosclerosis Cardiovascular Complications: A Hospital-Based Case-Control Study in Ukrainian Population | 05-10-2022 | Materials and Methods 195 patients with ACS, 200 patients with LAS, and 234 control subjects were enrolled in this case-control study. Real-time PCR was used for ANRIL rs4977574 genotyping. SPSS software package (version 17.0, IBM, USA) was used for data analysis. Results A significant association between rs4977574 polymorphism and the risk of atherosclerosis and cardiovascular complications was found under the recessive model regardless of adjustment for nongenetic risk factors (OR = 1.551; p = 0.025). Moreover, the link between rs4977574 locus and serum levels of total cholesterol (p = 0.021) and LDL (p = 0.022) was detected. A separate analysis in subgroups demonstrated the association of rs4977574 polymorphism with increased risk of ACS under the recessive model (OR = 1.501; p = 0.048). No relation between rs4977574 site and LAS development was revealed (p > 0.05). Conclusion Obtained data suggested that ANRIL rs4977574-GG genotype can be a possible genetic marker for the development of atherosclerosis and cardiovascular complications in Ukrainian population. | The Link between ANRIL Gene RS4977574 Polymorphism and Common Atherosclerosis Cardiovascular Complications: A Hospital-Based Case-Control Study in Ukrainian Population
195 patients with ACS, 200 patients with LAS, and 234 control subjects were enrolled in this case-control study. Real-time PCR was used for ANRIL rs4977574 genotyping. SPSS software package (version 17.0, IBM, USA) was used for data analysis.
A significant association between rs4977574 polymorphism and the risk of atherosclerosis and cardiovascular complications was found under the recessive model regardless of adjustment for nongenetic risk factors (OR = 1.551; p = 0.025). Moreover, the link between rs4977574 locus and serum levels of total cholesterol (p = 0.021) and LDL (p = 0.022) was detected. A separate analysis in subgroups demonstrated the association of rs4977574 polymorphism with increased risk of ACS under the recessive model (OR = 1.501; p = 0.048). No relation between rs4977574 site and LAS development was revealed (p > 0.05).
Obtained data suggested that ANRIL rs4977574-GG genotype can be a possible genetic marker for the development of atherosclerosis and cardiovascular complications in Ukrainian population.
Atherosclerotic lesion of the cardiovascular system is known to be the leading cause of death in the world. It is reported that 30 to 40% of all deaths in different countries are caused by cardiovascular complications of atherosclerosis [1, 2]. That is why today the efforts of many research centers are aimed at revealing the molecular genetic markers and detailed mechanisms of atherosclerosis development. Since 2007, a number of genome-wide association studies (GWAS) have been performed, which have shown a strong link between the human chromosome 9p21.3 region and the development of coronary artery disease (CAD) [3, 4], ischemic stroke [5], and peripheral arterial disease [6]. It is currently established that the three tumor suppressor genes (cyclin dependent kinase inhibitor CDKN2A/p16INK4A, CDKN2A/p14ARF, and CDKN2B/p15INK4B), the methyladenosine phosphorylase gene, and the gene of long noncoding RNA (lncRNA) ANRIL (antisense noncoding RNA in the INK4 locus) are localized both on the sense and antisense strands of the chromosome 9p21.3 region [7]. ANRIL is considered a key gene in this genomic locus in the context of atherosclerosis onset and development. Functional studies by Yari et al. showed a significant decrease in the expression of the ANRIL transcript EU741058 in the peripheral blood of CAD patients [8]. Cho et al. found a significant reduction in the formation of the ANRIL transcript DQ485454 in the endothelial cells of arteries affected by atherosclerosis [9]. Moreover, the positive correlation between atherosclerosis severity and expression of ANRIL transcripts EU741058 and NR_003529 in atherosclerotic plaques was revealed by Holdt et al. [10]. It has also been shown that the polymorphic loci of the 9p21.3 region with the highest contribution to the risk of CAD development are located exactly in the ANRIL gene [11]. The question of specific molecular mechanisms of lncRNA ANRIL is not yet fully disclosed. However, it is assumed that the main effects of ANRIL transcripts are carried out through the interaction with proteins of polycomb repressive complex 1 and 2 (PRC1 and PRC2). Ultimately, this leads to epigenetic cis-inactivation of the already mentioned tumor suppressor genes: p16INK4A, p14ARF, and p15INK4B [12]. The ANRIL gene (official name: CDKN2B-AS1; Gene ID: 100048912) consists of 126307 nucleotide pairs (NC_000009.12) and contains at least 21 exons. To date, more than 25 different linear and circular ANRIL isoforms formed during transcription have been described [13]. As of September 2021, 50,580 polymorphic loci are located in the ANRIL gene (according to the NCBI: https://www.ncbi.nlm.nih.gov/snp/?term=CDKN2B-AS1). It is considered that the single nucleotide polymorphism (SNP) rs4977574 is one of the most significant in relation to the occurrence of cardiovascular diseases. The results of several GWASs have shown a strong link between this polymorphic site and CAD development [11, 14, 15]. A large number of case-control studies to investigate the association of the rs4977574 locus with the risk of CAD [16–18], myocardial infarction [19–21], ischemic stroke [20, 22], and hypertension [23] has also been performed. In addition, several meta-analyses have confirmed an association between the rs4977574 polymorphism and the risk of myocardial infarction and ischemic stroke [16, 22, 24–26]. Most of the mentioned studies have been performed in different populations of Asia and America. There is almost no information on the different allelic variants distribution of ANRIL rs4977574 polymorphism among Ukrainians. The question of the possible link between rs4977574 SNP and the risk of atherosclerosis complications in Ukrainian population is totally uncovered. That is why we decided to perform our study.
The aim of the present work was to test the possible association between ANRIL gene rs4977574 polymorphism and the development of acute coronary syndrome and large artery stroke in Ukrainian population.
In sum, 629 unrelated Ukrainians were enrolled in this hospital-based study. All subjects were divided into case (395) and control (234) groups. The case group included 195 patients with acute coronary syndrome (ACS) and 200 patients with large artery stroke (LAS). All ACS patients were treated in the cardiology department of the Sumy Regional Clinical Hospital for War Veterans and Sumy Regional Clinical Hospital. The diagnosis of acute myocardial infarction and unstable angina was established on the basis of clinical, ECG, and biochemical examination in accordance with the recommendations of the European Society of Cardiology [27]. LAS patients were registered at the dispensary in the outpatient department of the Sumy Clinical Hospital No. 5. The ischemic nature of the stroke was established according to the anamnesis, disease clinical picture, and results of the brain magnetic resonance imaging. The subtype of ischemic stroke was determined according to the TOAST criteria [28] on the basis of anamnesis, disease, clinical course, and results of ECG and ultrasound Doppler examination of the main head arteries. Patients with cardiogenic shock, severe renal and hepatic failure, bronchial asthma, trauma or major surgery, acute or chronic inflammation in the acute stage, malignant tumors, and systemic diseases were excluded from the study. On the first day of hospitalization, serum lipid profiles (total cholesterol, HDL, LDL, and triglycerides) were determined in 195 ACS patients and 187 LAS patients. Thus, the analysis of the effect of rs4977574 polymorphism on lipid metabolism was performed in 382 patients. The control group included relatively healthy patients who underwent routine checkup at the Sumy Clinical Hospital No. 5 and the Sumy Regional Clinical Hospital. The absence of cardiovascular pathology was confirmed by collecting anamnestic data, recording ECG, blood pressure, measuring, and studying of blood biochemical parameters. The study was complied with the principles of the Helsinki Declaration and was approved by the Bioethics Commission of the Medical Institute of Sumy State University (number 1/11 12 November, 2018). All participants provided written informed consent before enrollment.
Blood leukocyte DNA was extracted using commercial GeneJET Whole Blood Genomic DNA Purification Mini Kit (Thermo Fisher Scientific, USA). The genotyping of ANRIL gene polymorphic site rs4977574 was performed by real-time polymerase chain reaction (Real-time PCR) using TaqMan assay C_1754681_10 (catalog number: 4351379). Allele A was determined using probe containing fluorescent dye VIC, allele G: fluorescent dye FAM. The volume of reaction system was 10 μl, including 5 μl Master Mix 2x, 3.25 μl H2O, 0.25 μl forward and reverse primers, and 1.5 μl genomic DNA. The QuantStudio 5 Dx Real-Time instrument (Applied Biosystems, USA) was used for reaction. The amplification consisted of an initial 10 minute denaturation (95°C) followed by 45 cycles of amplification for 15 sec (95°C) and for 30 s (60°C).
Mathematical data analysis was performed using the SPSS software package (Statistical Package for the Social Sciences, version 17.0, IBM, USA). Continuous data were checked for normality using the Kolmogorov-Smirnov test. All continuous variables are presented in the form of mean and standard deviation (M ± SD). The correspondence of the rs4977574 genotype frequency to the Hardy–Weinberg equilibrium was assessed using the Pearson χ2 test. Comparative analysis of the genotype distribution, as well as the distribution of other categorical variables between the tested groups, was also performed using the χ2-criterion. Student's t-test for two independent samples was used to compare the mean values between two groups. The mean values between the carriers of three different rs4977574 genotypes were compared using the ANOVA method with the subsequent Bonferroni post hoc test. To determine the risk of atherosclerosis complications depending on the specific rs4977574 genotype, the binary logistic regression was applied. Multivariable logistic regression was used to adjust the analysis for sex, age, body mass index, smoking habit, and hypertension. Values of p < 0.05 in all tests were considered as statistically significant.
The general characteristics of the comparison groups are presented in Table 1. It was shown that the mean age in the control group (66.1 ± 14.5) was significantly higher than in patients with atherosclerosis (61.4 ± 11.0; p < 0.001). This fact increases the reliability of control, as it reduces the likelihood of atherosclerosis complications in later periods of these individuals' lives. In return, the case group had significantly higher mean systolic blood pressure (p < 0.001), mean diastolic blood pressure (p < 0.001), mean fasting glucose (p < 0.001), the number of people with hypertension (p < 0.001), the number of people with overweight (p = 0.012), and smokers (p = 0.003). No difference in the ratio of subjects of different sexes between the two groups was found (p = 0.744). The lipid profile parameters in patients with atherosclerosis complications are shown in Table 2. The serum blood concentration of total cholesterol and LDL in patients with ACS was significantly higher than in LAS patients (p < 0.001). However, the difference in the level of HDL and triglycerides between ACS and LAS patients was absent (p = 0.113 and p = 0.890, respectively). The distribution of ANRIL rs4977574 genotypes in the control group (G-allele frequency = 0.438), in the common case group (G-allele frequency = 0.516), in ACS patients (G-allele frequency = 0.528), and in LAS patients (G-allele frequency = 0.505) did not deviate from the Hardy-Weinberg equilibrium (p = 0.276, p = 0.052, p = 0.058, and p = 0.397, respectively). Table 3 indicates the results of ANRIL gene rs4977574 genotyping in both groups. It was revealed that the difference in the distribution of three different rs4977574 genotypes (AA, AG, and GG) between the control and general case group was significant (p = 0.036). The separate comparison of control subjects with LAS patients showed no significant difference in the distribution of rs4977574 genotypes (p = 0.162). At the same time, the frequency of rs4977574 genotypes in ACS patients significantly differed from the control group (p = 0.035). The results of ANRIL rs4977574 genotypic association with the development of atherosclerosis and cardiovascular complications are shown in Table 4. A significant association between rs4977574 locus and the risk of atherosclerosis complications (analysis in the general group) was found under the dominant (ORobs = 1.436, CI 95% = 1.009‐2.044; pobs = 0.044) and recessive (ORobs = 1.551, CI 95% = 1.058‐2.273; pobs = 0.025) models of inheritance. After adjusting for sex, age, body mass index, smoking, and hypertension, the association between rs4977574 locus and the risk of atherosclerosis complications remained only under the recessive model (padj = 0.048). Thus, individuals with the GG genotype had a 1.501-fold higher risk of atherosclerosis and cardiovascular complications (CI 95% = 1.003‐2.246) compared with A-allele carriers. The link between rs4977574 polymorphism and the risk of LAS development was absent in all models of inheritance both before and after adjustment for covariates (p > 0.05). Instead, a significant relation between rs4977574 locus and the ACS was found under recessive inheritance model (ORobs = 1.719, CI 95% = 1.110‐2.660; pobs = 0.015). The statistical significance of the obtained results was preserved even after adjusting for nongenetic risk factors (padj = 0.049). The risk of ACS in individuals with GG genotype was 1.648 times (CI 95% = 1.002‐2.711) higher than in individuals with AA and AG genotypes. A possible link between different ANRIL rs4977574 genotypes and lipid profile parameters in the case group was also analyzed (Table 5). The results of ANOVA test in the general group revealed the association of rs4977574 locus with the serum concentration of total cholesterol (p = 0.021) and LDL (p = 0.022). The Bonferroni post hoc test showed a significant difference between GG and AA genotypes (p = 0.019, for total cholesterol; p = 0.025, for LDL). There was no relation between rs4977574 site and lipid profile parameters separately in LAS and ACS patients (p > 0.05).
Thus, the relation between ANRIL gene rs4977574 polymorphism and the development of common atherosclerosis cardiovascular complications in the Ukrainian population was tested. The results in the general group revealed the significant association of rs4977574-GG genotype with increased risk of atherosclerosis lesions. A separate analysis in subgroups demonstrated that the rs4977574-GG genotype is linked to an increased risk of ACS, but not of LAS. Over the past decade, a number of studies to determine the involvement of rs4977574 polymorphism in the development of various atherosclerosis complications have been published. Shanker et al. revealed that the G-A-A-A-A haplotype formed from five ANRIL gene polymorphic sites (rs1333049, rs10757278, rs2383206, rs4977574, and rs10757274, respectively) is associated with a two-fold reduction of the CAD risk in the Indian population [17]. The association between ANRIL gene rs4977574 locus and the occurrence of myocardial infarction in the Turkish population was revealed by Sakalar et al. [21]. Instead, Temel et al. did not find the link between rs4977574 polymorphism and CAD development in the Turkish population [18]. The results of a prospective cohort study in the Swedish population showed that the G-allele of the rs4977574 SNP increased the risk of ischemic stroke and myocardial infarction by 16% [20]. Studies in the Chinese population performed by Wang et al. demonstrated a strong association of the rs4977574 polymorphism with an increased risk of myocardial infarction, which persisted after adjustment for nongenetic risk factors [19]. The results of a case-control study by Huang et al. also showed a strong link between SNP rs4977574 and CAD development in the Chinese population [16]. Moreover, the authors also conducted a meta-analysis of the already published studies [29]. Obtained results confirmed the association of the G-allele with an increased risk of CAD occurrence. In the last few years, the results of three independent meta-analyses performed by Chinese researchers have also been published [24–26]. The significant link between ANRIL gene rs4977574 polymorphism and the development of CAD and myocardial infarction was reported. In addition, Wang et al. performed both their own case-control study and meta-analysis to verify the relationship between the rs4977574 locus and ischemic stroke onset [22]. In contrast to our results, both analyses showed that the G-allele of rs4977574 SNP is related to an increased risk of ischemic stroke. The results of our study showed the association between rs4977574-GG genotype and elevated serum concentrations of total cholesterol and LDL in patients with cardiovascular complications of atherosclerosis. Similar data were obtained by Temel et al. [18]. It was shown that the level of total cholesterol in the blood serum of CAD patients with rs4977574-GG genotype was significantly higher than in the main A-allele carriers. In addition, Hindy et al. reported that G-allele of rs4977574 locus was associated with reduced HDL serum levels in Swedes and nonsmokers [20]. Instead, no effect of rs4977574 locus on lipid profile in patients with myocardial infarction was detected by Wang et al. [19]. We have shown that the frequency of the rs4977574-G allele in the control group was 0.438, while in the common case group: 0.516. According to the 1000 Genomes project, the average frequency of G-alleles in the global population is 0.395; in Europeans: 0.492; in the population of both Americas: 0.416; in Central Asia: 0.531; in South Asia: 0.484; and in the African populations: 0.141 [26]. More detailed data from the European countries have shown that the G-allele frequency in Sweden population is 0.448 [20] and in the Finnish population: 0.355 [23]. Thus, the frequency of the G-allele of rs4977574 polymorphism in the Ukrainian population corresponds to this indicator in Europe and South Asia, and mostly in line with the Sweden population. It is known that the polymorphic locus rs4977574 is located in the 16th intron of the ANRIL gene (103785th position). The question of the effect of this SNP on the transcription functioning of lncRNA ANRIL and the development of atherosclerotic phenotype remains debatable. According to the main hypothesis, it is assumed that the genotype of the rs4977574 intron locus may affect the balance between the formation of linear and circular ANRIL isoforms in proatherogenic cells, in particular, in macrophages and smooth muscle cells [7]. It is proposed that the presence of the G-allele leads to enhanced formation of linear isoforms of ANRIL molecule along with reduced expression of the circular ANRIL transcripts. The linear isoforms of the ANRIL molecule activate the PRC1, causing repression of tumor suppressors (CDKN2A and CDKN2B). Eventually, this leads to inhibition of apoptosis and excessive proliferation of proatherogenic cells. Instead, the A-allele may contribute to the enhanced formation of the circle ANRIL isoforms. Such type of ANRIL transcripts inhibits the activity of the PeBoW complex required for rRNA maturation. This in turn leads to rRNA deficiency, nucleolar stress, and p53 protein activation, culminating in the inhibition of cell division and apoptosis activation. There are several limitations in our case-control study. The number of people enrolled in our study was relatively small. Moreover, persons treated in only two specific hospitals of one city were included. Thus, the association with LAS development, as well as with some lipid profile parameters could be missed due to small statistical power and weak population diversity. In addition, the relation between rs4977574 genotype and ANRIL isoform expression was not tested. However, we are going to perform such experiments in the near future. At the same time, we hope that the results of the present study will become an important part of the future meta-analysis of the link between ANRIL gene rs4977574 polymorphism and the development of atherosclerosis cardiovascular complications in European populations.
This is the first case-control study to analyze the relationship between ANRIL genetic polymorphism and cardiovascular disease development in the Ukrainian population. The obtained results showed that rs4977574 polymorphism is associated with atherosclerosis and may affect lipid profile. It was found that the rs4977574-GG genotype is linked to the increased risk of atherosclerosis and cardiovascular complications, and in particular, to the increase of ACS risk. However, no association between rs4977574 locus and the LAS development was established. | true | true | true |
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PMC9556209 | Yu-Mei Jia,Cai-Feng Zhu,Ze-Yu She,Meng-Meng Wu,Yang-Yang Wu,Bing-Yuan Zhou,Na Zhang | Effects on Autophagy of Moxibustion at Governor Vessel Acupoints in APP/PS1double-Transgenic Alzheimer's Disease Mice through the lncRNA Six3os1/miR-511-3p/AKT3 Molecular Axis | 05-10-2022 | Objective To explore the effect and mechanism of moxibustion at acupoints of the governor vessel on lncRNA Six3os1 in amyloid precursor protein/presenilin1 (APP/PS1) double-transgenic Alzheimer's disease (AD) mice. Methods Twenty-four specific pathogen-free and APP/PS1 double-transgenic male mice were randomly allocated into the AD model and moxibustion groups, with 12 cases in each group. Twelve syngeneic C57BL/6J mice were selected as the control group. Mice in the moxibustion group received aconite cake-separated moxibustion at the Baihui acupoint. Suspension moxibustion was applied at Fengfu and Dazhui for 15 minutes each day. All treatments were conducted over two weeks. Control and AD model mice were routinely fed without any intervention. Behavioral observation tests were conducted before and after the intervention. The autophagosome in the hippocampus was observed using transmission electron microscopy. Immunohistochemistry was performed to detect Aβ1-42 expression. LC3B and P62 expressions were evaluated by immunofluorescence. The expression levels of the lncRNAs Six3os1, miR-511-3p, and AKT3 were detected by qRT-PCR. The differential expression of PI-3K, AKT3, mTOR, LC3B-II/I, and P62 proteins in the hippocampus was detected by western blot. The dual-luciferase assay was undertaken to examine the targeting relationships of the lncRNAs Six3os1, miR-511-3p, and AKT3. Results Compared with the control group, the AD model showed higher escape latency in the Morris Water Maze and reduced autophagic vacuoles in the cytoplasm of hippocampal neurons (both p < 0.01). Compared with the control group, the AD model showed higher expression of Aβ1-42, the lncRNAs Six3os1, PI-3K, mTOR, P62, and AKT3 protein (all p < 0.01); but lower mir-511-3p and LC3B (both p < 0.01). Compared with the AD model group, the moxibustion group had a shorter escape latency, more autophagic bubbles in the hippocampus, and lower expression of positive Aβ1-42, the lncRNAs Six3os1, PI-3K, mTOR, P62, and AKT3 protein (all p < 0.01). In contrast, the levels of miR-511-3p and LC3B proteins were considerably increased in the moxibustion group compared to the AD model group (both p < 0.01). Based on the dual-luciferase assay, there was a targeting link among the lncRNAs Six3os1, miR-511-3p, and AKT3. Conclusion Moxibustion at acupoints of the governor vessel can suppress the lncRNA Six3os1 expression, promote cell autophagy, accelerate Aβ1-42 clearance and alleviate cognitive dysfunction of AD mediated by the PI3K/AKT/mTOR signaling pathway through the lncRNA Six3os1/miR-511-3p/AKT3 axis. | Effects on Autophagy of Moxibustion at Governor Vessel Acupoints in APP/PS1double-Transgenic Alzheimer's Disease Mice through the lncRNA Six3os1/miR-511-3p/AKT3 Molecular Axis
To explore the effect and mechanism of moxibustion at acupoints of the governor vessel on lncRNA Six3os1 in amyloid precursor protein/presenilin1 (APP/PS1) double-transgenic Alzheimer's disease (AD) mice.
Twenty-four specific pathogen-free and APP/PS1 double-transgenic male mice were randomly allocated into the AD model and moxibustion groups, with 12 cases in each group. Twelve syngeneic C57BL/6J mice were selected as the control group. Mice in the moxibustion group received aconite cake-separated moxibustion at the Baihui acupoint. Suspension moxibustion was applied at Fengfu and Dazhui for 15 minutes each day. All treatments were conducted over two weeks. Control and AD model mice were routinely fed without any intervention. Behavioral observation tests were conducted before and after the intervention. The autophagosome in the hippocampus was observed using transmission electron microscopy. Immunohistochemistry was performed to detect Aβ1-42 expression. LC3B and P62 expressions were evaluated by immunofluorescence. The expression levels of the lncRNAs Six3os1, miR-511-3p, and AKT3 were detected by qRT-PCR. The differential expression of PI-3K, AKT3, mTOR, LC3B-II/I, and P62 proteins in the hippocampus was detected by western blot. The dual-luciferase assay was undertaken to examine the targeting relationships of the lncRNAs Six3os1, miR-511-3p, and AKT3.
Compared with the control group, the AD model showed higher escape latency in the Morris Water Maze and reduced autophagic vacuoles in the cytoplasm of hippocampal neurons (both p < 0.01). Compared with the control group, the AD model showed higher expression of Aβ1-42, the lncRNAs Six3os1, PI-3K, mTOR, P62, and AKT3 protein (all p < 0.01); but lower mir-511-3p and LC3B (both p < 0.01). Compared with the AD model group, the moxibustion group had a shorter escape latency, more autophagic bubbles in the hippocampus, and lower expression of positive Aβ1-42, the lncRNAs Six3os1, PI-3K, mTOR, P62, and AKT3 protein (all p < 0.01). In contrast, the levels of miR-511-3p and LC3B proteins were considerably increased in the moxibustion group compared to the AD model group (both p < 0.01). Based on the dual-luciferase assay, there was a targeting link among the lncRNAs Six3os1, miR-511-3p, and AKT3.
Moxibustion at acupoints of the governor vessel can suppress the lncRNA Six3os1 expression, promote cell autophagy, accelerate Aβ1-42 clearance and alleviate cognitive dysfunction of AD mediated by the PI3K/AKT/mTOR signaling pathway through the lncRNA Six3os1/miR-511-3p/AKT3 axis.
Alzheimer's disease (AD) is a multifactorial and irreversible neurodegenerative disease that accounts for 50–70% of dementia cases [1]. Pharmacological therapies used to treat AD can relieve symptoms but do not reverse disease progression [2]. The failure of a range of clinical agents has led some to question the amyloid-β (Aβ) pathophysiological hypothesis of AD [3]. However, anti-Aβ drugs such as aducanumab and ALZ-801 have shown encouraging outcomes in phase 3 trials and have confirmed amyloid as a viable therapeutic target [4, 5]. Studies have established that dysfunctional autophagy is involved in neurodegenerative disease and that its induction can accelerate the clearance of abnormally accumulated Aβ, thereby improving cognitive function in AD [6]. Furthermore, an increasing number of studies have revealed that autophagy is implicated in the etiology and progression of AD [7, 8]. Therefore, the identification of key regulators of autophagy is essential for AD treatment. LncRNAs are noncoding RNAs > 200 nucleotides in length that can be widely distributed in the nucleus; they have emerged as critical regulators of numerous basic biological activities [9]. Studies have shown that lncRNAs can be represented as molecular sponges to target miRNAs and influence cell autophagy directly [10]. Xu et al. found that overexpression of the lncRNA H19 affects the normal activity of the PI3K/Akt/mTOR signaling pathway, impairing impair cell survival and increasing cell autophagy. Our earlier study found that moxibustion effectively treated AD by improving patient cognitive function and daily tasks. Underlying these clinical effects, moxibustion may act by inhibiting PI3K/AKT/mTOR and P38 MAPK signaling pathways to enhance cell autophagy and accelerate Aβ clearance [11–13]. We examined gene expression in the hippocampal tissue of APP/PS1 double-transgenic mice by utilizing high-throughput sequencing technology. We aimed to determine the differential expression of lncRNAs and mRNAs before and after the moxibustion treatment. Functional enrichment analyses were also performed to enrich the PI3K/AKT/mTOR signaling pathway to construct a ceRNA regulation network and eventually screen out the crucial lncRNA Six3os1. Next, we evaluated the specific effects and mechanisms of moxibustion in modulating the PI3K/AKT/mTOR signaling pathway through lncRNA Six3os1 to provide reliable molecular markers and targets for the clinical diagnosis and treatment of AD.
Six-month-old APP/PS1 double transgenic and specific pathogen-free male AD mice were provided by Nanjing Junke Bioengineering Co., Ltd. [License: SCXK (Su) 2020-0009]. The average body weight was 28 ± 2 g. The animals were raised in a clean animal room at the Science Experimental Center of the Anhui University of Chinese Medicine. Each animal was kept in a separate cage clarified at 23 ± 2°C, 50 ± 5% humidity, and in a 12-hour light-dark cycle. Approval for the study was provided by the Anhui University of Chinese Medicine (NO: AHUCM-mouse-2021042). The Morris water maze spatial learning test was performed one week following adaptive feeding; animals who did not swim or exhibited significant differences in test scores from other mice were excluded from the experiment. The remaining 24 animals were randomly but evenly divided into the AD model and moxibustion groups. Twelve healthy wild-type C57BL/6J mice were simultaneously screened for the control group. The experiments were conducted according to the requirements of the Caring for Laboratory Animals guidelines issued by the Ministry of Science and Technology in 2006.
PI3K (ab86714, Abcam), AKT3 (bs-5146R, Bioss), mTOR (2972s, CST), LC3B (bs-2912R, Bioss), P62 (18420-1-AP, Triple Eagle), western removal buffer of primary antibody and second antibody (P0025, Beyotime), RIPA cell lysate (P0013B, Beyotime), ECL hypersensitive luminescence kit (34095, Thermo), goat anti-mouse IgG secondary antibody (ZB-2305, Zsbio), goat anti-rabbit IgG secondary antibody (ZB-2301, Zsbio), goat anti-rabbit IgG (FITC) (B029, Ebiogo), sheep serum block (B010, Ebiogo), anti-fluorescence quench blocking agent (containing DAPI) (B024, Ebiogo), TRIzol (15596026, Life Technologies), and hematoxylin (BA-4041, BaSO). EPS 300 electrophoresis instrument (Tanon), VE-180 electrophoresis tank (Tanon), JW-3021HR high-speed refrigerated centrifuge with 6.8cm centrifugal radius (Anhui Jiawen Instrument Equipment), JEM1400 flash transmission electron microscope (Jieou Lu, Beijing), PIKOREAL 96 fluorescence quantitative PCR instrument (Thermo), OD1000+ ultra-micro spectrophotometer (Nanjing Wuyi), CX41 microscope (Olympus), RM2016 Leica microtome (Leica), Pannoramic MIDI digital section scanner (3DHISTECH), and a 1319A digital thermometric indicator(Shanghai TES).
The acupoints Baihui, Dazhui, and Fengfu were selected according to the Nomenclature and Location of Acupuncture Points for Laboratory Animals [14]. Animals were shaved at the intervention site and acupoints were marked. Several aconite cakes with a diameter of ∼1 cm and a thickness of 4–6 mm were prepared in advance and multiple small holes were made on their surface with a toothpick. Mice were secured in a restraint with the head and neck exposed. In the moxibustion-treated group, the moxibustion bar was lit and the lit end was placed on the aconite cake, which was then positioned at Baihui for 15 minutes every day. Dazhui and Fengfu were treated with suspension moxibustion for 15 minutes per day at a distance of 2–3 cm from the skin. To control for radiant heat, one end of a temperature probe was affixed next to the Fengfu acupoint and the moxibustion temperature was maintained at 44–46°C (the same protocol was followed at Dazhui acupoints). The control and AD model groups were routinely housed under comparable conditions but received no intervention. All mouse groups were treated once daily for two weeks. Trained professionals from the Anhui Acupuncture Hospital performed the procedures.
The water maze test was performed before and after the intervention. The laboratory was sheltered from light, and the room temperature was maintained at 24–25°C with the water temperature at 24 ± 2°C. Mice were continuously trained for four days before data collection. On the first day, the mice were placed in the water for two minutes to adapt to the surroundings. Each mouse received two training sessions, separated by 4 hours, per day from the second day. Each time, they were introduced to the water from a different point. The latency time (from placement until arrival at the platform) was recorded. If the mouse did not find the platform within 2 minutes, the latency was recorded as 2 minutes. The mice were permitted to stay on the platform for 30 seconds whether or not they found the platform within 2 min. Following the training, the mice were tested to establish a baseline and again after the treatment.
Brains were harvested from six mice and the hippocampi were isolated; harvesting was performed on an ice plate. The hippocampal CA1 region was excised and stored in an electron microscopy solution for subsequent electron microscopy analysis; the remaining hippocampal tissues were preserved at −80°C for gene and protein quantification. Several isolated fresh sections (∼1 mm3) of the hippocampal CA1 region were rinsed, fixed, dehydrated, and embedded for ultrathin sectioning (60 nm thickness). Three sections were taken from the mice of each group. The morphology of neuronal cell structures, autophagic vacuoles, autolysosomes, and lysosomes was examined and photographed using the JEM1400 transmission electron microscope after double staining (lead and uranium staining). Three to five fields were randomly selected from each section for analysis.
Three mice from each group were randomly selected and anesthetized by intraperitoneal injection with 0.3% pentobarbital sodium (30 mg/kg). The brains were fixed after perfusion with 4% paraformaldehyde. Sections of 4 μm thickness were made from prepared paraffin blocks, then deparaffinized and hydrated for antigen retrieval. The sections were then rinsed ×3 in phosphate-buffered saline ×5 min, blocked, and incubated in Aβ (1 : 1000) primary antibody overnight at 4°C. The secondary antibody (1 : 5000) was added dropwise to the sections for incubation at 37°C for 40 minutes before rinsing. DAB was added dropwise to the sections and the chromogenic time was adjusted under the microscope. The sections were washed following appropriate color development. The sections were rewashed after hematoxylin counterstaining for two to five minutes, after which the sections were washed after blueing with lithium carbonate solution for 30 seconds. After dehydration and xylene-induced tissue transparency, neutral gum was then added and the sections were coverslipped for imaging. The images were observed and captured under a high-power (×400) microscope to determine the mean absorbance values of the positive staining.
–80°C frozen hippocampal tissues weighing 50–60 mg were weighed, chopped, and total RNA was extracted using TRIzol-chloroform-isopropanol-ethanol. According to the instructions, RNA was reverse transcribed into cDNA using a PrimeScript™ RT reagent Kit with gDNA Eraser (TaKaRa). The PCR reaction system consisted of 5 μL of 2 × SYBR Green mixture, 1 μL of each upstream and downstream primers, 1 μL cDNA, and 2 μL of nuclease (10 μL of the final mixture). The PCR parameters for lncRNAs Six3os1, miR-511-3p, and AKT3 were as follows: 95°C for 1 minute, 95°C for 20 seconds, and 60°C for 1 minute. The fluorescence signals were acquired over 40 cycles with three technical replicates per sample. β-actin was used as the internal reference gene and the results were analyzed by using the 2−ΔΔCt method after appropriate quality checking (e.g. melt curves). Primer sequences are shown in Table 1.
Three mice in each group were randomly selected and their brains were harvested and cut into two along the sagittal axis. The fresh brain tissues were placed on a frozen plate and embedded in OCT until the tissues were covered entirely, following which the tissues were stored at −80°C refrigerators until frozen. The brains were sectioned and rinsed. Antigen retrieval was done in a pressure-cooker then goat serum blocking solution was added dropwise and incubated at 37°C. The primary antibody (LC3B/P62) was added dropwise and incubated at 37°C for 60 minutes. The secondary antibody (goat anti-rabbit; 1 : 400) was added dropwise, capped, and incubated at 37°C in the dark for 30 minutes. Then, an anti-fluorescent quench blocking agent was added (containing DAPI) and the fluorescent sections were scanned by using Pannoramic MIDI.
Approximately 100 mg of hippocampal tissue, frozen at −80°C, was lysed in 1 ml of RIPA cell lysis buffer + 1 mM PMSF protease inhibitor. The samples were centrifuged at 1,200 RCF for 10 min at 4°C, and the supernatants were collected for protein extraction. The proteins were tested in seven consecutive steps including denaturation, loading electrophoresis, transmembrane, blocking with 5 percent fat-free milk powder for 2 hours at room temperature, and incubation with primary antibodies (PI-3K, mTOR, and LC3B-II/I at 1 : 1000; AKT3 at 1 : 500) overnight at 4°C. The next day the membranes were washed and incubated with secondary antibodies (goat anti-mouse -IgG and goat anti-rabbit IgG at 1 : 1000) at room temperature for 1.2 hours. The ECL luminescence kit was used for detection on film with appropriate exposure and film development. Image J software was used to analyze film strips. GAPDH was used as the reference protein.
We used the starbase database (https://starbase.sysu.edu.cn/) to predict binding sites and construct dual-luciferase reporter vectors, including Six3os1-wt, Six3os1-mut, AKT3-wt, and AKT3-mut. 293T cells and target plasmids previously prepared for transfection were dispensed into 96-well plates at 50–70% confluence. The target plasmid was fully mixed with 5 pmol of miR-511-3p (Negative Control, NC) at room temperature (solution A), following which 10 μL DMEM was mixed thoroughly with 0.3 μL of transfection reagent (HANBIO product with a concentration of 0.8 mg/mL) at room temperature for 5 min (solution B). Solution A was thoroughly mixed with solution B at room temperature for 20 min. The cell media were refreshed before transfection, following which the transfection mixture was added to the mix and incubated at 37°C with 5% CO2. After six hours, the media were exchanged and the cells were incubated for 48 hours. Luciferase activity was assayed by following the instructions of the Promega Dual-Luciferase assay kit.
SPSS version 23.0 was used for all statistical analyses. Data were expressed as mean ± standard deviation (mean ± SD). One-way analysis of variance was used to test differences between multiple groups and the least significant difference was used to examine group differences. Data that were non-normally distributed or showed signs of heteroscedasticity were analyzed by using the Kruskal-Wallis H test. Statistical significance was determined by p < 0.05.
As shown in Figure 1, before treatment, the escape latency was markedly longer in the AD model group of the double transgenic mice compared with the control mice (p < 0.01). There was no significant difference between the AD model and moxibustion groups (p > 0.05). After the intervention, the escape latency of AD mice in the model group was longer compared with the control group (p < 0.01). The escape latency was substantially shorter in the moxibustion group than in the AD model group (p < 0.01).
tAs shown in Figure 2, organelles were well arranged with clear and complete structures. More autophagic vacuoles and autophagosomes were observed in the hippocampal cytoplasm of the control mice. Deformed and atrophied organelles were detected in the AD model group and the autophagic vacuoles were significantly reduced. Organelles were abundant and autophagic vacuoles and autophagosomes were increased in the moxibustion group compared with the AD model group.
As shown in Figure 3, Aβ1–42 protein content was markedly increased in the AD model group compared with the control group, as determined by immunohistochemistry (p < 0.01). Aβ1–42 content was significantly decreased in the moxibustion group compared to the AD model group (p < 0.01).
As shown in Figure 4, compared with the control group, in the AD model the expression of the lncRNAs Six3os1 and AKT3 was increased while miR-511-3p expression was lower, as determined by qRT-PCR (both p < 0.01). In contrast, compared to the AD model group, in the moxibustion group, the expression of the lncRNAs Six3os1 and AKT3 was decreased and miR-511-3p expression was significantly increased (both p < 0.01).
As shown in Figure 5, compared with the control group, in the AD model the LC3B-II/I ratio was markedly decreased, while P62 was significantly increased, as determined via WB (both p < 0.05). Compared with the model group, in the moxibustion group, the LC3B-II/I ratio was greatly increased, while P62 expression was increased (both p < 0.05). As shown in Figure 6, the fluorescent LC3B signal was attenuated in the AD model and moxibustion groups compared with the control group. At the same time, P62 was significantly enhanced in the AD model group (both p < 0.01). Compared with the model group, in the moxibustion group, LC3B fluorescence was significantly enhanced and P62 was greatly attenuated (both p < 0.01).
As shown in Figure 7, the expressions of PI3K, AKT3, and mTOR proteins were significantly increased in the model group compared to the control group, as demonstrated by WB (all p < 0.01). Conversely, compared with the model group, the moxibustion group showed lower expression of PI3K, AKT3, and mTOR proteins (all p < 0.01).
As shown in Figure 8, starbase binding sites predicted complementary binding sites for the miR-511-3p and the 3′UTR of lncRNA-Six3os and AKT and constructed the mutation sites of lncRNA-Six3os-3′UTR and AKT-3′UTR. As shown in Figure 9, compared with the NC group, the miR-511-3p significantly downregulated the luciferase expression of lncRNA-Six3os-3′UTR-wt (p < 0.01), while miR-511-3p failed to downregulate the luciferase expression of lncRNA-Six3os-3'UTR-mut after the mutation (p > 0.05). As shown in Figure 10, compared with the NC group, the miR-511-3p significantly downregulated the luciferase expression of AKT-3'UTR-wt (p < 0.01), while miR-511-3p failed to downregulate the luciferase expression of AKT-3′UTR-mut after the mutation (p > 0.05).
AD is a type of dementia. In Chinese Medicine, several factors are recognized in older individuals as being pathogenic for AD including dysfunction of zang-fu organs, marrow sea deficiency, promotion of kidney Yang, and poor function of warmth. Professor CAI Shengchao, a renowned traditional Chinese physician posited the hypothesis underlying our study; that is, that the governor vessel connects to brain function, inline with the heart and kidney, and passes through the Ren Channel, where all are organically connected with the function of the house of the soul. Therefore, it was proposed that dementia treatment should start from the shen-brain-governor vessel-kidney-Ren Channel axis [15]. In our experiment, we selected the three acupoints Baihui, Fengfu, and Dahui from the governor vessel, with the intent of thriving the governor vessel, filling the marrow sea, resolving the phlegm, and opening the brain orifices. The pathogenesis of AD is complicated and includes the abnormal accumulation of Aβ, Tau protein hyperphosphorylation, and neuroinflammation [16, 17]. Furthermore, the deposition of amyloid-β produces further pathogenic cascades that underlie the primary mechanisms for AD etiology and progress [18]. Gene mutations in amyloid precursor protein (APP), presenilin-1 (PS-1), and presenilin-2 (PS-2) can mediate the Aβ hypersecretion and eventually deposit to form senile plaques, which trigger neuronal damage and death [19]. In our study, we observed that in the AD model, the escape latency in the Morris Water Maze was significantly prolonged and Aβ1–42 expression was significantly higher than in the control group. The moxibustion intervention reduced Aβ1–42 deposition in AD mice and improved spatial memory. Autophagy is a primary metabolic process in eukaryotic cells that utilize lysosomes to degrade damaged organelles and aberrant proteins to maintain cell homeostasis [20]. As a landmark protein of autophagy, LC3B is involved in forming early autophagic vacuoles and can reflect the extent of autophagy [21]. The autophagic substrate P62 is continuously consumed during autophagy formation and reflects autophagic activity [22]. It has been demonstrated that activation of autophagy can reduce Aβ levels [23]. For example, Chen et al. reported several biochemical alterations that can enhance autophagic activity, including downregulation of miR-331-3p and miR-9-5p which markedly attenuated the accumulation of Aβ in mice with early AD [24]. Wu et al. reported that SIRT5 overexpression can ameliorate AD progression in vitro and in vivo by activating autophagic mechanisms to clear Aβ protein [25]. AKT, as a serine/threonine protein kinase, is a central effector molecule of the phosphoinositide 3-kinases/protein kinase B (PI3K/AKT) signaling pathway with its location at its hub [26]. AKT can influence downstream mTOR signaling, thereby contributing to the PI3K/AKT/mTOR pathway. The PI3K/AKT/mTOR signaling pathway is one of the critical pathways that regulate autophagy; inhibition of this pathway can activate autophagy in the AD mouse model [27]. Here we found that AD mice exhibited reduced autophagic vesicles and autophagosomes, indicating defective autophagy and promotion of Aβ deposition. The expression of PI3K, AKT3, mTOR, and P62 protein was decreased after moxibustion compared with the AD model group. In contrast, the autophagy marker protein LC3B was increased, indicating that moxibustion might inhibit the PI3K/KT/mTOR signaling pathway to promote autophagy and reduce Aβ deposition; this, in turn, improved the cognitive function of the treated mice. This outcome was consistent with prior research [11]. Several studies have demonstrated that lncRNA is involved in essential physiological processes such as hippocampal development, neuronal differentiation, and brain aging in mice [28]. The previous sequencing had screened out Six3os1, a critical differential gene lncRNA with high expression in the AD mouse hippocampus. It is known that Six3os1 can operate as a molecular scaffold to recruit histone-modifying enzymes to homeodomain factor Six3 target genes, which can regulate the activity of the related protein-coding genes and play a vital role in controlling neurodevelopment [29]. Geniposide might upregulate Six3os1 and attenuate the depressive-like-induced oxidative stress in mice through the miR-511-3p/Fezf1/AKT axis [30]. Combined with the ceRNA hypothesis, miR-511-3p was inferred as the target gene of lncRNAs Six3os1 and AKT. The software predicted its binding site and we validated it using a dual-luciferase reporter system. We showed that miR-511-3p strongly suppresses the expression of luciferin of wild-type lncRNAs Six3os1 and AKT, confirming that miR-511-3p is a target gene of the lncRNAs Six3os1 and AKT. As expected, these results were further corroborated by qRT-PCR with high expression of lncRNAs Six3os1 and AKT and low expression of miR-511-3p in the AD model group. Moxibustion lowered the expression of the lncRNAs Six3os1 and AKT and elevated miR-511-3p.
In summary, we speculated that moxibustion can regulate the lncRNA Six3os1 and inhibit the PI3K/Akt/mTOR signaling pathway via miR-511-3, thus modulating downstream target proteins to promote cell autophagy. Those effects contributed to the acceleration of Aβ1–42 clearance in the hippocampus, reduced neuronal damage, and alleviated cognitive dysfunction. These data provide support for the lncRNA Six3os1 as a molecular marker and target for the diagnosis and treatment of AD [31]. | true | true | true |
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PMC9556215 | Yupeng Liu,Tao Li,Chunlei Peng,Qinghua Mao,Biao Shen,Minxin Shi,Haimin Lu,Ting Xiao,Aimin Yang,Chun Cheng | Knockdown of Long Noncoding RNA LINC00240 Inhibits Esophageal Cancer Progression by Regulating miR-26a-5p | 05-10-2022 | Background Esophageal cancer is the most prevalent digestive system tumor. Due to a lack of characteristic symptoms and early diagnosis, a confirmed esophageal cancer is typically detected at a progressively harmful stage. Therefore, it is critical to investigate the molecular mechanisms governing the formation and progression of esophageal cancer in order to identify new treatment targets for esophageal cancer early detection. Methods We first screened the differentially expressed gene LINC00240 in the TCGA database. Multivariate analysis and Cox regression were performed, and a nomogram was constructed for internal validation. The correlation between LINC00240 and immune cells was analyzed using the TIMER database. The possible mechanism of action was explored through GSEA enrichment analysis. Then, in 43 esophageal cancer tissues, paracancour tissues, and cell lines, the LINC00240 expression was found. Transwell assays, CCK-8, and clone formation assays were utilized to assess the impact of LINC00240 on the metastasis of esophageal cancer cells. The binding activity of LINC00240 to downstream miRNAs was assessed using the luciferase reporter gene. Results TCGA database showed that LINC00240 expression was increased in cancer tissues compared to adjacent tissues. The C-index of the nomogram is 0.712 (0.666–0.758), and the prediction model has good accuracy. According to the TIMER database, the LINC00240 expression is linked to immune infiltration and may be crucial in encouraging the immune escape of tumor cells. Gene enrichment analysis depicts that LINC00240 could influence the biological events of esophageal cancer by taking part in pathways such as affecting the cell cycle. LINC00240 expression was substantially greater in the plasma of esophageal cancer patients (3.94 ± 1.55) than in the normal control group (2.13 ± 0.89). Plasma expression of LINC00240 was linked to the degree of differentiation (P=0.0345) and TNM stage (P=0.0409). Knocked down LINC00240 inhibited esophageal cancer cells proliferation, lone formation, and invasion. LINC00240 might bind itself to miR-26a-5p and influence its expression. MiR-26a-5p inhibitor can dramatically limit the ability of LINC00240 knockdown on plate colony formation and relocation of esophageal cancerous cells was demonstrated in colony formation and migration experiments. Conclusion LINC00240 expression is elevated in esophageal cancerous tissues, and knocking down LINC00240 decreases esophageal cancer cell proliferation, clone formation, invasion, and migration via miR-26a-5p. As a result, LINC00240 could be a novel target for esophageal cancer patients' early diagnosis and treatment. | Knockdown of Long Noncoding RNA LINC00240 Inhibits Esophageal Cancer Progression by Regulating miR-26a-5p
Esophageal cancer is the most prevalent digestive system tumor. Due to a lack of characteristic symptoms and early diagnosis, a confirmed esophageal cancer is typically detected at a progressively harmful stage. Therefore, it is critical to investigate the molecular mechanisms governing the formation and progression of esophageal cancer in order to identify new treatment targets for esophageal cancer early detection.
We first screened the differentially expressed gene LINC00240 in the TCGA database. Multivariate analysis and Cox regression were performed, and a nomogram was constructed for internal validation. The correlation between LINC00240 and immune cells was analyzed using the TIMER database. The possible mechanism of action was explored through GSEA enrichment analysis. Then, in 43 esophageal cancer tissues, paracancour tissues, and cell lines, the LINC00240 expression was found. Transwell assays, CCK-8, and clone formation assays were utilized to assess the impact of LINC00240 on the metastasis of esophageal cancer cells. The binding activity of LINC00240 to downstream miRNAs was assessed using the luciferase reporter gene.
TCGA database showed that LINC00240 expression was increased in cancer tissues compared to adjacent tissues. The C-index of the nomogram is 0.712 (0.666–0.758), and the prediction model has good accuracy. According to the TIMER database, the LINC00240 expression is linked to immune infiltration and may be crucial in encouraging the immune escape of tumor cells. Gene enrichment analysis depicts that LINC00240 could influence the biological events of esophageal cancer by taking part in pathways such as affecting the cell cycle. LINC00240 expression was substantially greater in the plasma of esophageal cancer patients (3.94 ± 1.55) than in the normal control group (2.13 ± 0.89). Plasma expression of LINC00240 was linked to the degree of differentiation (P=0.0345) and TNM stage (P=0.0409). Knocked down LINC00240 inhibited esophageal cancer cells proliferation, lone formation, and invasion. LINC00240 might bind itself to miR-26a-5p and influence its expression. MiR-26a-5p inhibitor can dramatically limit the ability of LINC00240 knockdown on plate colony formation and relocation of esophageal cancerous cells was demonstrated in colony formation and migration experiments.
LINC00240 expression is elevated in esophageal cancerous tissues, and knocking down LINC00240 decreases esophageal cancer cell proliferation, clone formation, invasion, and migration via miR-26a-5p. As a result, LINC00240 could be a novel target for esophageal cancer patients' early diagnosis and treatment.
Esophageal cancer (EC) is the world's sixth greatest reason behind deaths related to cancer and the eighth most common type of cancer. Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EA) are among the two most common forms of EC [1]. Considering the advancements in the pharmacological therapies for treating EC, tens of thousands of people still die from esophageal cancer every year worldwide, and the incidence of esophageal cancer remains high in China [2, 3]. The main treatment method is surgery along with radiation and chemotherapy for esophageal cancer at present, yet the limitations of surgical treatment and many adverse reactions of radiotherapy and chemotherapy combined with the fact that most patients are diagnosed in an advance stage result in a low survival rate and physical and mental burden of patients [4, 5]. Therefore, finding new early diagnostic biomarkers or therapeutic targets is one of the main goals of EC research to prolong the survival of patients. lncRNAs (long noncoding RNAs) are a form of RNA with over 200 nucleotides and occupy at least 80% of the human genome but do not code for proteins [6]. According to growing data, many biological functions, including proliferation, metastasis, cell cycle progression, cell development, and apoptosis, are thought to be influenced by lncRNAs [7, 8]. In the process of gene modification, lncRNAs act as transcriptional regulators, posttranscriptional processing factors, chromatin remodelers, and splicing regulators [9]. In addition, lncRNAs take part in the detection and therapy of cancers and in promoting or inhibiting cancer development. The use of lncRNA as a ceRNA to control the progression of esophageal cancer has been a hot topic in the study, and it could be a possible oncogene or tumor suppressor gene involved in the biological process of the disease; for example, lncRNA DNM3OS secreted by cancer-associated fibroblasts increases radioresistance by modulating DNA destruction in ESCC [10]. lncRNA EIF3J-AS1 increases AKT1 mRNA levels through miR-373-3p, thus exhibiting oncogenic function in EC, and can serve as a possible treatment target and prognostic biomarker [11]. Therefore, in-depth exploration of the functions or regulatory pathways of lncRNAs in esophageal cancer will provide a theoretical basis and possible targets for timely detection and treatment of esophageal cancer. LINC00240 is a new class of lncRNAs identified in recent years and is responsible for manifesting various tumors, such as gastric, liver, and cervical cancer [12–14]. But the function and LINC00240 molecular mechanism in tumor tissue, especially in esophageal cancer tissue, are still unclear. Our study mainly researched the expression of LINC00240 and its function in the biological events of esophageal cancer patients. In addition, bioinformatics analysis and in vitro experiments were performed to study the effects of LINC00240 on tumor cell behavior and its underlying mechanisms.
The TCGA database was employed for data analysis to investigate the LINC00240 expression in esophageal cancer.
To personalize the predicted survival probabilities at 1, 3, and 5 years, nomograms were constructed as per the outcomes of the multivariate analysis. The RMS R package was employed to construct nomograms. The discriminative power of the nomogram was assessed by employing the Concordance Index (C-index), which was calculated using the bootstrapping technique with 1000 resampling. Additionally, the C-index was utilized to compare the predictive accuracy of nomograms and specific prognostic factors.
The correlation between the LINC00240 expression and various immune cells in esophageal cancer was illustrated by constructing a bar graph from the TIMER database.
Functional analysis was performed online using Metascape. Add differential genes to Metascape for functional analysis.
Nantong Tumor Hospital's ethics committee accepted this study, and all participants signed informed consent forms (NO. 2022-A 05). A total of 43 preoperative plasma samples from patients with esophageal cancer in our hospital from January 2019 to June 2021 were collected, and 43 healthy control group plasma samples were also collected. In addition, a total of 43 pairs of postoperative tumor tissue and paracancours normal tissue samples were collected. Patients were in the 32 to 72 years old age range, with an average of 52.5 ± 8.12 years, and included 24 males and 19 females. All patients' tissue samples were pathologically diagnosed as esophageal cancer, with no antitumor treatment such as radiotherapy or chemotherapy before surgery. The paracancerous tissue is the normal tissue located 5 cm from the tumor tissue. The tissue obtained by surgical resection is washed with normal saline and immediately placed in liquid nitrogen for preservation. After adding RNA buffer, it was frozen via liquid nitrogen for later use, and total RNA in tissues was then extracted.
Esophageal cancer (EC) cell lines (OE-33, KYSE-150, TE-10, and Eca-109) and human normal esophageal epithelial cells (HEEC) and KYSE-30 were bought from Shanghai Cell Center, Chinese Academy of Sciences, and experimentally preserved. All (EC) cells were grown in RPMI 1640 media (ScienCell, Carlsbad, CA, USA) with 10% fetal bovine serum (FBS) (Gibco, Carlsbad, CA, USA) and 100 units/mL of penicillin and 100 milligrams of streptomycin. The cells were cultivated in a 5% CO2 incubator at 37°C, with the media being replaced every two days.
Trizol technique was utilized to isolate total RNA (Invitrogen, USA), and total RNA purity was determined using the Nanodrop 2000 and identified by nucleic acid electrophoresis. To avoid RNase contamination, all instruments were treated with de-RNase before the experiment, and the mortar was precooled with liquid nitrogen. The primers of LINC00240 and internal reference GAPDH are referenced in [14] and from GenePharma (Shanghai, China). The reaction was carried out by utilizing fluorescence quantitative PCR equipment with the reaction conditions listed below: predenaturation at 95°C for 15 seconds, followed by 45 cycles of denaturation at 95.0°C for 5 seconds, annealing, and extension at 60.0°C for 30 seconds. qRT-PCR was carried out with Bio-Rad iQ5 Real-Time PCR System SYBR Green kit (TaKaRa, Tokyo, Japan). The 2−ΔΔCt method was employed for analyzing the expression difference between tumor tissue and paracancours normal tissue, where Ct was the number of amplification cycles required for the fluorescence intensity to reach the threshold, and the corresponding Ct value was calculated, ΔCt = CtLINC00240 − CtGAPDH, ΔΔCt = ΔCt (normal tissue) − Ct (tumor tissue), and then the differences in the relative mRNA expression of each group were obtained.
In this study, the interfering sequence targeting LINC00240 was used as a reference [14]. The sequence was synthesized by Shanghai Sangong (Shanghai, China) and constructed into a lentiviral vector for subsequent transfection. Cells were digested with trypsin, 10 MOI of the virus was added to the medium, 400 μl of serum-free medium Opti-MEM (Invitrogen, USA) was added in all the wells, and 100 microliters of the transfection solution prepared above was added, then the cells were incubated in 5% CO2 solution at 37°C and cultured in a carbon dioxide incubator. After culturing for 4–6 hours, carefully aspirate the culture medium with a pipette, and replace it with a new medium before continuing the culture.
After the transfection of esophageal cancer cells to all the groups, cells were counted after being cultured for 48 hours. The 96-well plates were transfected with cells at the density of 5 × 103 cells per well. Every group had three duplicate wells, and only RPIM1640 was added to the zero-adjusted well. The medium was gently shaken and mixed and then cultured at 37°C in a 5% CO2 incubator. The CCK-8 (Beyotime, Beijing, China) was utilized to determine the cell viability at 0 d, 1 d, 2 d, and 3 d after culture. The detection process was executed completely as per the kit's accompanying manual: 10 μl of CCK8 detection reagent was poured into all the wells along the well walls, and cells were incubated for 2 hours in a CO2 incubator. The OD value of all the wells was measured at 450 nm utilizing a microplate reader. The maximum and minimum values were removed, and the average of measurement results was utilized to build the growth curve.
After the transfection of esophageal cancer cells to all the groups, cells were counted after being cultured for 48 hours. About 800 cells in each group were transferred to a Petri dish and cultured in a carbon dioxide incubator. Every 2–3 days, the cell progression was monitored after changing the media. After culturing for about 14 days, the culture dish was taken out and twice washed in PBS buffer, and cells were fixed by adding 4% paraformaldehyde (Beyotime, Beijing, China) for 0.5 hours. The formaldehyde was removed by suction and washed twice with PBS buffer, and 4 ml of crystal violet staining solution (Beyotime, Beijing, China) was added for staining overnight at room temperature. Wash with PBS buffer 3–5 times after staining, and then collect photos of the formation of spots after drying. The number of clones is the cell mass of ≥50 cells, and the experiment is carried out three times.
Cell migration assay: take the cells in a good growth state, digest them with trypsin, and adjust the density to 1 × 106 cells/ml after cell counting. 500 μl of culture media (having 20% FBS) was added to the Transwell chamber (8 μm pore sizes, Corning, New York, USA), and 100 μl of the cell suspension was injected into the upper Transwell chamber in a carbon dioxide constant temperature incubator for cultivation. Observation after culturing for 36 hours, aspirate the liquid that remains in the upper chamber, wash with PBS buffer three times, and clean the cells that have not been transferred in the upper chamber; add 600 μl methanol to the cells transferred to the lower chamber for 30 minutes, and add 1% Crystal violet solution (Beyotime, Beijing, China) for staining. The cells were washed thrice in PBS buffer after staining, and five visual fields were picked at random for inspection under a light microscope, with the number of cells counted and statistically evaluated. Cell invasion assay: dilute Matrigel gel (BD Biosciences, Bedford, MA) with serum-free medium RPIM-1640 at a 1 : 8 ratio, and cover the diluted gel into the inner base of the Transwell's upper chamber. Cells in a good growth state were taken, and the cell density was adjusted to 1 × 106 cells/ml after cell counting. Add 500 μl of medium (having 20% FBS) to the Transwell chamber, and inoculate 100 μl of the cell suspension into the upper chamber. Avoid the formation of air bubbles during the procedure and make sure the cells are dispersed equally. Incubate in a carbon dioxide incubator at a steady temperature. After 36 hours of culture, observations are made, and data is processed and analyzed according to the migration experimental technique.
To observe if the miR-26a-5p has targeted binding to the LINC00240 gene, we combined the luciferase reporter gene with 3′UTR of the wild-type LINC00240 and mutant LINC00240 genes and then combined miR-26a-5p with the 3′UTR of LINC00240 gene. Plasmids carrying the LINC00240 target segment were cotransfected into cells and cultured overnight in a carbon dioxide incubator. The Dual-Luciferase Reporter Assay System was employed to assess luciferase activity in cotransfected cells. The specific detection steps are as follows: discard the old cells in each well. The medium was washed three times with PBS buffer, 100 μl of PLB (Passive Lysis Buffer) was added, and the cell lysate was collected after gently shaking to mix. Then 20 μl lysate was added to the luminescent plate and detected with a GloMax bioluminescence detector. The measurement interval was set to 2 s and the measurement time was set to 10 s. Then 100 μl of LAR I was added, the value was read for 2 s after rapid mixing, and the activity of hLuc luciferase was measured. The reporter gene cell lysate was used as a blank control group. Add 100 μl Stop &Glo® Reagent (Promega, USA), mix quickly, and read for 2 s to measure hRluc luciferase activity. Taking hLuc/hRluc luciferase activity as the relative activity, the activation degree of the target reporter gene was compared according to the obtained ratio.
SPSS 19.0 was employed to analyze the data; measurement data was represented as (mean ± standard deviation, ±s), and measurement data with a normal distribution were compared across groups using the t-test or (ANOVA) and nonparametric rank sum test. The chi-square test was employed to examine the enumeration data. A significant difference was set as P < 0.05.
We first performed a pan-cancer analysis through the TCGA database and observed that LINC00240 expression was elevated in most tumor tissues (Figure 1(a)). Further analysis revealed that LINC00240 expression was also elevated in esophageal cancer tumor tissues (Figure 1(b)). Constructing the ROC curve found that the AUC was 0.713, so LINC00240 also had a good prediction effect (Figure 1(c)).
For individually predicting the 1, 3, and 5-year survival probability of esophageal cancer patients, we constructed a nomogram based on the outcomes of multivariate analysis in the TCGA database. The nomogram C-index was 0.712 (0.666–0.758), which predicted the model has good prediction accuracy (Figure 2).
A bar graph was constructed showing the correlation between the LINC00240 expression and various immune cells in esophageal cancer using the TIMER database. A significant link between the LINC00240 expression and most of the infiltrating immune cells was observed, including a positive correlation with NK cells, Tcm, Th2 cells, NK CD56dim cells, etc. It was also observed that Mast cells, DC cells, B cells, and neutrophils were negatively correlated (Figure 3(a)). To further evaluate the influence of LINC00240 on the tumor microenvironment (TME), the correlation between the LINC00240 and specific immune cells was analyzed, and the outcomes revealed that different LINC00240 expressions correlated with the level of immune cell infiltration in most tumors (Figure 3(b)). These findings further support that LINC00240 expression could be considerably associated with immune infiltration and indicate that LINC00240 might have a significant function in promoting immune escape of tumor cells in the esophageal cancer tumor microenvironment, which also serves as a stronger resource for basic research in the future.
Considering the diversity of current treatments for esophageal cancer and the selectivity of current targeted therapy drugs, the NCCN guidelines also point out that targeted therapy drugs for esophageal cancer include anti-EGFR monoclonal antibodies such as nimotuzumab, or, for EGFR gene mutations, such as gefitinib and erlotinib. Targeted drugs also include specific antibodies against PD-1, such as so-called immune checkpoint inhibitors such as camrelizumab or toripalizumab. Targeted drugs also include targeted drugs against tumor angiogenesis, such as bevacizumab or recombinant human endostatin injection, that is, Endostat and so on. We conducted a correlation study between LINC00240 and the target molecules of these targeted drugs, and we found that LINC00240 had a good correlation with EGFR, VEGFA, VEGFB, VEGFC, VEGFD, ERBB2, and MSI1 (Figure 4).
Data mining from the TCGA database was employed for identifying the positively or negatively correlated genes coexpressed with LINC00240. The graph illustrates the top 50 genes that are positively and negatively associated with LINC00240 in esophageal cancer (Figures 5(a) and 5(b)).
We performed functional analysis online using Metascape. It was observed that LINC00240 might influence the biological events of esophageal cancer through these five pathways: KEGG_APOPTOSIS; KEGG_VEGF_SIGNALING_PATHWAY; WP_EGFEGFR_SIGNALING_PATHWAY; REACTOME_CELL_CYCLE_CHECKPOINTS; REACTOME_G2_M_DNA_DAMAGE_CHECKPOINT. The results of these predictions also provide a reference for the basic experimental research we carry out below (Figure 6).
Fluorescence quantitative PCR was employed to determine LINC00240 expression in 43 esophageal cancer and paracancours tissues. In comparison to paracancours tissues, LINC00240 was shown to be strongly expressed in esophageal cancer tissues (Figure 7(a)). LINC00240 expression was detected by fluorescent quantitative PCR in esophageal cancer cell lines (OE-33, KYSE-150, KYSE-30, TE-10, and Eca-109) and human normal esophageal epithelial cells (HEEC). The results show that LINC00240 is strongly expressed in esophageal cancer cell lines, with the highest levels of expression in KYSE-30 and Eca-109 (Figure 7(b)). The above findings indicate that LINC00240 is remarkably expressed in esophageal cancer tissues and cell lines, implying that LINC00240 might play a vital regulatory part in the incidence and progression of esophageal cancer. An interfering sequence targeting LINC00240 was constructed and then transfected into KYSE-30 and Eca-109 cells, and fluorescence qPCR was employed to identify the transfection efficiency. The outcome revealed in comparison to the blank control group (shRNA-NC), transfection of lentiviral vector knocking down LINC00240 could dramatically reduce the LINC00240 expression levels in esophageal cancer KYSE-30 and Eca-109 cells (Figures 7(c) and 7(d)).
Fluorescence quantitative PCR was employed to determine LINC00240 expression levels in the preoperative plasma of esophageal cancer patients and a healthy control group. LINC00240 expression in plasma of esophageal cancer patients (3.94 ± 1.55) was found to be greater than that of normal controls (2.13 ± 0.89) (P < 0.01, Figure 8).
Statistical analysis of clinicopathological data of 43 patients with esophageal cancer and expression of LINC00240 in plasma indicate that the expression level of LINC00240 was correlated with the degree of differentiation (P=0.0345) and TNM stage (P=0.0409) of patients as well as gender, age, and whether there is a vascular invasion or not. The results show no correlation between LINC00240 expression level and the location of the primary tumor or the number of the primary tumor (P > 0.05) (Table 1).
The above-stated outcomes elucidated that LINC00240 expression was high in esophageal cancer cells. The highest-expression esophageal cancer cell lines KYSE-30 and Eca-109 were utilized to establish the knockdown LINC00240 model. The LINC00240 knockdown influence on the malignant ability of esophageal cancer cells KYSE-30 and Eca-10 was determined by the CCK-8 assay. The outcome demonstrated that LINC00240 knockdown considerably decreased the progression of esophageal cancer cells KYSE-30 and Eca-10 as to that of the blank control group (shRNA-NC) (Figure 9(a)). In addition, the outcomes of the plate clone formation assay reveal that LINC00240 knockdown markedly inhibited the clone formation property of esophageal cancer cells KYSE-30 and Eca-10 in comparison to the blank control group (shRNA-NC) (Figure 9(b)). The above outcome demonstrated that the LINC00240 knockdown could dramatically decrease the proliferation of esophageal cancer.
The above outcomes suggest that LINC00240 knockdown can greatly inhibit the progression of esophageal cancer cells. The Transwell assay was utilized to see if knocking out LINC00240 impacts the capability of esophageal cancer cells to metastasize. The number of cells migrating from the upper to lower chamber of Transwell on esophageal cancer cells KYSE-30 and Eca-10 reduced in the LINC00240 knockdown group as to that of the blank control group (shRNA-NC), indicating that the LINC00240 knockdown can considerably inhibit the migration ability of esophageal cancer cells (Figure 10). In order to further simulate the in vivo 3D environment, Matrigel gel was added to Tranwell. In comparison with the blank control group (shRNA-NC), the number of cells in LINC00240 knockdown esophageal cancer cells KYSE-30 and Eca-10 invading the lower chamber had decreased (Figure 10). The upper chamber results showed that LINC00240 knockdown could greatly decrease esophageal cancer metastases.
The foregoing findings suggest that knocking off LINC00240 stops esophageal cancer cells from proliferating, invading, and migrating. For an in-depth study of the molecular mechanisms of LINC00240 regulating esophageal cancer cell activity, online bioinformatics prediction software was employed to predict the binding site of LINC00240. The binding site of LINC00240 and miR-26a-5p were found (Figure 11(a)). Esophageal cancer cells were transfected with synthetic miR-26a-5p mimics (mimics). The results of real-time quantitative PCR revealed that when compared to the blank control group (miR-NC), transfection of miR-26a-5p mimics (miR-26a-5p mimics) could significantly upregulate miR-26a-5p in esophageal cancer cells expression levels (Figure 11(b)). The miR-26a-5p expression in LINC00240 knockdown esophageal cancer cell lines was determined by real-time PCR. When compared to the blank control (shRNA-NC) group, the results demonstrated that knockdown of LINC00240 could significantly promote the miR-26a-5p expression level (Figure 11(c)). The luciferase gene activity assay further showed that in the LINC00240 wild-type group, compared with the miR-NC group, the addition of miR-26a-5p mimics could substantially inhibit the luciferase activity, while in the LINC00240 mutant group, the luciferase activity was significantly inhibited. Compared with the miR-NC group, the addition of miR-26a-5p mimics had no significant change in luciferase activity (Figure 11(d)). The expression level of LINC00240 in esophageal cancer (ESCA) tissue was strongly inversely linked with the expression level of miR-26a-5p (r = 0.002, P < 0.001), according to StarBase V3.0 data analysis (Figure 11(e)). The foregoing observations indicate that LINC00240 regulates miR-26a-5p expression in esophageal cancer cells via competitive binding.
The above outcomes reveal that LINC00240 regulates the miR-26a-5p expression by competitive binding in esophageal cancer cells. To further investigate whether LINC00240 affects the malignant ability of esophageal cancer by modulating the miR-26a-5p expression, three experimental groups were set as follows: blank control group (shRNA-NC), knockdown LINC00240 group (shRNA-240), and knockdown LINC00240 (shRNA-240) + miR-26a-5p inhibitor group. The outcome of the plate clone formation assay showed that in comparison to the blank control group (shRNA-NC), knockdown of LINC00240 (shRNA-240) could dramatically decrease the number of plate clones formed in esophageal cancer cells. In contrast, knockdown of the LINC00240 (shRNA-240) + miR-26a-5p inhibitor group could significantly block the inhibitory effect of knockdown of LINC00240 (shRNA-240) on esophageal cancer cell plate clones (Figure 12(a)). Transwell experiments also demonstrated that in comparison to the blank control group (shRNA-NC), knockdown of LINC00240 (shRNA-240) could significantly inhibit the migration number of esophageal cancer cells. In contrast, LINC00240 (shRNA-240) + miR-26a-5p inhibitor group could significantly block the inhibitory effect of knockdown of LINC00240 (shRNA-240) on the migration ability of esophageal cancer cells (Figure 12(b)). The above results suggest that the knockdown of LINC00240 inhibits the proliferation and invasion of esophageal cancer by negatively regulating the expression of miR-26a-5p.
Esophageal cancer pathology has been linked to a number of elements, according to research. Long noncoding RNAs (lncRNAs) are suspected of having an essential part in the evolution of various forms of cancers in recent years, thanks to the advent of high-throughput gene sequencing technologies [15, 16]. lncRNAs have been involved in regulating physiological functions such as cell proliferation, differentiation, metastasis, and apoptosis, along with the incidence and development of numerous malignant tumors, according to previous research [7, 9]. For example, lncRNACASC9 encourages the metastases of ESCC (esophageal squamous cell carcinoma) by interacting with CREB-binding protein to upregulate LAMC2 expression [17]. Also, lncRNAs in peripheral blood can be used as efficient, noninvasive biological indicators for diagnosing esophageal cancer [18]. Therefore, identifying and studying new lncRNAs is extremely important for diagnosing cancer in its early stages, monitoring postoperatively, and treating esophageal cancer. As sequencing and omics technologies have advanced, there have been more opportunities to investigate potential diagnostic and therapeutic targets and gain a deeper understanding of the mechanism underlying esophageal cancer. In the present research, we combined bioinformatics analysis and in vitro experiments to explore the role of LINC00240 in the occurrence and progression of esophageal cancer and the possible mechanism. In the TCGA database, we found that LINC00240 is elevated in esophageal cancer. To individually predict the 1-, 3-, and 5-year survival probabilities of patients with esophageal cancer, we constructed a predictive model based on the results of multivariate analysis in the database. The result prediction model has a certain accuracy. Further data analysis in the TIMER database supports that the LINC00240 expression may be considerably related to tumor immune infiltration and indicates that LINC00240 might have a significant function in promoting immune escape of tumor cells in the esophageal cancer tumor microenvironment. Next, we analyzed the correlation between LINC00240 and the target molecules related to current esophageal cancer targeted drug therapy. We found that LINC00240 has a good correlation with EGFR, VEGFA, VEGFB, VEGFC, VEGFD, ERBB2, and MSI1. The results can provide a better reference for the selection of targeted drugs from the side. There are also relevant reports in relevant global clinical trials. For example, AdvanTIG-203 shows that tislelizumab combined with TIGIT monoclonal antibody Ociperlimab has better advantages compared with placebo in the treatment of PD-L1 positive esophageal squamous cell carcinoma. The Keynote-590 study showed that in Chinese patients with advanced esophageal cancer, pembrolizumab combined with chemotherapy can significantly improve patient survival, progression-free survival, and objective response rate compared with chemotherapy. RATIONALE 302 study showed that compared with second-line chemotherapy, tislelizumab can significantly improve the survival time of patients with advanced or metastatic esophageal squamous cell carcinoma whose disease has progressed after first-line therapy and has a higher response rate, longer response time, and lower adverse reactions. RAMONA study also proposes that nivolumab combined with ipilimumab is safe and feasible in the second-line treatment of elderly patients with esophageal squamous cell carcinoma. Therefore, immunotherapy combined with targeted therapy may be a better treatment option for recurrent or metastatic esophageal cancer. Moreover, the molecule LINC00240 studied in this project is not only related to the immune infiltration of esophageal cancer but also to the target molecule, which reflects that our research has certain clinical value. Then, through GSEA enrichment analysis, it was observed that LINC00240 may influence the biological events of esophageal cancer through five pathways: KEGG_APOPTOSIS; KEGG_VEGF_SIGNALING_PATHWAY; WP_ EGFEGFR_SIGNALING_PATHWAY; REACTOME_ CELL_CYCLE_CHECKPOINTS. Previous studies also showed that LINC00240 promoted the proliferation, migration, and EMT of gastric cancer cells through the miR-124-3p/DNMT3B axis; lncRNA LINC00240 inhibited the invasion and migration of non-small-cell lung cancer by sponging miR-7-5p. Therefore, cytological experiments further verified the expression of LINC00240 in esophageal cancer. This research observed that LINC00240 is largely present in esophageal cancer cells, and knocking down LINC00240 can strongly ameliorate the cancer cell growth, clone formation, and malignant abilities of esophageal cancer cells. According to molecular mechanism studies, endogenous LINC00240 inhibits the buildup and invasion of esophageal cancer cells by combining and modulating the miR-26a-5p expression. The uncontrolled, unlimited proliferation ability of cancerous cells is the main element in causing poor prognosis for patients. Searching for drugs, oncogenes, lncRNAs, or other targets that block the rapid division of cancerous cells is one of the hotspots in tumor research. For example, stable knockdown of DLL4 decreases the esophageal cancer metastases by attenuating Akt phosphorylation [19]. lncRNA SNHG7 expression is considerably increased in esophageal cancer cells, and it can promote esophageal cancer growth by influencing the expression of p15 and p16 [20]. LINC00240 is a recent discovery of a novel family of lncRNAs that regulates the onset and progression of various cancers. LINC00240, for example, is elevated in gastric cancer cells, and its increased levels are linked to a higher TNM stage, more distant and metastatic lymph nodes, with awful health and low chances of illness-free survival [21]. lncRNA LINC00240 represses malignant abilities of non-small cell lung cancer by controlling miR-7-5p [22]. Through the miR-124-3p/DNMT3B axis, LINC00240 can also enhance the metastases of gastric cancer [12]. LINC00240 was discovered to be substantially present in esophageal cancer tissues in the present research. Further in vitro cell function investigations revealed that knocking down LINC00240 greatly inhibited the rapid growth of esophageal cancer cells and the number of plate clones, suggesting that LINC00240 in esophageal cancer may be a cancer-promoting agent gene, providing new targets for subsequent targeted therapy. Inhibiting the expression of LINC00240 can greatly suppress the metastases of esophageal malignant cells. Previous research studies have revealed that miR-26a-5p exhibits various modulatory functions in different tumor tissues, acting as an antitumor, or tumor promoter. For example, as a tumor suppressor gene, miR-26a-5p has lower levels in gastric cancer tissue. Overexpression of miR-26a-5p can suppress the Wnt5a expression, thereby promoting programmed cell death and inhibiting the malignant capabilities of gastric cancer cells [23]. On the other hand, among the prooncogenes, miR-26a-5p acts as an oncogenic microRNA in non-small-cell lung cancer by targeting FAF1 and might function as a possible therapeutic target [24]. Analysis of miR-26a-5p expression levels in plasma helps to differentiate bladder cancer patients from healthy controls [25]. The findings of this research further demonstrate that LINC00240 can negatively regulate the miR-26a-5p expression in esophageal cancer cells. Cell function experiments demonstrated that inhibiting miR-26 knocked down the expression of LINC00240. However, the further molecular mechanism, that is, how miR-26a-5p controls downstream target gene expression to exert its tumor suppressor effect, needs to be further studied and verified by in vivo experiments. | true | true | true |
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PMC9556567 | Sarathkumar Edachery,Prakash Patil,Rajashekar Mohan,Bhuvanesh Aradhya,Jayaprakash Shetty,Shama Prasada Kabekkodu,Manas Kumar Santra,Sathisha Jayanna Gonchigar,Praveenkumar Shetty | Loss of miR-936 leads to acquisition of androgen-independent metastatic phenotype in prostate cancer | 12-10-2022 | Cancer,Molecular biology,Oncology | Prostate cancer (PCa) progresses from a hormone-sensitive, androgen-dependent to a hormone-refractory, androgen-independent metastatic phenotype. Among the many genes implicated, ANXA2, a calcium-dependent phospholipid binding protein, has been found to have a critical role in the progression of PCa into more invasive metastatic phenotype. However, the molecular mechanisms underlying the absence of ANXA2 in early PCa and its recurrence in advanced stage are yet unknown. Moreover, recent studies have observed the deregulation of microRNAs (miRNAs) are involved in the development and progression of PCa. In this study, we found the down-regulation of miR-936 in metastatic PCa wherein its target ANXA2 was overexpressed. Subsequently, it has been shown that the downregulation of miRNA biogenesis by siRNA treatment in ANXA2-null LNCaP cells could induce the expression of ANXA2, indicating the miRNA mediated regulation of ANXA2 expression. Additionally, we demonstrate that miR-936 regulates ANXA2 expression by direct interaction at coding as well as 3′UTR region of ANXA2 mRNA by luciferase reporter assay. Furthermore, the overexpression of miR-936 suppresses the cell proliferation, cell cycle progression, cell migration, and invasion abilities of metastatic PCa PC-3 cells in vitro and tumor forming ability in vivo. These results indicate that miR-936 have tumor suppressor properties by regulating the over expression of ANXA2 in hormone-independent metastatic PCa. Moreover, our results suggest that this tumor suppressor miR-936 could be developed as a targeted therapeutic molecule for metastatic PCa control and to improve the prognosis in PCa patients. | Loss of miR-936 leads to acquisition of androgen-independent metastatic phenotype in prostate cancer
Prostate cancer (PCa) progresses from a hormone-sensitive, androgen-dependent to a hormone-refractory, androgen-independent metastatic phenotype. Among the many genes implicated, ANXA2, a calcium-dependent phospholipid binding protein, has been found to have a critical role in the progression of PCa into more invasive metastatic phenotype. However, the molecular mechanisms underlying the absence of ANXA2 in early PCa and its recurrence in advanced stage are yet unknown. Moreover, recent studies have observed the deregulation of microRNAs (miRNAs) are involved in the development and progression of PCa. In this study, we found the down-regulation of miR-936 in metastatic PCa wherein its target ANXA2 was overexpressed. Subsequently, it has been shown that the downregulation of miRNA biogenesis by siRNA treatment in ANXA2-null LNCaP cells could induce the expression of ANXA2, indicating the miRNA mediated regulation of ANXA2 expression. Additionally, we demonstrate that miR-936 regulates ANXA2 expression by direct interaction at coding as well as 3′UTR region of ANXA2 mRNA by luciferase reporter assay. Furthermore, the overexpression of miR-936 suppresses the cell proliferation, cell cycle progression, cell migration, and invasion abilities of metastatic PCa PC-3 cells in vitro and tumor forming ability in vivo. These results indicate that miR-936 have tumor suppressor properties by regulating the over expression of ANXA2 in hormone-independent metastatic PCa. Moreover, our results suggest that this tumor suppressor miR-936 could be developed as a targeted therapeutic molecule for metastatic PCa control and to improve the prognosis in PCa patients.
Prostate cancer (PCa) is the second most leading cancer in males with an incidence and mortality rates of 30.7 and 7.7 cases per lakh age-standardized individuals, respectively (GLOBOCON 2020). Looking at the current trend of life expectancy rates and the existing age-specific incidence, morbidity, and fatality rates, PCa will become a far greater public health burden in the future. PCa develops in stages, including prostatic intraepithelial neoplasia (PIN), prostate cancer in situ, and hormone-dependent and -independent metastatic disease. The transition of PCa from hormone-dependent to -independent may be due to the loss of EGFR regulation and its altered signaling. The increased EGFR expression in combination with functional loss of PTEN (haploinsufficiency, mutation, and deletion) leads to activation of EGFR downstream signalling, particularly the PI3K-AKT pathway, in hormone-independent metastatic PCa. This signaling has been linked to the PCa progression to invasion and metastasis. In addition to altered expression of EGFR and PTEN, over expression of calcium-dependent phospholipid-binding protein Annexin A2 (ANXA2) is the main cause of aggressive and metastatic behavior of hormone-independent PCa cells. Though normal prostate epithelial cells express ANXA2 abundantly, it is not oncogenic, but in PCa, the constitutively active Src phosphorylates ANXA2's tyrosine-23 residue, which is critical for ANXA2 membrane translocation and all cancer-related functions such as plasminogen activation, actin-cytoskeletal rearrangement, cellular migration, adhesion, and proliferation. The loss of ANXA2 during PIN and early PCa, and its re-emergence in metastatic PCa is the most widely discussed protein signature. In addition, this increase in ANXA2 expression is linked to a worse clinical outcome and cancer recurrence in patients with metastatic PCa. Furthermore, earlier studies have suggested that ANXA2 may also play a role in EGFR-mediated downstream signaling. In this regard, our previous research established the ANXA2-EGFR autocrine loop by demonstrating that ANXA2 in the cancer cell membrane plays a vital regulatory role in EGFR downstream signaling. In metastatic cancer cells, downregulation of ANXA2 completely blocks all the EGFR downstream signaling, associated oncogenic events, and activates apoptosis. However, the molecular mechanisms underlying the absence of ANXA2 in early PCa and its recurrence in advanced stage are yet unknown. An altered transcriptional signature is both a cause and an outcome of cancer's hallmarks that include persistent proliferation, replicative immortality, evasion of growth suppression and apoptotic signals, angiogenesis, invasion, metastasis, evasion of immune destruction, and metabolic re-wiring. The post-transcriptional processes play a significant role in determining this signature, as demonstrated by the fact that alternative RNA splicing occurs in more than half of human genes, and more than 60% of protein-coding genes contain at least one conserved miRNA-binding site. However, only a few studies have looked at the involvement of specific miRNAs and their targets in the development and progression of metastatic PCa. In this context, we investigated miRNA-mediated transcript regulations and identified that ANXA2-codon and -3′UTR-targeting miR-936 has inverse regulatory roles in the progression of androgen-independent metastatic PCa. In this study, siRNA-mediated downregulation of miRNA maturation enzymes Drosha and Dicer in hormone-dependent PCa cells (LNCap), resulted the massive induction of ANXA2 expression, and also showed that miR-936 antagomir treatment induced ANXA2 protein expression. In addition, overexpression of miR-936 destabilises the mature ANXA2 mRNA post-transcriptionally, resulting in ANXA2 near extinction in early-neoplastic PCa. However, the overexpression of miR-936 in metastatic PCa cells downregulated ANXA2 expression, related downstream activators, and oncogenic functions. Overall, the loss of ANXA2 is caused by increased expression of miR-936 during early hormone-dependent PCa, and the reciprocal regulation causes it to reappear when the miRNA level is low during metastatic PCa. Moreover, our clinical specimen observations show that miR-936 is involved in a variety of biological processes that help to limit tumour growth at the molecular level. The findings of the study could lead to the development of a novel biomarker for predicting PCa prognosis and a potential therapeutic target for improving PCa treatment.
The PCa cell lines LNCaP, DU145 and PC-3 were purchased from NCCS Pune (INDIA) and cultured in RPMI-1640 (HiMedia, India) supplemented with 10% fetal bovine serum (FBS), 100 U/mL penicillin, and 100 mg/mL streptomycin, incubated at 37 °C in 5% CO2 with humidified atmosphere. Polyethylenimine (PEI 25000, Polysciences, USA) was used as a transfection reagent, and cells were seeded a day before transfection. Next day, transfection mixture was made in 150 mM NaCl solution by mixing DNA and polyethylenimine in a 1:2.4 ratio [DNA (μg): polyethylenimine (μg)] and the mixtures were incubated at room temperature for 15 min before being added drop-by-drop to the culture medium. MicroRNA expression vector, pCMV-MIR (M1005758 (#SC400690), Origene technology Inc, USA) was used to construct hsa-miR-936 plasmid vector for transfection to produce stable PC-3 cell lines using G-418 selection, subsequently named as miR-PC-3 cells. Synthetic oligonucleotide against hsa-miR-936 (HmiR-AN0841-SN-10, GeneCopoeia, USA) was used to transfect LNCaP cells for neutralizing the endogenous hsa-miR-936.
Paraffin-embedded PCa tissue sections were obtained from the SDM College of Medical Sciences and Hospital, Dharwad in accordance with established core protocols and Institutional Ethical Board approval. ANXA2 protein expression in tissues collected from PCa patients, including hormone-dependent, metastatic malignant tissue and adjacent non-malignant epithelium, and also in mice tissues from animal experiments, was determined by immuno-histochemical staining as described previously. First, tissue sections were stained with hematoxylin–eosin to assess the histological form and grade of tumors and then subjected to immunohistochemistry. In brief, following deparaffinization and endogenous peroxidase blockage, the sections were heated in 0.01 M citrate buffer solution (pH 6.0) in a water bath at 98 °C for 20 min; then incubated with 1:100 diluted monoclonal anti-body to ANXA2 (sc-28385, Santa Cruz Biotechnology, TX, USA) overnight at 4 °C; and visualized using a 3,3′-diaminobenzidine detection kit (Vector labs). Staining intensity of ANXA2 was graded by microscopic observation on a scale of 0 to 3+ , where 0 and 3+ indicates no staining and strong staining, respectively.
As described earlier, the total RNA was isolated from the DU-145, PWR-1E and LNCaP cells and enriched for small RNA (< 300 nt) by size-fractionation using a YM-100 Microcon centrifugal filter (Millipore, Billerica, MA), according to the manufacturer’s instructions. The small RNAs isolated was 3′ extended with poly(A) tail using poly(A) polymerase and an oligonucleotide tag was ligated to the poly(A) tail for later fluorescent dye staining. For hybridization, the probe on the plate consisted of sequences complementary to the miRNA from miRBase and the custom sequences; the target was the RNA from the samples. After hybridization, detection used fluorescence labeling using tag-specific Cy3 dye. Images collected were analyzed using Array-Pro image analysis software. The data analysis involved subtraction of the background along with normalization using a LOWESS filter. The miRNA that was differentially expressed in the cells was identified and "BLAST"ed against the unspliced mRNA/genomic sequence of the ANXA2. The putative miRNA for the study met all of the following criteria: it was differentially expressed in the miRNA microarray analysis, had good matches with the target sequence in the BLAST search, and was predicted by one of the in-silico miRNA prediction methods.
Total RNA from the cells was isolated using TRIzol reagent method (Thermo Fisher Scientific Inc., USA) and 1 μg of RNA was used for cDNA synthesis (Thermo Fisher Scientific Inc., USA) according to the manufacturer instructions. As described previously, the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed using the gene-specific primers for ANXA2 (F-5′TAACTTTGATGCTGAGCGGG3′ ; R- 5′TAATTTCCTGCAGCTCCTG3′), GAPDH (F-5′GAGCGAGATCCCTCCAAA3′ ; R- 5′ACTGTGGTCATGAGTCCTT3′), miR-936 (F-5′ CAGACAGTAGAGGGAGGAATC3′ ; R- 5′GTCCAGTTTTTTTTTTTTTTTCTGC3′) and U6 snRNA (F-5′CTTCGGCAGCACATATACTAAAA3′ ; R-5′CGCTTCACGAATTTGCGTGTCAT3′) designed using Primer3 software, were used for the amplification using TB Green Premix Ex Taq II (#RR820A, Takara, Japan) in Quant Studio QS5 (Thermo Fisher Scientific Inc., USA). The relative transcripts expression level was calculated on the basis of 2−ΔΔCT method, where GAPDH and U6 snRNA expression were used as endogenous control, and each gene expression was reported as n-fold change.
Cellular proteins were extracted, quantified, separated on 10% Bis–Tris PAGE, and western blotting was performed as described previously. Proteins were detected using the specific monoclonal antibodies against ANXA2 (sc-28385), pEGFR (sc-81488), pAKT (sc-7985-R), AKT (sc-5298), pSTAT-3 (sc-7993), STAT-3 (sc-8019), pERK (sc-7383), p27-kip (sc-528), GAPDH (sc-25778), HIF-1-alpha (sc-13515), VEGF (sc-7269), Vimentin (sc-32322), E-Cadherin (sc-7870), MMP-9 (sc-12759), Bcl-2 (sc-492) and Bcl-xl (sc-8392) (Santa Cruz Biotechnology, SantaCruz, CA). Appropriate Secondary antibodies conjugated to horseradish peroxidase (BioRad, USA) were incubated for 2 h at room temperature with the respective membranes. The images were acquired using enhanced Chemiluminescence system (G: BOX Chemi XX9) and the protein bands were quantified by densitometry analysis using Image J (IJ 1.46 r).
Dual-Luciferase assay was performed as described previously. Briefly, the luciferase expression vector pGL4-human ANXA2 encoding the 3′UTR and coding region containing predicted miR-936 binding site 5′-UGUACUGU-3′ and 5′-UCUACUGU-3′, respectively, was constructed. Concomitantly, the site directed mutagenesis of miR-936 binding sites was performed to produce mutant constructs. The ANXA2 UTR-specific (infusion_1: ATC CTT TAT TAA GCT TAG CCC GAC ACG GCC TGA GCG T; infusion_2: TTA AAC AGT TAA GCT TCA TTT AAA TTT AAC TTA AAT AGC GAC AC) and ANXA2 coding region- specific (infusion_1: ATC CTT TAT TAA GCT TTC TAC TGT TCA CGA AAT CCT G; infusion_2: TTA AAC AGT TAA GCT TGT CAT AGA GAT CCC GAG CAT C) primers were used. PC-3 and LNCaP cells were transiently transfected with either WT or mutated reporter constructs and pre-miR-936 using polyethylenimine in a 24-well plate, and co-transfected with anti-miR-936 after 48 h of transfection, then the cells were harvested and lysed for the assay. Luciferase activity was measured according to the Dual-Luciferase Reporter Assay System (Promega, USA), and renilla luciferase expression was used for data normalization.
In vitro scratch assay was performed as described previously. Briefly, 6 × 105 PC-3 and stable miR-936 expressing PC-3 (miR-PC-3) cells were seeded onto six-well plate, after reaching confluency, a scratch was made using 200 μL pipette tip. The open space was tracked using live cell imaging microscope (Motic AE2000 series camera), photographed at 0, 6, and 18 h interval, and the percentage of wound closure was quantified using Image J (IJ 1.46r).
Five thousand PC-3 and/or miR-PC-3 cells were seeded in 35-mm culture dish and allowed to grow for 12–15 days to form the colonies. Surviving cell colonies were fixed with 3.7% formaldehyde, washed with PBS, and stained with 0.2% crystal violet solution and 2% ethanol. Plates were photographed, and the percentage of surviving colonies was quantified using Image J (IJ 1.46 r).
As previously described, in vivo tumorigenicity studies were conducted in compliance with the Institutional Animal Ethics Committee (IAEC) of SDM College of Medical Sciences and Hospital, Dharwad. In brief, 4–5 weeks old, 16–19 g male BALB/c nude mice were used for in vivo tumorigenicity studies. The suspensions of PC-3 and miR-PC-3 cells (~ 1 × 107 cells/mL) were mixed with Matrigel and injected (n = 4 per group) subcutaneously into the flank of mice. The tumor size was observed regularly up to the onset of palpable tumor and all the mice were injected intraperitoneally with ketamine (90 mg/kg) to anaesthetize and euthanised by cervical dislocation to collect the tumor. Visual images of the tumor were immediately photographed after the excision. To measure the length (L) and width (W) of tumors using digital Vernier Caliper, and the tumor size was calculated using the following formula: V = ab2/2 (a, length; b, width).
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee of SDM College of Medical Sciences and Hospital (SDM-IEC-54/Ext-2016, and 08-07-2016) for studies involving humans. Informed consent was obtained from all subjects involved in the study. The animal study protocol was approved by the Institutional Animal Ethics Committee of SDM College of Medical Sciences and Hospital (SDM-IAEC-53/Ext-2016, and 08-07-2016) for studies involving animals and confirming that all experiments were performed in accordance with the ARRIVE guidelines as stipulated in the Indian Committee for the Purpose of Control and Supervision of Experiments on Animals (CPCSEA), a statutory Committee of Department of Animal Husbandry and Dairying (DAHD), Ministry of Fisheries, Animal Husbandry and Dairying (MoFAH&D) constituted under the Prevention of Cruelty to Animals (PCA) Act, 1960 regulations.
To confirm the altered expression of ANXA2 in PCa, its expression level in different stages of PCa was determined by immunohistochemical analysis. As observed in earlier studies, our immunohistochemistry data also demonstrated the significantly (P < 0.0001) high expression of ANXA2 in normal prostate epithelial cells with 2+ staining intensity. In PIN and during early PCa incidence, the ANXA2 is very low or null with 0 or 1+ staining intensity. However, the higher Gleason score and poorly differentiated PCa specimen demonstrated abundant expression of ANXA2 with 3 + staining intensity (Fig. 1a,b).
The siRNA mediated downregulation of miRNA maturation enzymes Drosha and Dicer in hormone-dependent PCa LNCaP cells resulted in massive induction of ANXA2 expression. Drosha siRNA treatment alone induced nearly 30-fold increase in ANXA2 mRNA level, Dicer siRNA treatment alone increased about 16-fold and both together increased 70-fold ANXA2 mRNA expression (Fig. 1c). These results clearly indicate that disappearance of ANXA2 in LNCaP cells is due to miRNA mediated destabilization of ANXA2 mRNA.
MicroRNA profiling of normal prostatic epithelial cells PWR1E, early hormone-dependent PCa cells LNCaP and metastatic PCa cells DU145 and PC-3 identified hsa-miR-936 as the most differentially expressed miRNA. Further in silico and expression analysis revealed that miR-936 expression was minimal in PC-3, PWR1E and DU145 cells, and was very highly expressed in LNCaP cells (Fig. 1d). Moreover, the increased expression of miR-936 resulting in near absence of ANXA2 was observed in early neoplastic stage as this miR-936 has a seed sequence complimentary to the ANXA2 coding region that post-transcriptionally destabilizes the synthesis of mature mRNA (Figs. 1a,b,e). Furthermore, another complimentary seed sequence in the 3’UTR region of ANXA2 was also identified for miR-936 (Fig. 1e).
Considering the null expression of ANXA2 and relatively very high expression of miR-936, an androgen dependent PCa cell line LNCaP was selected for the antagomir treatment experiment. ANXA2 mRNA expression was induced within 6 h of miR-936 antagomir treatment by qRT-PCR and observed stable till 48 h post treatment (Fig. 2a). Additionally, the reappearance of ANXA2 protein expression was observed by western blot analysis in ANXA2-null LNCaP cells after 48 h of miR-936 antagomir treatment, demonstrates the role of miR-936 in the destabilization of ANXA2 mRNA during early PCa (Fig. 2b).
In order to clarify the involvement of miR-936 in the transition of hormone-dependent to hormone-independent metastatic PCa, tissue samples obtained from PCa patients were analysed for miR-936 and ANXA2 expression by qRT-PCR. The expression of miR-936 was significantly decreased in metastatic PCa compare to hormone dependent PCa, where miR-936 expression was significantly increased. On the contrary, ANXA2 mRNA level is negligible in Hormone dependent PCa compared to very high expression in metastatic PCa tissue samples (Fig. 2c). This clinical data convincingly illustrates the involvement of miR-936 in driving the very high expression of ANXA2 in hormone-independent metastatic PCa. To ascertain the clinical sample observations, a dual-luciferase reporter assay was performed to confirm the presence of direct interaction between miR-936 and ANXA2 mRNA. An infusion cloning method was adopted to generate a reporter plasmid that is driven by the cytomegalovirus basal promoter and harbouring the ANXA2 coding and 3’UTR nucleotides at the 3′ position of the Luciferase reporter gene. The transient transfection of ANXA2 reporter constructs expressing plasmid into LNCaP cells where basal miR-936 expression is high, reduced the luciferase activity of plasmid but not affected by co-transfection with miR-936 antagomir (Fig. 2d). However, the luciferase activity of plasmid was not affected in PC-3 cells where miR-936 expression is expected to be very low, but significantly decreased after co-transfection with miR-936 expressing plasmid (Fig. 2e). These results indicated that miR-936 interacted with the specific coding region and 3’UTR of ANXA2 mRNA.
The loss of miR-936 in PC-3 cells and metastatic PCa was demonstrated to possess the higher tumorigenicity mediated by the expression of ANXA2, was further assessed for its effect on ANXA2-EGFR mediated downstream signaling. Transient transfection of miR-936 in PC-3 cells inhibited ANXA2 protein expression after 72 h of treatment. Consistent with the decrease of ANXA2 expression, anti-apoptotic Bcl-xl and signaling molecules like pAKT and pSTAT-3 expressions were also decreased at the protein level following the transient transfection of miR-936. Conversely p27kip, a putative tumor suppressor expression was increased, while the expression of STAT-3 and AKT remain unchanged (Fig. 3a). The ANXA2 mRNA and protein expression in PC-3 cells was significantly knockdown with the transfection of miR-936 vector by gain-of-function assay. In accordance with the reduction in ANXA2 expression, the ectopic expression of miR-936 had the same effect on downstream effectors of ANXA2 such as VEGF, HIF-1alpha, vimentin, and MMP-9, however increase in E-Cadherin was also observed (Fig. 3b). Similarly, pEGFR and its other downstream signaling molecules like pAKT, pSTAT-3 and pERK expressions were also downregulated at the protein level following overexpression of miR-936 (Fig. 3c).
The results of cellular function assays demonstrated that over expression of miR-936 in PC-3 cells had markedly decreased the proliferation, colony formation, migration, and invasion processes of the metastatic PCa PC-3 cells. Given that ANXA2 has a critical role in the regulation of cell proliferation, colony formation and migration, metastatic PCa cells, PC-3 were transfected with miR-936 and analyzed for these terminal functions. The migration potential of miRNA-936 expressing PC-3 cells significantly abrogated compared to wild type PC-3 cells (Fig. 4a,b). Cell proliferation of PC-3 cells were compared with stable PC-3 cells expressing miR-936 (miR-PC-3). The proliferation index was assessed at 2, 4, 6, 8 and 10 d (Fig. 4c) till ten days the rate was high in PC-3 compared to miR-PC-3 cells, after ten days significant 50% inhibition in proliferation was noticed in miR-PC-3 cells. Colony formation assay revealed that miRNA overexpression in PC-3 cells leads to significant decrease in the number as well as size of colonies compared to vector control PC-3 wild type cells as reported in Fig. 4d. Results taken together suggest that cancer cell proliferation, colony formation and migratory potential is inhibited by miR-936 predominantly through downregulation of ANXA2-EGFR signaling and inactivation of terminal functional proteins.
We looked into the tumorigenic inhibitory potential of miR-936 in PCa progression. During examination, we made xenografts of PC-3 cells expressing either miR-936 or vector control in male BALB/c nude mice to demonstrate miR-936's growth-repressive effect on PCa in vivo. Tumor growth was measured after a palpable tumor appeared. The tumor sizes were tracked every 5 d until the 31st day (Fig. 5a). As a result, the over expression of miR-936 in PC-3 cells, the tumor showed significant decreases compared to the group treated with vector control. These findings demonstrated that ectopic expression of miR-936 significantly suppressed tumor growth and also our immunohistochemistry data reveals the reduced ANXA2 expression in xenografts of PC-3 cells ex-pressing miR-936 in male BALB/c nude mice compared to vector control (Fig. 5b).
PCa is the most commonly diagnosed and is the second most leading cause of cancer-related deaths among men. Androgens and the androgen receptor (AR) play an important role in prostate pathobiology as they are required for their normal growth and maintenance. The vast majority of PCa are androgen-dependent tumors. Androgen deprivation therapy is often used as an adjuvant treatment along with radiotherapy. Even though patients initially respond well to hormonal therapies, tumors will eventually progress to develop a castration-resistant PCa (CRPC), a treatment-insensitive, metastatic disease with a worse prognosis. The majority of patients develop CRPC and progress to metastatic disease. In addition to androgens, prostate growth and function is in-part regulated by several growth factors and their cognate receptors, one of which is the epidermal growth factor and its receptor (EGFR) has been known to drive hormone independent PCa progression. EGFR alone cannot drive the progression of metastatic PCa tumours, but its linked to its upstream fibrinolytic receptor ANXA2, are together known to the PCa and breast cancer progression. Further, our in silico analysis revealed that the survival ability of the prostate cancer patients is poor with the increased expression of ANXA2 along with the high (> 6.0) gleason score (Fig. S1). However, the molecular mechanism underlying the progression from hormone-dependent PCa to metastatic CRPC is poorly understood. Also, the primary rationale behind the absence of ANXA2 in early PCa and its reappearance in advanced PCa are not yet deciphered. Interestingly, it has been observed that ANXA2 and EGFR expression is reduced in hormone-dependent PCa but abundant in metastatic PCa, suggesting their functional role in PCa progression that the function of these molecules may depending on the cellular context. Furthermore, overexpression of ANXA2 in certain tumor is correlated with worst clinical outcomes and also it has been associated with a variety of oncogenic functions, including signal transduction, cytoskeletal rearrangement, membrane fusion, cellular migration, adhesion, and proliferation. MicroRNAs, a class of post-transcriptional regulators were found to be active in carcinogenesis, particularly PCa. Extensive research revealed that miRNAs could influence downstream messenger RNAs (mRNAs) via complementary base pairing, therefore influencing pathway signal transmission and the function of cellular processes. Comprehensive exploration of miRNAs associated with PCa development and progression will help to improve our understanding of the molecular basis of pathogenesis. As the differential expression of miRNA tends to be both the cause and the outcome of oncogenesis in cancer, we looked into the possibility of miRNAs regulating ANXA2 at the posttranscriptional level in PCa. In support to this, our initial microarray analysis of androgen-dependent cell line LNCaP, metastatic PCa cell line DU145 and normal prostatic epithelial cells PWR1E, revealed that miR-936 was the most differentially expressed. It indicates that miR-936 is involved in the development of androgen-dependent PCa and its transformation into metastatic CRPC. In recent studies, this miR-936 has been shown to influence the cell activity and tumour growth of gastric cancer and Laryngeal Squamous Cell Carcinoma. However, the precise role and mechanism underlying the involvement of miR-936 in the prostate cancer progression has not been determined yet. In the present study, we have shown that miR-936 is strongly expressed in hormone-dependent PCa cell line LNCaP that lacking ANXA2. In addition, we also found that miR-936 expression is minimal in metastatic PCa cell lines DU145 and PC-3 where ANXA2 expression is high. Furthermore, we identified that miR-936 have direct interaction with ANXA2-coding & -3UTR. By interacting with their target mRNAs, miRNAs post-transcriptionally control gene expression by regulating translational attenuation via miRNA-binding sites in the target gene's 3'UTR and these target genes are often involved in controlling crucial developmental events. However, interactions between miRNAs and other areas have been discovered, including the 5′ UTR, coding sequence, and gene promoters. According to some recent studies, miRNAs can target the coding region of mRNA and control the gene expression. ANXA2 at the cancer cell membrane surface interacts with EGFR and it is critical for the regulation of downstream signalling. As ANXA2 has a crucial function in the pathogenesis of PCa, current findings identified a correlation between dysregulated miR-936, overexpressed ANXA2 and PCa cell proliferation. As per our findings, ANXA2 is a direct target of miR-936 and also treatment with miR-936 antagomir induced ANXA2 mRNA as well as protein expression in ANXA2 null hormone-dependent PCa cell line LNCaP. These results were in similar to the upregulation of AR expression in LNCaP cells treated with miR-185 antagomir. However, overexpression of miR-936 in metastatic PCa cells PC-3 reduced ANXA2 expression, associated downstream activators, and oncogenic functions by inhibiting their proliferation, cell cycle progression, cell migration, and invasion abilities in vitro. Correspondingly, ectopic expression of miR-940 in metastatic PCa cell line DU145 and PC-3 attenuates its migration and invasion ability by regulating migration and invasion enhancer 1 (MIEN1) expression. Furthermore, xenografts of PC-3 cells expressing miR-936 in male BALB/c nude mice significantly reduced ANXA2 expression as well as subcutaneous tumor formation in vivo, indicating a tumor suppressor role of miR-936 in PCa. Overall, Fig. 5c depicts the demonstration of the near elimination of ANXA2 by overexpression of tumor suppressor miR-936 that directly targets ANXA2-codon & -3’UTR in metastatic PCa.
Current study convincingly demonstrates that miR-936 is a novel post-transcription regulator of calcium dependent phospholipid binding protein ANXA2 in hormone-dependent and -independent PCa. Moreover, this potential tumor suppressor miR-936 regulates the ANXA2 mRNA expression by binding to its coding and 3’UTR regions. Nonetheless, these results would pave the way to further research for unravelling the role of miR-936 in prostate cancer, possibly as an early diagnostic and, later as a prognostic indicator for the therapeutic management of PCa.
Supplementary Information.Supplementary Figure S1. | true | true | true |
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PMC9556637 | Omnia Ameen,Rehab M. Samaka,Reda A. A. Abo-Elsoud | Metformin alleviates neurocognitive impairment in aging via activation of AMPK/BDNF/PI3K pathway | 12-10-2022 | Physiology,Neurology | Slowing down age-related neurocognitive impairment has been a challenge. We evaluated the therapeutic effects of metformin in d -galactose-induced aging. Additionally, we studied the potential molecular mechanisms that could be responsible for metformin's anti-aging effects. Thirty male rats were equally divided into: 1—control group, which received saline solution, 2— d -galactose (D-gal) group, which received d -galactose (100 mg/kg/day) by gastric lavage for eight weeks, and 3— d -galactose + Metformin (D-gal + Met) treated group, which received d -galactose + metformin (200 mg/kg/day) by gastric lavage for eight weeks. Neurocognitive assessment was done. Measurement of inflammatory, oxidative stress, and BDNF biomarkers was performed. AMPK and PI3K genes expression were assessed. Hippocampal tissues were dissected for histopathological and immunohistochemical studies. D-gal resulted in neurocognitive impairments, elevation of inflammatory biomarkers, altered oxidative stress markers, decreased BDNF, decreased expression of synaptophysin and Bcl2 with increased expression of Caspase-3, and down-regulation of AMPK and PI3K genes. Neurodegenerative changes were present in the hippocampus. Metformin restored significantly D-gal induced neurodegenerative changes. We concluded that metformin could alleviate age-induced neurocognitive deficit via amelioration of neuroinflammation, attenuation of oxidative stress, reduction of apoptosis, as well as promotion of synaptic plasticity. These mechanisms could be mediated via the activation of the AMPK/BDNF/PI3K pathway. | Metformin alleviates neurocognitive impairment in aging via activation of AMPK/BDNF/PI3K pathway
Slowing down age-related neurocognitive impairment has been a challenge. We evaluated the therapeutic effects of metformin in d-galactose-induced aging. Additionally, we studied the potential molecular mechanisms that could be responsible for metformin's anti-aging effects. Thirty male rats were equally divided into: 1—control group, which received saline solution, 2—d-galactose (D-gal) group, which received d-galactose (100 mg/kg/day) by gastric lavage for eight weeks, and 3—d-galactose + Metformin (D-gal + Met) treated group, which received d-galactose + metformin (200 mg/kg/day) by gastric lavage for eight weeks. Neurocognitive assessment was done. Measurement of inflammatory, oxidative stress, and BDNF biomarkers was performed. AMPK and PI3K genes expression were assessed. Hippocampal tissues were dissected for histopathological and immunohistochemical studies. D-gal resulted in neurocognitive impairments, elevation of inflammatory biomarkers, altered oxidative stress markers, decreased BDNF, decreased expression of synaptophysin and Bcl2 with increased expression of Caspase-3, and down-regulation of AMPK and PI3K genes. Neurodegenerative changes were present in the hippocampus. Metformin restored significantly D-gal induced neurodegenerative changes. We concluded that metformin could alleviate age-induced neurocognitive deficit via amelioration of neuroinflammation, attenuation of oxidative stress, reduction of apoptosis, as well as promotion of synaptic plasticity. These mechanisms could be mediated via the activation of the AMPK/BDNF/PI3K pathway.
The steady loss of physiological function, mental agility, and memory that occurs with aging is a multifaceted process that may be triggered by neuronal cell death. The life expectancy in many countries is projected to exceed 85 years by 2030. Because of the decreased quality of life for the elderly and the associated economical and personal expenditures, aging-related cognitive impairments have emerged as a significant social issue. In addition, brain aging is the primary cause of the development of neurodegenerative diseases which frequently progress irreversibly. There are few or no effective treatments currently available for aging-related neurocogitive impairment. d-galactose (D-gal), a monosaccharide abundant in milk products, is normally converted to glucose by enzymes. However, long-term systemic D-gal administration can pose substantial health hazards. Previous research suggested that persistent systemic D-gal delivery to rats could transform them into models of aging and age-related neurodegenerative disorders. The D-gal aging model has several advantages over the natural aging model, including the ability to concentrate solely on the aging process. In the natural aging model, comorbidities including diabetes and hypertension are complicating variables. D-gal is thought to generate biochemical anomalies similar to those seen in the aging human brain, such as reduced the activity of antioxidant enzymes and attenuation of the cholinergic neurons. Advanced glycation end products, which are linked to both normal aging and the pathophysiology of many diseases, are produced by interaction of D-gal with protein amino groups. Animals provided D-gal caused neuroinflammation, mitochondrial damage, and oxidative damage from the development of Reactive Oxygen Species (ROS) along with problems in novelty habituation, deficiencies in spatial learning, and cognitive functions. Inflammation could be a key factor in cognitive deterioration among the elderly. High levels of interleukin-6, IL-1, tumor necrosis factor-α, and C-reactive protein have been linked to an increased risk of morbidity and mortality in the elderly. Chronic d-galactose treatment in rats induced neuronal apoptotic signaling pathways activation and neuroinflammation in the cerebral cortex and hippocampus. Aging results in a decline in Brain-derived neurotrophic factor (BDNF) which is a crucial protein engaged in plastic changes associated to learning and memory as well as a vital mediator for neuronal proliferation and integrity. The discovery of novel compounds delaying aging and supporting cognitive performance has become one of the greatest challenges. Metformin quickly penetrates the blood–brain barrier and builds-up in a number of brain areas, including the pituitary gland and hippocampus. It has been demonstrated that long-term metformin administration reduces the onset of age-related pathological complications and lengthen longevity in humans. Furthermore, metformin has been shown to improve cognitive impairment and behavioral disorders like anxiety in both diabetic and non-diabetic individuals and patients with neurodegenerative diseases. However, the underlying mechanisms of metformin's effects in improving age-related neurocognitive impairment are complicated and yet not entirely understood. The neuroprotective effects of metformin may be primarily attributable to the activation of the AMP-Activated Protein Kinase (AMPK) signaling pathway. AMPK activation up-regulates the expression of BDNF, which has a critical role in synaptic transmission and memory consolidation. In addition to this well-established property of AMPK activation, previous results have demonstrated that metformin can enhance memory through the restoration of oxidative stress, decrement of neuroinflammation, and inhibition of apoptosis, which may expand its clinical indications in the area of neurodegenerative disorders. Metformin is a strong activator of the phosphatidylinositol 3‑kinase/protein kinase B (PI3K/Akt) pathway which is an important critical signaling pathway in inhibiting apoptosis and promoting cell survival. Taking into consideration metformin's benefits, which include it's safety, affordability, and usability; we studied the neuroprotective effects of metformin administration against neurocognitive impairment caused by d-galactose-induced aging in rats. Additionally, the underlying molecular mechanisms of these protective effects were invistigated.
Thirty Wister albino male rats weighing 200–250 grams were used in the experiment after obtaining the necessary approvals from the Research Ethical Committee in the Faculty of Medicine, Menoufia University, Egypt (registration No. 10/2022 PHYS 9). Experimental procedures followed ARRIVE guidelines. The rats were housed in wire mesh cages (80 × 40 × 30 cm). All animals were provided full access to food and water during the study period after conditioning them for 2 weeks at constant environmental conditions and 12:12-h light/dark cycle.
The animals were divided randomly into three groups (10/group): Control group: Received saline solution via oral gavage. d -galactose (D-gal) group: Received d -galactose (Sigma-Aldrich St. Louis, USA) dissolved in a saline solution in a dose of 100 mg/kg body weight via gastric lavage for eight consecutive weeks d -galactose + Metformin (D-gal + Met) treated group: Received d -galactose (by the same dose in the D-gal group) + metformin (Sigma-Aldrich St. Louis, USA) dissolved in a saline solution in a dose of 200 mg/kg/day via gastric lavage for eight consecutive weeks Following the completion of eight weeks, a neurobehavioral assessment of all rats was done. Thereafter, rats were anesthetized and sacrificed by cervical elongation and dislocation. The brain was extracted and washed with phosphate buffer saline (pH 7.4). The left hemisphere was weighed and divided into two halves; one of them was used for biochemical analysis and the other half was used for RT-PCR studies. The right hemisphere was fixed in a 10% formalin saline for histopathological and immunohistochemical assessment of the hippocampal tissues.
The novel object recognition test was used to assess the rats’ capacity to recognize a new object in a familiar setting. Each rat had three days of testing, which included three phases: habituation, training, and testing. Rats were placed into an open-field apparatus (50 cm × 50 cm × 40 cm) during the habituation phase, and they were given ten minutes for adaptation without any items. Each rat was kept in a chamber with two identical objects for five minutes during the training phase. After twenty-four hours, each rat was placed in the chamber for five minutes during the test phase, which involved the replacement of one of the old objects with a new one. The stopwatch was used to time the duration of object exploration. The discrimination index [= (novel object exploration time–familial object exploration time)/total exploration time × 100%] is used to assess rats' cognitive performance. Alcohol was used to clean the open field and the objects between rats.
The Morris water maze was used to examine the impact of metformin on spatial learning and memory. A pool was made of stainless steel, had a diameter of 210 cm and a height of 50 cm including a submerged escape platform 1 cm below the water's surface. The water was maintained at 24 ± 1 °C. The acquisition task was tested over the course of five days of testing with four trials each day. The time needed to get to the secret platform during each trial was recorded as escape latency. A maximum of 60 seconds were given to the rats to locate the covert platform. A maximum time limit of 60 s was assigned, and the rat was manually guided to the hidden platform. A single probe trial was conducted 24 h after the last trial of the fifth day. The platform was removed and the rat was placed into the pool from the quadrant opposite to the training quadrant. Then, the rat was allowed to freely swim for 60 s. The time spent in the target quadrant was recorded.
EPM is an established technique for evaluating anxiety-like behavior in rats. It was made of wood and consisted of open and closed arms (50 cm in length × 10 cm in width). The two closed arms were enclosed by 40 cm high walls. The arms were attached by a central square platform (10 × 10 cm). The apparatus was 50 cm above the floor. Each rat was placed in the center of the apparatus facing a closed arm and allowed to move freely for five minutes. The time spent in the open and closed arms was recorded. Also, open arms entries were recorded. We also measure the Transfer Latency (TL) which used to assess memory and learning. On the first day (the acquisition session), each rat was exposed to EPM for 90 s. Time taken by the rat to reach the closed arm was recorded as the TL. Rats that failed to enter in closed arms in 90 s were excluded from the study. On the second day (the retention session), each rat was put into the open arm and the TL was recorded for a maximum of 90 s.
Brain tissue was perfused with PBS solution, then homogenized in a 5 ml cold buffer per gram tissue. Centrifugation of the brain tissue was done at 4000 rpm for 15 minutes, then the supernatant was removed and stored at − 80 °C until measurements of Malondialdehyde (MDA) and Superoxide Dismutase (SOD) by using the conventional colorimetric (QuantiChrom™, BioAssay Systems, USA), serum Tumour Necrosis Factor (TNF-α), Interleukin 10 (IL-10), and Brain-Derived Neurotropic Factor (BDNF) by using ELISA kit (Quantikine, Abcam company, Cambridge, UK) according to the manufacturer’s instructions.
Brain tissues were prepared for total RNA isolation using Qiagen RN easy plus Universal Kit from the USA. Then, RNA quality and purity were assured. RNA was stored at − 80 °C till use. Then, the first step was cDNA synthesis using QuantiTect Reverse Transcription Kit, Qiagen from the USA, using Applied Biosystems 2720 thermal cycler (Singapore) for only one cycle. GAPDH primers were used in RT-PCR reactions as an RNA loading control. The second step was cDNA amplification: cDNA was used in SYBR green-based quantitative real-time PCR for Relative Quantification (RQ) of AMPK and PI3K genes expression by SensiFASTTMSYBR Lo-ROX Kit, USA, using the following designed primers (Midland, Texas): The forward primer for AMPK was (TGCGTGTACGAAGGAAGAATCC). And the reverse primer was (TGTGACTTCCAGGTCTTGGAGTT). The forward primer for PI3K was (AGCTGGTCTTCGTTTCCTGA), and the reverse primer was (GAAACTTTTTCCCACCACGA). Finally, data analysis with the Applied Biosystems 7500 software version 2.0.1 was done. The RQ of AMPK and PI3K genes expression was performed using a comparative ∆∆Ct method, where the amount of the target genes (AMPK and PI3K) mRNA is normalized to an endogenous reference gene (GAPDH) and relative to a control.
Brain tissue was fixed in a 10% formalin solution, embedded in paraffin, and serial coronal sections of 5 μm thickness were obtained. Sections of the brain hippocampus were then stained with Hematoxylin and Eosin (H&E) for examination with a light microscope.
Immunohistochemical staining of caspase-3 (CAT number: ab32351, Abcam company 152 Grove Street Waltham, M02453, USA) and synaptophysin (CAT number: ab32127, Abcam company 152 Grove Street Waltham, M02453, USA) were performed by using rabbit monoclonal antibodies. For Bcl-2 (CAT number: ab59348, Abcam company 152 Grove Street Waltham, M02453, USA), it took place by using rabbit polyclonal antibodies. They were received in a single vial containing 1 ml of antibody. Anti-caspase-3, anti-synaptophysin, and anti-Bcl-2 were used in diluted quantities 1:50, 1:400, and 1:100 respectively. Sections were cut at 5 µm and stained by an automated LINK 48 immunostainer (Dako, Agilent Technologies Inc, Santa Clara, USA). For heat retrieval, citrate buffer was used by immunostainer. Slides were stained automatically by primary diluted antibodies. Positive control for the reaction was performed using specific paraffin-embedded sections of the normal human tonsil, human pancreas, and follicular adenoma for caspase-3, synaptophysin, and Bcl-2, respectively. Negative controls were made by substituting the primary antibodies with non-immune serum. Assessment of histopathology and immunohistochemical markers (caspase-3, synaptophysin and Bcl-2) was done in different areas of the hippocampus including CA1,CA2 and CA3.
Results are expressed as mean ± Standard Deviation (SD). Analysis of Variances (ANOVA) was used for statistical analysis of the different groups, using Origin® software and the probability of chance (p values). P values < 0.05 were considered significant.
This work was approved by and in accordance with the guidelines of the Ethical Committee of the Faculty of Medicine, Menoufia University, Egypt.
Regarding the novel object test, the percentage of discrimination index was significantly lower in the D-gal group when compared with the control group (-37.16 ± 3.31% vs. 30.16 ± 2.92%, respectively, P < 0.05). The percentage of discrimination index was significantly higher in the D-gal + Met group (16.66 ± 4.67%, P < 0.05) when compared with the D-gal group. However, this percentage is still significantly lower when compared with the control group (Fig. 1). Regarding the Morris maze test, the mean value of the duration of escape latency was significantly higher in the first, second, third, fourth, and fifth days in the D-gal group when compared with the control group (58.16 ± 1.94, 40.62 ± 1.33, 32.75 ± 1.10, 24.37 ± 1.58, and 15.29 ± 0.98 s vs. 40.16 ± 2.92, 25.16 ± 1.15, 17.04 ± 1.08, 11.75 ± 1.31, and 5.83 ± 0.86 s, respectively, P < 0.05). The mean value of the duration of escape latency was significantly lower in the D-gal + Met group in the five training days (50 ± 1.41, 34.08 ± 1.15, 25.16 ± 1.31, 16.04 ± 1.75, and 10.25 ± 1.01 s, respectively, P < 0.05) when compared with the D-gal group. However, the mean values of the durations of escape latency in the five training days in the D-gal + Met group were still significantly higher when compared with the control group. The mean value of the duration that the rats spent in the target quadrant was significantly lower in the D-gal group when compared with the control group (12.50 ± 1.87 vs. 23.50 ± 1.87 s, respectively, P < 0.05). However, the mean value of the duration that the rat spent in the target quadrant was significantly higher in the D-gal + Met group (19.66 ± 2.16 s, P < 0.05) when compared with the D-gal group. However, its level is still significantly lower when compared with the control group (Fig. 2). In the elevated plus-maze test, the mean value of the duration that the rats spent in the open arms was significantly lower in the D-gal group when compared with the control group (60 ± 6.54 s vs. 90.83 ± 3.48 s, respectively, P < 0.05). On the other hand, the mean value of the duration that the rats spent in the open arms was significantly higher in the D-gal + Met group (73.83 ± 5.41 s, P < 0.05) when compared with the D-gal group. However, its level was still significantly lower when compared with the control group. On the contrary, the mean value of the duration that the rats spent in the closed arms was significantly higher in the D-gal group when compared with the control group (107.33 ± 3.07 s vs. 57.66 ± 5.12 s respectively, P < 0.05). The mean value of the duration that the rats spent in the closed arms was significantly lower in the D-gal + Met group (74.66 ± 2.58 s, P < 0.05) when compared with the D-gal group. However, its level was still significantly higher when compared with the control group. The mean value of the number of open-arm entries was significantly lower in the D-gal group when compared with the control group (12.50 ± 1.87 vs. 32.33 ± 3.07, respectively, P < 0.05). On the contrary, the mean value of the number of open-arm entries was significantly higher in the D-gal + Met group (21.66 ± 2.16, P < 0.05) when compared with the D-gal group. However, its level is still significantly lower when compared with the control group. The mean value of the duration of the transfer latency was significantly higher in the D-gal group when compared with the control group (48.33 ± 6.88 s vs. 25 ± 1.87 s, respectively, P < 0.05). While the mean value of the duration of the transfer latency was significantly lower in the D-gal + Met group (34.66 ± 3.77 s, P < 0.05) when compared with the D-gal group. However, its level was still significantly higher when compared with the control group (Fig. 3).
The mean value of brain MDA level was significantly higher, while the mean value of brain SOD level was significantly lower in the D-gal group when compared with the control group (70 ± 3.23 nmol/mg protein and 13.05 ± 1.86 U/mg protein vs 33.76 ± 2.13 nmol/mg protein and 29.11 ± 4.34 U/mg protein respectively, P < 0.05). The mean value of brain MDA level was significantly lower, while the mean value of brain SOD level was significantly higher in the D-gal + Met group (50.02 ± 4.26 nmol/mg protein and 21.90 ± 2.33 U/mg protein, respectively, P < 0.05) when compared with the D-gal group. However, the mean value of MDA is still significantly higher and the mean value of SOD significantly lower when compared with the control group (Fig. 4a,b). The mean value of brain TNF-α level was significantly higher, while the mean value of brain IL-10 level was significantly lower in the D-gal group when compared with the control group (67.50 ± 10.03 pg/mg protein and 72.91 ± 8.45 pg/mg protein vs. 16.61 ± 1.21 pg/mg protein and 157.23 ± 12.46 pg/mg protein, respectively, P < 0.05). The mean value of brain TNF-α level was significantly lower, while the mean value of brain IL-10 level was significantly higher in the D-gal + Met group (49.83 ± 1.89 pg/mg protein and 131.67 ± 4.54 pg/mg protein, respectively, P < 0.05) when compared with the D-gal group. But, the mean value of TNF-α was still significantly higher and the mean value of IL-10 significantly lower when compared with the control group (Fig. 4c,d). The mean value of brain BDNF level was significantly lower in the D-gal group when compared with the control group (125.72 ± 4.17 pg/mg protein vs. 225.20 ± 5.52 pg/mg protein, respectively, P < 0.05). The mean value of brain BDNF level was significantly higher in the D-gal + Met group (215.03 ± 3.65 pg/mg protein, P < 0.05) when compared with the D-gal group. However, its level is still significantly lower when compared with the control group (Fig. 5).
The expression of the AMPK and PI3k genes (0.52 ± 0.11and 0.37 ± 0.03, respectively, P < 0.05) was significantly down-regulated in the D-gal group when compared with the control group (1). However, the expression of AMPK and PI3k genes was significantly up-regulated in the D-gal + Met group (0.95 ± 0.08 and 0.98 ± 0.04, respectively, P < 0.05), when compared with the D-gal group, but it was insignificantly changed (P > 0.05) when compared with the control group (Fig. 6).
The H&E stain of hippocampal tissue in the control group revealed unremarkable pathological changes. The D-gal group showed much neuronal degeneration and apoptotic bodies with massive edema and gliosis. However, the D-gal + Met group sections showed few neuronal degenerations and few apoptotic bodies with mild edema and mild focal gliosis (Fig. 7).
The immunohistochemical results revealed that the H score value of synaptophysin expression in hippocampal tissue was significantly lower (P < 0.05) in the D-gal group when compared with the control group (100 ± 5.78 vs. 260 ± 4.03). However, the expression of synaptophysin (180 ± 5.26) in hippocampal tissue in the D-gal + Met group was significantly higher when compared with the D-gal group. However, it was still significantly lower when compared with the control group (Fig. 8). The H score value of the caspase-3 expression in hippocampal tissue was significantly higher (P < 0.05) in the D-gal group when compared with the control group (279 ± 5.35 vs. 89 ± 3.54). On the other hand, the H score value of the caspase-3 expression in hippocampal tissue in the D-gal + Met group (151 ± 4.73) was significantly lower when compared with the D-gal group, but still significantly higher when compared with the control group (Fig. 9). The H score value of Bcl-2 expression in hippocampal tissue was significantly lower (P < 0.05) in the D-gal group when compared with the control group (161 ± 4.36 vs. 301 ± 6.11). While the H score value of Bcl-2 expression in hippocampal tissue in the D-gal + Met group (179 ± 7.48) was significantly higher when compared with the D-gal group, but it was still significantly lower when compared with the control group (Fig. 10).
The increase in average life expectancy increases the risk of illness in the elderly, especially in the cognitive arena which might be, at least in part, due to neuronal loss in the brain. It is well accepted that the long-term injection of d-galactose contributes to the aging progress and slight neuronal damage and memory deficits. Since D-gal-induced aging is accompanied by neurodegeneration, it could be an ideal model for studying the molecular mechanisms involved with age-associated neurodegeneration and for testing new therapeutic approaches. Our study showed that chronic administration of D-gal impaired novelty-induced exploratory behaviors and working memory in rats. This was obvious in the results of the novel object, Morris water maze, and elevated plus-maze tests. These results were in line with other reported studies. On the other hand; treatment with metformin improved the working memory and preference for novelty when compared with the D-gal group. Supporting our results, a previous study reported that metformin improved short-term memory in streptozotocin-induced diabetic mice. It is well documented that aging is associated not only with a decline in cognitive functions but also with emotional changes including anxiety-like behavior which results in functional impairment. In the present study, EPM test results showed increased anxiety-like behavior in the D-gal group when compared with the control group. While treatment with metformin attenuated anxiety-like behavior. The present study revealed that neurobehavioral changes caused by oral administration of D-gal were accompanied by disturbances in brain oxidative stress markers. The mean value of MDA level in brain tissue homogenate was significantly higher, while the activity of the antioxidant enzyme SOD was significantly lower in the D-gal group when compared with the control group. Similar results were previously reported. D-gal interacts with various free amines in the protein architecture via non-enzymatic glycation, resulting in the generation of advanced glycation products. This results in the generation of ROS which increases brain aging via oxidative damage to DNA, lipids, and proteins. Memory loss and learning impairment induced by chronic administration of D-gal could be attributed to the generation of free radicals, resulting in impairment of neurogenesis and, ultimately, neurodegeneration. Moreover, brain neurons are more susceptible to oxidative stress due to the presence of high lipid content and higher oxygen consumption. On the contrary, metformin administration significantly restored the redox balance. Evidence demonstrated that metformin could inhibit the Mitochondrial Permeability Transitional Pore (mPTP) and reduce ROS production and lipid peroxidation. Therefore, this indicates that the anti-aging effect of metformin might be possibly mediated by its antioxidative defense. Besides oxidative stress, inflammation is also an important aging-inducing mechanism of D-gal treatment. D-gal promotes the generation of ROS that activate inflammatory pathways. Chronic neuroinflammation and secretion of pro-inflammatory cytokines is a hallmark of aging. There is an agreement that inflammatory cytokines are involved in oxidative stress. TNF-α, IL-6, and IL-1β are essential in the development and progression of oxidative stress. These cytokines are associated with ROS and activate Nuclear factor-κB (NF-κB) to translocate to the nucleus and regulate the expression of pro-inflammatory genes such as iNOS and COX2, which are involved in inflammatory and immune responses, and consequently leads to fibrosis, apoptosis, and acute phase responses that cause organ damage. The aforementioned data was consistent with our results, as the level of TNF-alpha was significantly higher, and IL-10 was significantly lower in the D-gal group compared with the control group. On the other hand, treatment with metformin resulted in a significant reduction in the inflammatory markers when compared with the D-gal group. The anti-inflammatory effects of metformin could be attributed to the activation of AMPK signaling, which suppresses inflammatory reactions via the inhibition of NF-κB. Also, it decreased pro-inflammatory cytokines production and microglial activation in the brain which, in turn, decrease oxidative stress. To further understand the molecular mechanisms underlying metformin actions, we examined the protein expressions of AMPK and PI3k. Our study revealed that the expression of AMPK was significantly down-regulated in the D-gal group when compared with the control group, while its level was significantly up-regulated in the metformin-treated group when compared with the D-gal group. Previous studies reported that the AMPK activation and AMPK responsiveness decrease with age, which may explain the altered metabolic regulation, resulting in reduced autophagy and an increase in oxidative stress. Metformin were found to activate AMPK by increasing the phosphorylation of AMPKα at Thr-172. AMPK is the primary target of metformin for its protective function against cognition disruption. Ghadernezhad et al. reported that metformin-induced activation of AMPK led to the activation of the BDNF/P70S6K pathway in hippocampal neurons to enhance the formation of memory in passive avoidance task in a global cerebral ischemia/reperfusion rat model. BDNF activation has a vital role in the regulation of neurocognitive functions like learning, memory, synaptic transmission, and plasticity. Several studies demonstrated that AMPK could act as a modulator of Long-Term Potentiation (LTP), and it is required for memory formation. Therefore, metformin-induced memory improvement in our study could be mediated through AMPK signaling activation. Also, activation of AMPK signaling suppresses inflammatory reactions via activating SIRT1, stimulating FOXO proteins and inhibiting ER stress, and reducing oxidative stress. All these mechanisms will subsequently repress NF-κB signaling and neuroinflammation associated with aging. In addition to its anti-inflammatory effects, AMPK is involved in various activities, including angiogenesis, autophagy enhancement, and mitochondrial protein induction. Although the AMPK-dependent protective roles in different contexts have been reported, the AMPK-independent manners of metformin are less studied. The present study revealed that there was significant down-regulation of the PI3K gene in the D-gal group when compared with the control group, while metformin co-administration led to the up-regulation of its level when compared with the D-gal group. PI3K/Akt is one of the important signaling pathways in cell apoptosis prevention. Activation of PI3K can be followed by Akt1 phosphorylation. Akt1 can inhibit the phosphorylation of JNK3 that promotes the activation of c-Jun. C-Jun is a protein that can induce the expression of apoptotic proteins. Thus, Akt1 activation will result in the inactivation of JNK3 and c-Jun, and, then the proportion of cell survival is improved. Therefore, we explored the effects of metformin on cellular apoptosis by studying the immunohistochemical reaction of the apoptotic markers caspase-3 and Bcl-2. This study revealed an increment in the expression of the apoptotic marker caspase-3 with a reduction of the expression of the anti-apoptotic marker Bcl-2 in the hippocampus of the D-gal group when compared with the control group. Supporting our results, previous studies confirmed that mitochondrial ROS induce the activation of a large number of mitochondrial apoptotic proteins, leading to cellular apoptosis and organ damage. Many apoptotic proteins are closely related to anti-apoptotic proteins in the aging induced by the injection of D-gal. Caspase-3 is known to be a key factor of apoptosis in mammals. The Bcl-2 protein is a key player in the inhibition of apoptosis. It is a known factor in cell aging, and its overexpression can effectively prevent the apoptosis induced by free radicals. It is commonly believed that Bcl-2 acts downstream of caspase-3 activation and, thus, apoptosis is inhibited. As shown in our results, metformin administration significantly decreases the Caspase-3/Bcl-2 ratio. These results were in accordance with other studies that suggest that activation of AMPK by metformin up-regulates the Bcl-2 protein expression so it protects against apoptotic cell death induced by D-gal and increases neuronal viability. BDNF is an interesting molecular candidate that could help establish a link between molecular and biochemical alterations and memory deficits associated with aging. Optimal cognitive function is linked to efficient neuronal plasticity. Memory deficits associated with aging might be coupled to alterations in the expression and regulation of plasticity-related proteins such as BDNF which is an important neurotrophic factor. It has been demonstrated that reduction of BDNF leads to neuronal atrophy and death. The present study revealed that BDNF level in the D-gal group was significantly lower when compared with the control group. A decrease in BDNF and/or its receptors in aging animals was evident in previous studies. Mizisin et al. suggested that galactose metabolism by aldose reductase influenced axonal function and structure by altering the production of nerve and muscle BDNF. On the contrary, treatment with metformin was associated with a significant increase in BDNF when compared with the D-gal group. Our results were in agreement with previously published reports which demonstrated that metformin up-regulates BDNF via AMPK activation. Due to its critical role in LTP, BDNF has been postulated to be an essential part of the cellular mechanism supporting memory formation and maintenance by promoting synaptic consolidation. BDNF increases memory storage by favoring changes in spine morphology leading to the stabilization of LTP. BDNF can also increase the number, size, and complexity of dendritic spines. Furthermore, BDNF increases neurogenesis through changes in cell proliferation. The binding of BDNF to TrkB receptors induces PI3K activity which inhibits apoptosis and promotes cell survival. Taken together, our study suggests that the anti-aging effects of metformin in improving neurocognitive impairment could be, at least in part, due to the activation of AMPK/BDNF/PI3K pathway. Hippocampus plays an important role in learning and memory consolidation as well as in behaviors and mood regulation, and where both functional and structural plasticity occur well into adulthood. Previous studies reported that hippocampus undergoes several structural changes both grossly and at the cellular level with aging. H & E study of the hippocampus in the D-gal group showed severe neuronal degeneration with multiple apoptotic bodies and gliosis. This result could be explained by the deleterious effects of d-galactose in the induction of oxidative stress, inflammation, and apoptosis. Additionally, we evaluated the expression levels of a synaptic marker protein (synaptophysin) in the hippocampus. Synaptophysin is a marker of synaptic plasticity. It is used as a specific marker for the presynaptic terminal, and its level is related to the synaptic density. Our results showed that the expression of synaptophysin was significantly lower in the D-gal group when compared with the control group. These results were in line with previously reported studies that demonstrated that D-gal-induced synaptogenesis impairment in the hippocampus. However, metformin co-treatment with D-gal restored the synaptophysin expression and hippocampal tissue structure to levels close to their respective control levels. Evidence has shown that metformin promotes rodent and human neurogenesis and enhances spatial memory formation. The increment in synaptic density and neurogenesis in the hippocampus goes hand in hand with the improvement in the neurobehavioral tests' results in this group. This could be explained by the antioxidant, anti-inflammatory, and antiapoptotic effects of metformin, which are mediated by activation of AMPK/BDNF/PI3K signaling pathway.
Our findings support the use of D-gal in the rat model to carry out aging-related studies. We concluded that metformin could alleviate memory impairment and cognitive deficit caused by aging. The mechanisms likely involved are amelioration of neuro-inflammation, attenuation of oxidative stress, enhancement of the expression of the anti-apoptotic protein Bcl-2, as well as the promotion of neurogenesis and synaptic plasticity. We believed that these mechanisms could be mediated via activation of the AMPK/BDNF/PI3K pathway. To the best of our knowledge this is the first study demonstrate the action of metformin on improving cognitive impairment in aged rats via activation of this pathway. Therefore, our findings suggest that metformin is a useful anti-aging agent. | true | true | true |
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PMC9556687 | Jian Wang,Liping Li,Xue Jiang,Bin Wang,Xiaodong Hu,Weiwei Liu,Ying Zhang | Silencing of long non-coding RNA TUC338 inhibits the malignant phenotype of nasopharyngeal cancer cells via modulating the miR-1226-3p/FGF2 axis | 12-10-2022 | TUC338,miR-1226-3p,FGF2,NPC | Long noncoding RNAs (lncRNAs) have been suggested as essential regulators in the cancer progression. LncRNA TUC338 was found to promote the malignancy of various cancers, however, the involvement of TUC338 in nasopharyngeal cancer (NPC) has not been well characterized. Here, our results found the significant overexpression of TUC338 in NPC tissues. Higher level of TUC338 was also observed in NPC cells. Interestingly, NPC patients harboring overexpressed TUC338 have worse prognosis. Functional study indicated that down-regulated TUC338 remarkably suppressed the NPC cell proliferation and cell migration. Notably, depletion of TUC338 significantly inhibited the in vivo tumor growth. Mechanistically, TUC338 acted as molecular sponge of miR-1226-3p and attenuated the negative regulation of miR-1226-3p on the expression of fibroblast growth factor 2 (FGF2). Down-regulation of TUC338 inhibited FGF2 expression in NPC cells and tumor tissues. Overexpression of FGF2 attenuated the suppressed NPC proliferation upon the depletion of TUC338. Our results demonstrated the novel function of TUC338/miR-1226-3p/FGF2 axis in NPC progression, suggesting the potential diagnosis and therapeutics significance of TUC338 in NPC. | Silencing of long non-coding RNA TUC338 inhibits the malignant phenotype of nasopharyngeal cancer cells via modulating the miR-1226-3p/FGF2 axis
Long noncoding RNAs (lncRNAs) have been suggested as essential regulators in the cancer progression. LncRNA TUC338 was found to promote the malignancy of various cancers, however, the involvement of TUC338 in nasopharyngeal cancer (NPC) has not been well characterized. Here, our results found the significant overexpression of TUC338 in NPC tissues. Higher level of TUC338 was also observed in NPC cells. Interestingly, NPC patients harboring overexpressed TUC338 have worse prognosis. Functional study indicated that down-regulated TUC338 remarkably suppressed the NPC cell proliferation and cell migration. Notably, depletion of TUC338 significantly inhibited the in vivo tumor growth. Mechanistically, TUC338 acted as molecular sponge of miR-1226-3p and attenuated the negative regulation of miR-1226-3p on the expression of fibroblast growth factor 2 (FGF2). Down-regulation of TUC338 inhibited FGF2 expression in NPC cells and tumor tissues. Overexpression of FGF2 attenuated the suppressed NPC proliferation upon the depletion of TUC338. Our results demonstrated the novel function of TUC338/miR-1226-3p/FGF2 axis in NPC progression, suggesting the potential diagnosis and therapeutics significance of TUC338 in NPC.
Nasopharyngeal cancer (NPC) is a most frequently diagnosed head and neck cancer mainly occurs in Southeast Asia, especially in China [1]. Currently, the main therapeutic strategies that surgery combined with chemotherapy or radiotherapy have substantially benefited the prognosis of patients [2]. However, NPC usually develops distant metastasis and progresses into poor outcomes. Therefore, identifying key factors involved in the progression of NPC is necessary to benefit the diagnosis and treatment of NPC. Increasing evidence has found that non-coding RNAs (ncRNAs) act importantly in the initiation and development of cancers [3–6]. MicroRNA (miRNAs) and lncRNAs are well defined two major classes of ncRNAs [7]. Specifically, lncRNAs are > 200 nucleotides (nt) in length and take up more than 98 percentage of transcriptomes [8]. Dysregulation of lncRNAs is closely involved in the oncogenesis and development of cancers [9]. As a big part of ncRNAs, miRNAs, with the length of approximately 22 nt, are dysregulated and modulate the tumorigenesis [10–12]. Mechanistically, miRNAs trigged the target mRNA degradation or translation defects through binding the mRNA’s 3′-untranslated region (UTR) [13, 14]. Generally, one of the functional mechanisms of lncRNA is to physically bind and sequester miRNA to attenuate its suppressive effect on targeted mRNAs. These lnRNAs are also named as competitive endogenous RNAs (ceRNAs) [15]. The cancer-promoting effects of LncRNA TUC338 have been identified in liver cancer and tongure squamous cell carcinoma [16, 17]. Highly expressed TUC338 promoted cancer cell proliferative and invasive capacities [18–21]. Nevertheless, the reports about the function of TUC338 in NPC is not available. Fibroblast growth factor (FGF2) is a prototypic growth factor belonging to the FGF family [22, 23]. Recent study demonstrated that FGF2 is a type of proto-oncogene that is expressed higher in many types of malignancies [24]. Overexpressed FGF2 in NSCLC promoted the progression of and was correlated with the poorer survival of NSCLC patents [25]. Regulatory mechanism by which FGF2 activity is regulated in NPC remains to be revealed. In this study, TUC338 was up-regulated in NPC and associated with the advanced progression of NPC patients. Mechanistically, TUC338 regulated FGF2 expression by sponging miR-1226-3p and modulated the NPC pathogenesis. Our results shed light on the promising therapeutic significance of TUC338/miR-1226-3p/FGF2 axis in NPC.
A cohort of clinical samples including 50 pairs of NPC tissues and their paired adjacent non-cancerous tissues were collected from NPC patients at the Cangzhou Central Hospital between January 2010 and August 2011. Participants were not undergone any treatments prior to the tissue collection. Tissues were stored in liquid nitrogen. The experimental procedures were approved by the Ethics Committee of Cangzhou Central Hospital (Approval Number: ECCCH20100892). Patients provided written informed consents.
CNE-1, HONE-1, SUNE-1, 5-8F cells, human nasopharyngeal epithelial NP69 cells were all purchased from ATCC (Manassas, VA, USA). The culture condition of the cells was RPMI-1640 medium plus 10% fetal bovine serum (FBS, Invitrogen, Shanghai, China) and 1% streptomycin/penicillin (Hyclone, South Logan, UT, USA) at 37 °C with 5% CO2. NP69 cells were maintained in keratinocyte/serum-free medium (Invitrogen, Shanghai, China) with bovine pituitary extract (Absin Bioscience Co., Ltd., Shanghai, China). All cells were incubated in a humidified CO2 (5%) incubator at 37 °C.
Total RNA from cells or tissues was generated into cDNA via reverse transcription with PrimeScript Reverse Transcriptase (RT) kit (Thermo Fisher Scientific, Inc.). qPCR was preformed to quantify the levels of TUC338 and miR-1226-3p with the SYBR Master Mix (Bio-Rad, USA). The levels of TUC338 or miR-1226-3p was normalized to that of GAPDH or U6 RNA, respectively. Primers used were TUC338 forward, 5′-GCAGCGACAGTGCGAGCT, reverse, 5′-TCCGAGTGAGTTAGGAAG; GAPDH forward, 5′-GGTCTCCTCTGACTTCAACA, reverse, 5′-GTGAGGGTCTCTCTCTTCCT; miR-1226-3p forward, 5′-GCGGCTCACCAGCCCTGTGT, reverse, 5′-CAGCCACAAAAGAGCACAAT; FGF2 forward, 5′-ACTGGCTTCTAAATGTGTTACG, reverse, 5′-TTGGATCCAAGTTTATACTGCC.
4–5 weeks of BALB/c mice (female) were obtained for Charles River Laboratories and housed at SPF conditions. 200 μl of NPC cells (1 × 106) with lentivirus expressed siRNA-TUC338 or siRNA-control were subcutaneously administrated into the flanks of mice. Tumors size was measured with the caliper at the interval of 5 days. After the tumor implantation of 30 days, cervical dislocation was applied to euthanize the mice and tumors were collected. The tumor length (a) and width (b) was measure. The tumor volume (V/mm3) was calculated with the formula V = ab2/2. This experiment was approved in accordance with the regulations of Committee the Cangzhou Central Hospital Experimental Animal Use and Care. The maximal tumour size/burden permitted by the ethics was no more than 2000 mm3. The maximal tumour size was not exceeded 2000 mm3 in this study.
Equal amount of protein extracted form NPC cells was separated through running SDS-PAGE and semi-dry transferred onto the 0.22 μm nitrocellulose membrane (Real-Times Biotechnology Co., Ltd., Beijing, China). The membrane was firstly pre-sealed with 5% skim milk followed by incubating with specific primary antibody against FGF2 (1:1500 dilution; #ab92337, Abcam, USA) or GAPDH (1:2000 dilution; #ab181602; Abcam, USA) overnight at 4 °C. The signals were further developed using IRdye 800-conjugated anti-IgG second antibody (1:3000 dilution; Invitrogen, USA) for 1 h at RT and detected with the ECL Western Blotting Substrate (Pierce, Thermo Fisher Scientific, Inc).
The TUC338 fragment carrying the predicted miR-1226-3p seeding sites were PCR-amplified and constructed into the pmirGLO plasmid. pmirGLO-TUC338 and miR-1226-3p or control miRNA were co-transfected into the NPC cells. The luciferase activity was examined after 48 h of transfection using the Dual-Luciferase Assay Kit (Promega, Madison, WI, USA).
Control-siRNA or siRNA-TUC338 were transfected into NPC cells and cell proliferation was determined by the Cell Counting Kit-8 (CCK-8) assay (Quanxinquanyi Biotech, Shanghai, China) following the protocol of the manufacturer. Specifically, NPC cells were seeded into the 96-well plate (1000 cells/well). After incubating with 10 μl of CCK-8 for 3 h, the cell proliferation was measured using the microplate reader at the absorbance of 450 nm.
NPC cells were cultured in a 6-well plate and transfected with control-siRNA or TUC338-siRNA. After 36 h of the transfection, the cell cycle profile was examined by staining with propidium iodide (PI; Solarbio, Beijing, China). Briefly, the fixation with 75% ethanol was performed overnight at 4 °C. Cells were then subjected to RNase digestion for 15 min at RT and stained by PI for 20 min avoiding light. After filtering with 200-mesh membrane, the cell cycle of NPC cells was analyzed with the flow cytometry (Beckman Coulter, Epics XL).
The cell lysates were incubated with Argonaute 2 (Ago 2) antibody at 4 °C overnight. Protein G beads were added to couple the antibody. The IP complex was treated with proteases K followed by RNA extraction. The enrichment of TUC338 was detected by RT-qPCR. For the pull-down assay, the antisense oligonucleotides that recognizing TUC338 or LacZ were conjugated to biotin and incubated with the CNE-1 or 5-8F cell lysates. The biotinylated components were further captured by streptavidin beads (Invitrogen, Shanghai, China). RNA was extracted from the pull-down components and detected by RT-qPCR analysis using the primers against miR-1226-3p.
SPSS version 19.0 was used for the statistical analysis. Data was presented as the mean ± standard deviation. Difference between two groups was analyzed with Student’ t test. Multi-sample comparison was performed with One-way ANOVA. Statistical significance was defined when p < 0.05. *p > 0.05, **p > 0.01, ***p > 0.001.
To investigate whether TUC338 was involved in NPC progression, TUC338 expression in NPC tissues and matched non-cancer tissues was detected. As confirmed by the data of RT-qPCR, TUC338 was significantly overexpressed in NPC using the normal tissues as control (Fig. 1A). Meanwhile, TUC338 expression in NPC cell lines and normal cells was also compared. The data indicated the relative higher level of TUC338 in NPC cells (Fig. 1B). To deeply evaluate the clinical value of TUC338, those 50 patients were divided into TUC338-low and high expression groups based on the mean expression value of TUC338. Correlation analysis showed that patients with poorer survival had higher level of TUC338 (Fig. 1C). These findings suggested the potential clinical significance of TUC338 for the prognosis of NPC patients.
As TUC338 was aberrantly expressed in NPC, to reveal the role of TUC338 in NPC, both CNE-1 and 5-8F cells were transfected with siRNA-TUC338 or siRNA-control, and the knock down efficiency of TUC338 was confirmed as indicated in Fig. 2A. The data of CCK-8 assay demonstrated that depletion of TUC338 significantly slowed the NPC cell proliferation (Fig. 2B and C). The effects of TUC338 on the growth of NPC cells were also validated by analyzing the cell cycle progression with the down-regulation of TUC338. Depletion of TUC338 significantly induced the accumulation of cells in G1 phase and reduction in S phase (Fig. 2D), suggesting G1 cell cycle arrest with knockdown of TUC338. Consistently, down-regulation of TUC338 obviously increased the apoptotic percentage of both CNE-1 and 5-8F cells (Fig. 2E). Additionally, the effects of TUC338 on NPC cell migration was also determined via the transwell assay, which showed that depletion of TUC338 significantly inhibited the migration of NPC cells (Fig. 2F). Collectively, all these results demonstrated that TUC338 was required for the malignant phenotype of NPC cells.
To confirm the function of TUC338 in tumorigenicity in vivo, xenograft mice model was established by subcutaneously injecting both CNE-1 and 5-8F cells with stably expressed siRNA-TUC338 or siRNA-control. After 30 days, mice were sacrificed to harvest the tumors and the tumor weight was measured. The knockdown efficiency of TUC338 in tumors was confirmed by RT-qPCR (Fig. 3A). Significantly reduced tumor volume and weight were observed with TUC338 knocked down (Fig. 3B–D). These results demonstrated the repressed in vivo tumor formation with down-regulation of TUC338.
Base on the theory of ceRNA, to further understand the molecular mechanism of TUC338 in NPC, the binding between TUC338 and miRNAs were predicted with the miRDB database. According to the bioinformatics analysis, TUC338 might be a molecular sponge of miR-1226-3p among all the candidates. The putative binding sequence between TUC338 and miR-1226-3p was presented as Fig. 4A. To confirm this, the data of luciferase assay suggested that the luciferase intensity of NPC cells expressing WT-TUC338 was significantly decreased with miR-1226-3p overexpression (Fig. 4B and C). However, transfection of miR-1226-3p did not affect the luciferase activity of cells expressing mutated TUC338 that disrupted the binding with miR-1226-3p (Fig. 4B and C). Moreover, the Ago2-IP assay showed the significant enrichment of TUC338 in Ago2-IP compared to control IgG-IP (Fig. 4D). RNA pull-down assay revealed that TUC338 was specifically enriched in pull-down components using TUC338 antisense oligonucleotides but not with LacZ (Fig. 4E). miR-1226-3p was selectively enriched in TUC338 pull down assay (Fig. 4E). These findings indicated the specific physical interaction of TUC338 with miR-1226-3p. To detect whether the interaction of TUC338 affected miR-1226-3p expression, the levels of miR-1226-3p in both 5-8F and CNE-1 cells were detected. The RT-qPCR analysis showed that TUC338 overexpression significantly decreased the expression of miR-1226-3p (Fig. 4F). Consistently, down-regulated TUC338 increased miR-1226-3p expression in NPC cells (Fig. 4G). As TUC338 was overexpressed in NPC tissues, the abundance of miR-1226-3p was also detected. Compared with the non-caner samples, miR-1226-3p was remarkably down-regulated in NPC tissues (Fig. 4H). Meanwhile, negative correlation for the levels of TUC338 and miR-1226-3p was also found in NPC (Fig. 4I). Collectively, TUC338 sponged miR-1226-3p in NPC.
Previous studies demonstrated the tumor inhibitory role of miR-1226-3p in the progression of cancers, while the regulatory function of miR-1226-3p in NPC remains unclear. To investigate the involvement of miR-1226-3p in modulating the growth of NPC cells, NC-miRNA or miR-1226-3p mimics were transfected into the cells (Fig. 5A). miR-1226-3p overexpression significantly inhibited NPC cell proliferation cells (Fig. 5B and C), indicating the suppressive function of miR-1226-3p in NPC. To deeply understand the molecular mechanism by which miR-1226-3p regulated NPC cell growth, the potential miR-1226-3p targets were searched via bioinformatics analysis. The results showed that FGF2 containing presumed binding sites of miR-1226-3p (Fig. 5D). As indicated by the luciferase assay, miR-1226-3p overexpression notably decreased the luciferase activity of NPC cells expressing WT but not mutant 3’-UTR of FGF2 (Fig. 5E and F). To evaluate the influence of miR-1226-3p on the expression of FGF2, RT-qPCR and western blot assays were carried out after the transfection of NC-miRNA or miR-1226-3p. miR-1226-3p overexpression reduced both the mRNA and protein levels of FGF2 in CNE-1 and 5-8F cells (Fig. 5G and H). These findings indicated that FGF2 served as a target of miR-1226-3p in NPC. Additionally, FGF2 expression was also detected by RT-qPCR, which exerted a significant enrichment in NPC tissues compared with non-cancerous tissues (Fig. 5I). FGF2 abundance was negatively correlated with miR-1226-3p, but positively correlated with TUC338 in NPC (Fig. 5J and K).
To determine whether FGF2 mediated the role of TUC338 in NPC, we first detected the expression of FGF2 with depletion of TUC338. The data showed that transfection of siRNA-TUC338 markedly decreased the mRNA level of FGF2 (Fig. 6A). Meanwhile, the protein expression of FGF2 was also down-regulated with the depletion of TUC338 (Fig. 6B). Moreover, the FGF2 level in xenograft mouse tumor tissues was also detected. As shown in Fig. 6C and D, both the mRNA and protein abundance of FGF2 in tumors harboring depleted TUC338 was significantly decreased with tumors expressing siRNA-control as the control. These findings demonstrated that knockdown of TUC338 inhibited the expression of FGF2 both in vivo and in vitro. To demonstrate whether TUC338 regulated NPC cell proliferation via FGF2, the expression of FGF2 was overexpressed by transfecting pcDNA-FGF2 into NPC cells (Fig. 6E and F). CCK-8 assay was performed after cells were transfected with siRNA-TUC338 and pcDNA-FGF2. As indicated in Fig. 6G and H, up-regulation of FGF2 significantly attenuated the reduced proliferation of NPC cells induced by TUC338 depletion. Consistently, restoration of FGF2 also markedly reversed TUC338 knockdown-induced NPC cell apoptosis (Fig. 6I). These results demonstrated that TUC338 modulated the malignancy of NPC cells at least via regulating FGF2 by sponging miR-1226-3p.
Accumulating data have suggested the active participation of lncRNAs in various physiological conditions and contribute greatly to the oncogenesis of cancers [3, 5]. Abnormal expression of lncRNA has been found in NPC [26, 27]. In the current study, TUC338 was overexpressed in NPC tissues and cells. Highly expressed TUC338 was correlated with NPC patients’ poorer survival. Results of functional experiments indicated that down-regulation of TUC338 significantly inhibited the NPC cancer development and therefore serves as a potential oncogenic lncRNA in NPC. It is well established that the biological function of lncRNAs depends on the miRNAs and proteins to which they bind [4]. Our results revealed a new miRNA target for TUC338, miR-1226-3p, which has been shown to be involved in the pathogenesis of cancers. The interacting of TUC338 decreased the level of miR-1226-3p in NPC cells. Consistent with the overexpression of TUC338, miR-1226-3p was obviously reduced in NPC samples with the non-cancer adjacent tissues as the control. Previous reports have showed the tumor inhibitory function of miR-1226-3p in the progression of cancers [28, 29]. In this study, overexpressed miR-1226-3p reduced the viability of NPC cells, suggested the negative role of miR-1226-3p in NPC. The essential roles of FGF2 has been reported in cancer progression [30–32]. Highly expressed FGF2 was associated with the unfavorable prognosis of lung cancer patients [33]. To deeply understand the function of miR-1226-3p in NPC, the targets of miR-1226-3p were predicted and FGF2 was found as a candidate. MiR-1226-3p bound FGF2 3′-UTR and decreased its level in NPC. Interestingly, accumulating evidence demonstrated that FGF2 was targeted by different miRNAs and regulated tumorigenesis [34–38]. For example, miR-889-3p inhibited the viability and invasive capacities of cervical cancer cells through directly inhibiting FGF2 [38]. FGF2 was regulated by miR-497-5p and inhibited the proliferation of NSCLC cells [37]. In this study, consistent with the negative regulation of miR-1226-3p by TUC338, down-regulation of TUC338 significantly decreased the level of FGF2. Restoration of FGF2 reversed the suppressive function of TUC338 in NPC cell proliferation and apoptosis. These results uncovered the functional mechanism of TUC338/miR-1226-3p/FGF2 pathway in the progression of NPC.
Our findings demonstrated the overexpression of TUC338 in NPC. Down-regulation of TUC338 inhibited NPC tumorigenesis both in vitro and in vivo. Functional analysis suggested that TUC338 exerted its potential oncogenic role partially via the miR-1226-3p/FGF2 axis. These findings indicated the potential application of TUC338 in the diagnosis and therapy of NPC. | true | true | true |
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PMC9556718 | Dengna Lin,Hao Chen,Jing Xiong,Jing Zhang,Zhaoxia Hu,Juan Gao,Bin Gao,Shaoquan Zhang,Junfeng Chen,Huijuan Cao,Zhihui Li,Bingliang Lin,Zhiliang Gao | Mesenchymal stem cells exosomal let-7a-5p improve autophagic flux and alleviate liver injury in acute-on-chronic liver failure by promoting nuclear expression of TFEB | 12-10-2022 | Autophagy,Mesenchymal stem cells | Acute-on-chronic liver failure is a distinct clinical syndrome characterized by a dysregulated immune response and extensive hepatocyte death without satisfactory therapies. As a cytoplasmic degradative and quality-control process, autophagy was implicated in maintaining intracellular homeostasis, and decreased hepatic autophagy was found in many liver diseases and contributes to disease pathogenesis. Previously, we identified the therapeutic potential of mesenchymal stem cells (MSCs) in ACLF patients; however, the intrinsic mechanisms are incompletely understood. Herein, we showed that MSCs restored the impaired autophagic flux and alleviated liver injuries in ACLF mice, but these effects were abolished when autophago-lysosomal maturation was inhibited by leupeptin (leu), suggesting that MSCs exerted their hepatoprotective function in a pro-autophagic dependent manner. Moreover, we described a connection between transcription factor EB (TFEB) and autophagic activity in this context, as evidenced by increased nuclei translocation of TFEB elicited by MSCs were capable of promoting liver autophagy. Mechanistically, we confirmed that let-7a-5p enriched in MSCs derived exosomes (MSC-Exo) could activate autophagy by targeting MAP4K3 to reduce TFEB phosphorylation, and MAP4K3 knockdown partially attenuates the effect of anti-let-7a-5p oligonucleotide via decreasing the inflammatory response, in addition, inducing autophagy. Altogether, these findings revealed that the hepatoprotective effect of MSCs may partially profit from its exosomal let-7a-5p mediating autophagy repairment, which may provide new insights for the therapeutic target of ACLF treatment. | Mesenchymal stem cells exosomal let-7a-5p improve autophagic flux and alleviate liver injury in acute-on-chronic liver failure by promoting nuclear expression of TFEB
Acute-on-chronic liver failure is a distinct clinical syndrome characterized by a dysregulated immune response and extensive hepatocyte death without satisfactory therapies. As a cytoplasmic degradative and quality-control process, autophagy was implicated in maintaining intracellular homeostasis, and decreased hepatic autophagy was found in many liver diseases and contributes to disease pathogenesis. Previously, we identified the therapeutic potential of mesenchymal stem cells (MSCs) in ACLF patients; however, the intrinsic mechanisms are incompletely understood. Herein, we showed that MSCs restored the impaired autophagic flux and alleviated liver injuries in ACLF mice, but these effects were abolished when autophago-lysosomal maturation was inhibited by leupeptin (leu), suggesting that MSCs exerted their hepatoprotective function in a pro-autophagic dependent manner. Moreover, we described a connection between transcription factor EB (TFEB) and autophagic activity in this context, as evidenced by increased nuclei translocation of TFEB elicited by MSCs were capable of promoting liver autophagy. Mechanistically, we confirmed that let-7a-5p enriched in MSCs derived exosomes (MSC-Exo) could activate autophagy by targeting MAP4K3 to reduce TFEB phosphorylation, and MAP4K3 knockdown partially attenuates the effect of anti-let-7a-5p oligonucleotide via decreasing the inflammatory response, in addition, inducing autophagy. Altogether, these findings revealed that the hepatoprotective effect of MSCs may partially profit from its exosomal let-7a-5p mediating autophagy repairment, which may provide new insights for the therapeutic target of ACLF treatment.
Acute-on-chronic liver failure (ACLF) is featured with acute decompensation of liver function in patients with chronic liver diseases. Unlike decompensated cirrhosis, ACLF is characterized by submassive or massive hepatocyte necrosis/apoptosis and uncontrolled systemic inflammation, followed by multiple organ failures and extremely high mortality within 28 days [1, 2]. Despite extensive efforts and significant improvement in ACLF treatment, the conventional therapeutic interventions, including nucleoside antiviral drugs, artificial liver support system, and liver transplantation, are not yet satisfactory due to the poor response and lack of donor livers [3–5]. Thus, searching for more effective treatment strategies has become an urgent issue to be resolved. In recent years, significant attention has focused on the potential use of mesenchymal stem cells (MSCs) for improving the treatment of inflammatory and degenerative diseases due to their unique immune-regulatory and regenerative capacity [6, 7]. Our previous study showed that MSCs transplantation could obviously improve the short-term survival rate and reduce the incidence of complications such as severe infection in ACLF patients [8], but certain obstacles (e.g., low cell survival and migrating rate, cell senescence) remain to be overcome [9–12]. As newly discovered 30–120 nm small diameter vesicles, exosomes are thought to be secreted by MSCs and mediate their therapeutic effect through transferring contents of miRNA and proteins to the recipient cells. In addition, compared with MSCs, exosomes have the same immune-modulative function and gain the advantage of liver distribution, avoiding the problem of aging or rejection in the application of its cellular counterparts [13–16]. Therefore, the determination of hepatoprotective components in exosomes derived from MSCs (MSC-Exo) may provide a new strategy for ACLF treatment. Autophagy, is an evolutionarily conservative cellular adaptive response against intra- or extracellular stress or stimuli, by which damaged organelles or misfolded proteins were degraded and recycled for ATP production and protein synthesis to facilitate cell survival and homeostasis [17]. Previous studies indicated that under conditions of mild hepatic injury, the autophagic signaling cascade can be activated to protect cells from death; however, in the case of more severe or prolonged liver damage, autophagy seems to be inhibited [18], which is contradictory to the view that autophagy would be quickly induced under pathological conditions. In this regard, if and how the autophagic function is affected under the condition of ACLF is not clear and needs to be further explored. Meanwhile, multiple studies demonstrated the hepatoprotective effect of MSCs transplantation could be mediated by regulating autophagy and reducing the inflammatory response in case of liver fibrosis or acute liver injury [19, 20]; however, whether autophagy is involved in the protective effect of MSCs therapy for ACLF and the specific mechanism is not known. Hence, in this study, we aim to investigate whether the biological effect of MSCs therapy on ACLF was due to the regulation of autophagy and determine the related molecular mechanism. Finally, we present evidence that the administration of MSCs restored the impaired autophagic flux by inducing the formation of autolysosomes and therefore protecting hepatocytes from death in vivo in ACLF mice. Mechanistically, we identified that the let-7a-5p, which is enriched in exosomes, could mediate the autophagy regulation of MSCs by promoting the nuclear translocation of transcription factor EB (TFEB) and inducing the expression of lysosome genes.
All animal experiments applied in this study were conducted with the approval of the Laboratory Animal Ethics Committee of Guangzhou Forevergen Biosciences. C57BL/6, B6 mice (male, 4–6 weeks, weighting 18–22 g) were purchased from the Guangdong Medical Laboratory Animal Center (Guangdong, China) and assigned randomly to groups. All mice were housed in specific pathogen-free conditions and exposed to a 12 h daylight/darkness environment, allowing unlimited access to food and water. To establish of ACLF model, the mice were intraperitoneally injected with 10% carbon tetrachloride (CCl4, #319961, Sigma, USA, 5 ml/kg body weight) twice a week for 8 consecutive weeks, and challenged with a single dose of 50% carbon tetrachloride (8 ml/kg) in day 3 of week 8 (ACLF group). The control mice were intraperitoneally injected with the same amount of olive oil at the same time (Sham group). After the establishment of the ACLF model, mice were further divided into two groups, which were infused with MSCs (1 × 105, resuspended in sterile saline (NS)) (ACLF + MSC group) or saline via tail vein. For in vivo autophagy flux measurements, we intraperitoneally injected mice with Leu (#HY-18234A, MCE, USA, 20 mg/kg body weight) or phosphate buffer solution (PBS) [21].
The MSCs (human bone marrow mesenchymal stem cells) were obtained from the Human Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Guangzhou, Guangdong, China. The identification and characterization methods of MSCs were performed as previously described [6]. Exosomes were isolated by ultracentrifugation and analyzed for nanoparticle tracking analysis (NTA), and the protein markers and morphology were detected by western blot and scanning electron microscope (SEM), respectively (Fig. S1A and S1C). In brief, MSCs in the fifth generation were seeded in T75 cm2 flasks and cultured in low-glucose Dulbecco’s modified Eagle medium (DMEM) with 10% fetal bovine serum (FBS) and 100 ug/mL penicillin-streptomycin. After reaching 50–60% confluence, MSCs were washed by PBS, then the fresh low-glucose DMEM with exosome-depleted FBS was added and cultured for another 48 h. The collected supernatant was centrifuged at 2000 × g for 20 min at 4 °C and then 10,000 × g for 40 min at 4 °C to remove cell debris and separate microvesicles. Then, the supernatant was transferred to ultracentrifuge tubes and centrifuged twice at 100,000 × g for 90 min at 4 °C to obtain exosomes [22]. Exosomes were resuspended in 100 µL PBS and stored at −80 °C.
A normal human liver cell line of L02 cells was purchased from iCell Bioscience Inc (Shanghai, China) and cultured in high-glucose DMEM with 10% FBS and 100ug/mL penicillin-streptomycin. To the establishment of in vitro C/I model, which mimics the severity of liver injury in ACLF, L02 cells were treated with 50 μM carbon tetrachloride for 3 h (C/I group), during performing autophagic flux assay, 100 μM leupeptin was added to block lysosomal proteolysis at 4 h before protein extraction [23]. For the in vitro MSCs and exosome treatment experiment, MSCs were inoculated in the upper transwell chambers (0.4 μm, Corning, USA) of six-well plates and co-cultured with L02 cells at a 2:1 ratio for 18 h (C/I + MSC group) (Fig. S1D). Exosomes were added directly to the culture medium of L02 cells at a ratio of 2 ug /1 × 105 recipient cells and cultured for another 18 h (C/I + MSC-Exo group). To prevent exosome secretion, MSCs were pretreated with the phospholipase inhibitors GW4869 (20 μM) (#D1692, Sigma, USA) for 12 h.
All data were expressed as Mean ± SD, the student t-test was applied to compare two groups of quantitative data, while three or more groups of quantitative data were compared by One-way ANOVA combined with Bonferroni multiple comparison test. P-values < 0.05 were considered statistically significant, and SPSS 22.0 and GraphPad Prism 8.0 were used for statistical analysis.
We previously identified that MSCs can improve the survival rate of ACLF patients. In order to investigate whether the improvement of ACLF by MSCs transplantation was associated with autophagic activity modulation, we first established a murine ACLF model which mimics the pathogenesis of clinical settings by administering CCl4 (Fig. 1A) and evaluated the therapeutic effects of MSCs. In macroscopic views, the liver tissue of mice in the model group exhibited a brown appearance, uneven surface with nodular protrusions of different sizes, and a hard texture (Fig. S1E). Histopathological analysis of the liver of ACLF mice revealed disrupted architecture, obvious fibrosis, massive hepatocyte necrosis, and portal/periportal inflammation occurred throughout the lobules, as we previously reported [24]. As shown in Figs. S1F and 1G, MSCs were successfully isolated, osteogenic and lipogenic differentiation was induced, and flow cytometry verified that MSCs used in our study were concordant with the definition of MSCs [6]. Next, we evaluated the hepatoprotective effect of MSCs, and found that significantly reduced mortality of ACLF mice, visually decreased mRNA expression of TNF-α, IFN-γ, IL-6, and IL-1β in the liver (Fig. 1B), and serum AST and ALT levels can be seen after 24 h of MSCs administration (Fig. 1C). Furthermore, the hepatic necrosis in the lobules was also significantly mitigated by MSCs transplantation, which can be seen at 6 h and became more evident at 24 h (Fig. 1D, E), in lines with H&E staining, the result of TUNEL assay confirmed that cell death rate was markedly reduced after 6 h of MSCs therapy. (Fig. 1F, G). To examine the effect of MSCs on autophagy, we first analyzed the molecular changes in the autophagy proteins LC3 (a marker of autophagosomes) and p62 (autophagic degrade substrates). Notably, the IHC staining in liver tissue of ACLF mice showed that the levels of LC3 and p62 were obviously decreased after 6 h of MSCs transfusion (Fig. 2A, B). Moreover, the results of the western blot also revealed a significant reduction in LC3 and p62 expression has occurred after 6 h of MSCs treatment (Fig. 2C, D). The lack of p62 accompanied by reduced expression of LC3-II indicated enhanced autophagic degradation activity in the late stages of autolysosome processing [25].
To verify the late stage of autophagy, which autophagosomes were fused with lysosomes to form autolysosomes, was promoted by MSCs, and transmission electron micrography (TEM) was performed [25]. As shown in Fig. 2E, F, compared to ACLF group, the number of autolysosomes in the liver was substantially increased, and autophagosomes decreased in ACLF + MSC group. In addition, the pharmacological flux assays using protease inhibitor leupeptin to block the formation of autolysosomes also showed the LC3-II accumulation (Fig. 2G, H) was significantly greater in ACLF + MSC group than ACLF group. These results are indicative of autolysosome formation being blocked in ACLF and thus leading to the accumulation of autophagosomes, and the above scenarios were gradually reversed after administration of MSCs [25]. Multiple studies demonstrated the application of mCherry-eGFP-LC3 construct could monitor the autophagic flux by detecting the relative intensity of red/green light spots, in brief, the yellow puncta were a combination of GFP and RFP fluorescence which represent autophagosomes, whereas red puncta whose acidic pH quenches GFP fluorescence represent autolysosomes [26, 27]. For a further intuitively observation of the effect of MSCs on autophagic flux, an in vitro model that mimics the severity of liver injury in ACLF was established (C/I model), Based on the result of half lethal concentration (LD50), we chose a 3 h treatment with carbon tetrachloride 50 µM as the optimal condition for subsequent experiments (Fig. 3A). In accordance with in vivo experiments, the result of TUNEL assay and flow cytometry demonstrated that cell death was reduced in MSCs co-cultured C/I L02 cells (Figs. 3B through 3D), furthermore, mRNA levels of TNF-α, IFN-γ, IL-6 and IL-1β in cells were also markedly decreased in C/I + MSC group (Fig. S1H). Notably, the results of genetic flux assays using mCherry-eGFP-LC3 lentivirus transfected L02 hepatocytes showed persistence of green puncta in the condition of lethal liver injury, administration of MSCs significantly increased the red puncta and resulted in the quenching of the green fluorescence (Fig. 3E, F), suggested the late stage of autophagy was repaired, and fusion of autophagosomes into lysosomes was promoted by MSCs.
To determine the hepatoprotective effects of MSCs were dependent on autophagic flux regulation, we next treated each group of mice with leupeptin (Leu), a protease inhibitor that blocked the formation of autolysosomes, and detected the change in liver injury and hepatocellular death. Apart from the sharply reduced survival rates (Fig. 3G), administration of Leu could significantly reverse the effect of MSCs on serum levels of transaminase (AST and ALT) and mRNA levels of TNF-α, IFN-γ, IL-6, and IL-1β in the liver (Fig. S1I and S1J). Moreover, results of TUNEL assay showed the number of dead cells was obviously increased after Leu treatment (Fig. 3H, I), suggesting the therapeutic effect of MSCs in ACLF mice was dampened by inhibiting the formation of autolysosomes.
To understand the mechanism by which MSCs enhanced the synthesis and function of autolysosomes, we then performed western blot to detect the nuclear and cytoplasmic expression of transcriptional factor EB (TFEB), which was shown to regulate lysosomal biogenesis and autophagy upon its translocation into the nucleus and activate the transcription of the related genes [25, 28]. In our study, we found that transfusion of MSCs could increase nuclear translocation of TFEB in ACLF primary hepatocytes (Fig. 4A, B). Notably, as shown in Fig. 4C, MSCs administration could induce the expression of lysosomes and autophagy-related genes, which seems to be partially contradicted by the expression of LC3-II protein reported above but laterally reflected the enhancement of degradative function and involvement of TFEB. Additionally, in vitro data of fluorescence staining validated that MSCs co-culture can stimulate the nuclear translocation of TFEB in C/I cells (Fig. 4D, E). To specifically verify whether TFEB is required for the MSC-mediated repairment of autophagic flux, we silenced TFEB in L02 hepatocytes by transfecting with TFEB shRNA adenovirus. As shown in Fig. 4F through I, TFEB silencing not only attenuated MSCs-induced accumulation of LC3-II proteins with leupeptin but also reduced the number of red puncta in mCherry-eGFP-LC3 transfected L02 hepatocytes co-cultured with MSCs. Furthermore, the number of TUNEL-positive cells and mRNA levels of TNF-α, IFN-γ, IL-6, and IL-1β in C/I + MSCs group were obviously increased after TFEB was knockdown (Fig. 4J through L). These suggested that TFEB is a critical mediator for MSCs repairs the autophagic flux, and alleviates liver injury in ACLF.
Next, we investigated whether the increase in TFEB nuclei expression after transfusion of MSCs is partially mediated by mesenchymal stem cell (MSC) derived exosomes (MSC-Exo), GW4869 sphingomyelinase inhibitors were applied to block the secretion of exosomes from MSCs and found an obviously decreased nuclear translocation of TFEB in co-cultured L02 hepatocytes administered GW4869 (Fig. 5A, B). To determine the components of exosomes responsible for MSC-Exo regulating TFEB expression, exosomal miRNA-seq analyses were performed to select the candidate miRNA. The seq-data suggested that miR-100-5p, let-7a/b/i-5p, miR-125a/b-5p, miR-99b-5p, miR-92a-5p, and miR-10a/b-5p were the top ten enriched miRNAs in MSC-Exo (Table S2 and Fig. 5C). Among of the miRNAs mentioned above, let-7a-5p was lately reported to significantly decreased in ACLF patients and associated with 30-day mortality of patients [29]. We, therefore, supposed that the transfer of let-7a-5p to the recipient hepatocytes by exosomes may mediate the therapeutic effect of MSCs, and thus the regulatory role of let-7a-5p on TFEB nuclear translocation and autophagic flux was addressed. As shown in Fig. 5D, the results of quantitative polymerase chain reaction analyses validated that let-7a-5p was reduced in ACLF mice, and MSCs treatment can significantly upregulate its expression in primary hepatocytes of ACLF mice. Furthermore, in vitro co-culture model revealed that the levels of let-7a-5p in L02 cells with MSCs co-cultured markedly decreased after applying GW4869 (Fig. 5E), which indicated that MSCs increased levels of let-7a-5p in ACLF was partially through the transfer of exosomes. To determine if there is an association between the increased let-7a-5p levels and nuclear translocation of TFEB and autophagic flux repairment, we first pretreated MSC-Exo with let-7a-5p inhibitor (i.e., MSC-Exoanti-let-7a-5p) or a negative control oligonucleotide (i.e., MSC-Exonc). The result of immunofluorescence staining showed that compared with MSC-Exonc group, nuclear translocation of TFEB was abolished in MSC-Exoanti-let-7a-5p group (Fig. 5F, G). Meanwhile, the western blot assays demonstrated pretreatment with let-7a-5p inhibitor failed to induce the accumulation of LC3II after application of Leu compared with the negative control oligonucleotide treatment group (Fig. 5H, I). In addition, the knockdown of let-7a-5p in exosomes abolished the hepatoprotective effect of MSC-Exo or MSC-Exonc (Fig. 5J, K). Taken together, the above data confirmed that MSCs mediate TFEB nuclear translocation and autophagic flux repairment partially via exosomal delivery of let-7a-5p, thereby dampening liver injury in ACLF.
To verify the mechanism by which MSC-Exo derived let-7a-5p induced nuclear translocation of TFEB, alteration in signaling pathways correlated with TFEB subcellular localization was investigated. The result of western blot showed the levels of phosphorylated TFEB were significantly lower in ACLF + MSC group mice, which suggested that MSCs could promote the transport of TFEB to the nucleus by dephosphorylation (Fig. 6A, B). Previous studies showed activity of TFEB nuclear translocation was mainly dependent on the levels of TFEB phosphorylation, and the mechanism target of MTOR and ERK are the two main signaling pathways leading to phosphorylation of TFEB [30–33]. Thus, in the present study, we next examined whether the regulation of TFEB nuclear expression by MSC-Exo derived let-7a-5p is related to the phosphorylation of the above pathway. As shown in Fig. 6C, D, concomitant with increased TFEB phosphorylation levels at Ser211, phosphorylated MTOR levels were also dramatically upregulated in groups of cells were treated with MSC-Exoanti-let-7a-5p. However, phosphorylated ERK1/2 levels were not significantly different between the groups. Next, the bioinformatic database Targetscan was applied to explore the specific target of let-7a-5p, which may involve in the phosphorylation of MTOR, and we found that 3’ UTR of MAP4K3, which was reported to activate MTOR signaling via promoting the formation of MTORC1 is predicted to be a binding-target sequence of let-7a-5p. Furthermore, to assess whether there was a direct interaction between let-7a-5p and MAP4K3, luciferase reporter plasmid containing either wild-type or mutant 3’-UTRs of MAP4K3 was constructed, and the binding sites of let-7a-5p were shown in Fig. 6E. The result showed that compared with the mutant 3’UTRs construct (3’UTRs mut), administration of let-7a-5p-mimic could significantly reduce the luciferase activity of wide-type MAP4K3 3’UTRs (Fig. 6F). Collectively, the above results implicated the involvement of MAP4K3 in MSC-Exo derived let-7a-5p mediated TFEB nuclear translocation. To further clarify whether the induction of TFEB nuclear translocation and autophagic flux repairment by MSC-Exo derived let-7a-5p was dependent on MAP4K3 inhibition, the expression of MAP4K3 in groups of cells co-cultured with MSC-Exoanti-let-7a-5p were knockdown by shRNA. The results showed that in the case of let-7a-5p absence in MSC-Exo, knocked down MAP4K3 could rescue the expression of TFEB in the nucleus and reduce phosphorylation levels of TFEB (Fig. 6G through J). Moreover, the magnitude of Leu-induced LC3-II accumulation in cells co-cultured with MSC-Exoanti-let-7a-5p was also significantly larger in MAP4K3 shRNA group than in the control shRNA group (Fig. 6K, L). All in all, these results showed that MSCs treatment can downregulate MAP4K3 protein kinase expression through secreting let-7a-5p, which was enriched in exosomes, thus inhibiting TFEB phosphorylation and inducing its nuclear translocation, thereby promoting the repairment of autophagic flux and alleviate liver injury in ACLF (Fig. 7).
Due to the lack of suitable experimental models for ACLF and the inaccessibility of liver tissue from ACLF patients, it has remained difficult to analyze the pathophysiological mechanism of ACLF and develop new strategies or improve existing therapies for the disease. In our study, we developed a mouse model of ACLF by chronically intraperitoneal injection of low-dose tetrachloromethane to induce persistent liver injury, followed by an acute sublethal dose of tetrachloromethane injection to initiate an acute burst of liver damage. This model recapitulates the key features of ACLF, which involves chronic liver injury and acute liver insult, moreover, the high short-term mortality, sharply increased serum aminotransferase levels, massive hepatocytes necrosis, and obvious intrahepatic hemorrhage and inflammatory cell infiltration developed in the model were also closely concordant with the histopathological change in patients with ACLF [5]. These results strongly suggest that the model reported in this manuscript represents an experimental setting to further probe the disease mechanisms and therapeutic interventions in ACLF. Ample lines of evidence have identified MSCs as a promising approach for ACLF due to their distinguishing features on immunomodulatory and hepatoprotective capacities [6–8]. In our previous clinical study, MSCs treatment has been shown to significantly improve the liver function of ACLF patients, improve their survival rate and reduce the incidence of complications such as severe infection, but the fatality rate of patients is still around 30% [8]. Thus, further investigation of molecular mechanisms is essential to optimize the therapeutic potential of MSCs in the treatment of ACLF. Autophagy is a highly dynamic and multistep process that involves the wrapping of damaged organisms and macromolecules, formation of autophagosomes, fusing of autophagosomes into lysosomes, and degradation of the autolysosomes [25], and evidence has accumulated that changes of autophagic activity can aggravate or attenuate the pathophysiology of liver failure [34–37]. Most recently, increasing reports underlined that a “static” analysis of autophagy cannot provide insights into the autophagic flux [35, 36]. From a dynamical point of view, increased LC3-II levels would be a response to increased autophagosome formation, or a block in autophagosomes fused with lysosomes [38]. Studies in bile duct-ligated (BDL) hepatic fibrosis mice or chronic ethanol-induced (Gao binge) liver injury mice reported that LC3-II is increased, suggestive of induced autophagy, however, the degradative protein p62 was also found accumulated, which points to an impaired autolysosome function [35, 36]. Moreover, hepatocellular carcinoma (HCC) can be induced with the accumulation of p62 via activating Nrf2/c-myc and Wnt/β-Catenin pathway, implying the involvement of insufficient autophagy in the pathogenesis of liver injury and HCC development [39, 40]. Therefore, restoring the autophagy-lysosomal function could be a novel, previously unappreciated therapeutic target. Herein, our in vivo and in vitro data showed an upregulated level of LC3II and p62 in ACLF model, referred to as a blockage of autophago-lysosomal fusion at the end-stage of autophagic flux. However, we also found a number of surprises. MSCs administration not only reduced the inflammatory response and delayed disease progress of ACLF, but also notably decreased the LC3II and p62 levels, which implied that MSCs could restore the pathological impaired autophagy in ACLF and facilitate the degradation of p62. Moreover, aggravated liver damage of ACLF + MSCs mice after phagosome-lysosome fusion impeded by leupeptin highlighted the later clearance stages of autophagosome-lysosome fusion in autophagy and its role in MSCs-mediated hepatic protection. In recent decades, the MiT/TFE family member, transcription factors EB (TFEB) has been considered a master regulator of lysosome biosynthesis and autophagy-related gene transcription. Once activated, TFEB could promote not only lysosomal-related gene expression under a coordinated lysosomal enhancement and regulation (CLEAR) signal network but also upregulate genes involved in early-stage autophagy [28]. Besides, owning to the effect on autophagy, TFEB was reported to involve in the development and progression of liver disease. Overexpression of TFEB was able to inhibit inflammation and decrease hepatocyte death in ethanol- and copper-induced models of liver injury [36, 37]. In our present study, we observed for the first time that nuclear expression of TFEB was reduced in ACLF hepatocytes, furthermore, MSCs transfusion induced accumulation of TFEB in the nucleus and promoted transcription of autophagy and lysosomal genes, indicating that MSCs-mediated hepatoprotective effects may rely on TFEB-activated lysosome-autophagy pathways. In support of this, in vitro experiment was applied and found that TFEB silencing significantly blocked autophagic flux and reduced lysosome formation in hepatocytes co-cultured with MSCs, and dampened the hepatoprotective role of MSCs with increased cell death. Indeed, further validated whether the lysosome biogenesis activity was involved in MSC-inducing autolysosome formation and if the TFEB control autophagic flux by affecting their expression was proposed and performed in our supplementary experiments. the results of immunohistochemical staining showed a greater and enlarged enrichment of LAMP1 granules in hepatocytes of ACLF group, whereas the granules of CTSB are relatively dispersed (Fig. S2C), which indicated that lysosomal function may be impaired and lysosomal membrane permeabilization (LMP) was promoted in hepatocytes under ACLF conditions. Besides, the immunofluorescence staining of LGALS3, which was highly sensitive to analyze the lysosomal integrity [41], showed that the lysosomal membrane was deficient in hepatocytes of ACLF and MSCs transfusion was implicated in lysosomal membrane repair, as evidenced by LGALS3 puncta were gather in lysosomes and form fluorescent spots in C/I group and a relatively more diffuse distributed and fewer fluorescent spots was founded in cells treated with MSCs (Fig. S2D). Additionally, the higher number of LGALS3 fluorescent spots after TFEB knockdown supported that TFEB favors LMP repair and functions in MSC-inducing autophagosome-lysosome fusion (Fig. S2D). In accordance with this, the specific regulatory mechanism of LMP has been proposed, and further LAMP1 and RAB7 double staining were performed to explore whether the protective effect of TFEB on MSCs-induced autophagy restoration was attributed to lysosome biogenesis and clearance of damaged lysosomes. The results of IF staining confirmed that transfusion of MSCs could promote lysosome synthesis and partly replenish pre-existing dysfunctional lysosomes, as evidenced by an increased number of vesicles for LAMP1 positive alone, which indicated primary lysosomes, in contrast, inhibition of TFEB may impede lysosome biogenesis and reduce the clearance of damaged lysosomes as detected by both of LAMP1- and RAB7-positive vesicles which represented secondary lysosomes were increased appreciably (data not shown). These data elucidated that the effect of MSCs on autophagy rejuvenation was in part ascribed to its ability to active TFEB, maintaining the integrity of the lysosomal membrane and restoring normal function by promoting lysosome biogenesis and clearance of damaged lysosomes. However, since the sophisticated series of membrane phenomena and complex interplay between the constituent players remains poorly understood and the mechanism underlying autophagosome-lysosome fusion is beyond the scope of this manuscript, we tentatively conclude that TFEB accelerated autophagosome-lysosome fusion by promoting the lysosomal assembly of cathepsin and induction of lysosomal acidification, nevertheless the detailed mechanism warrants future studies. Herein, how MSCs promotes nuclear localization of TFEB was addressed. Mechanistically, recent studies have validated that the therapeutic effects of MSCs transplantation on liver tissue repair were partly attributed to its secreted exosomes [14–16]. There, MSC-Exo, which was well described as a potential intercellular communicator that exchanges cellular substances and bioinformation and owned the same roles in the immunoregulatory and pro-regenerative capacity as MSCs, exhibited lower immunogenicity, enhanced homing and prolonged survival, and avoid the risks of replicative senescence, pulmonary embolism, and intractability microenvironment impacts when comparing with MSCs [39]. Here, our data also showed that MSC-Exo play a key role in MSCs-mediated TFEB nuclear translocation of ACLF, as evidenced by decreased nuclear expression of TFEB following application of exosomes inhibitor GW4869. Thus, it represents an interesting therapeutic target, and the concrete regulatory mechanisms for TFEB nuclear translocation still need to be fully elucidated. To further clarify the exosomal components involved in modulating nuclear import of TFEB, miRNA-Seq analysis in MSC-Exo was performed. Among those highly enriched miRNAs, we noticed that let-7a-5p was lately reported to be markedly reduced in the setting of ACLF and related to 30-day mortality of patients [29]. Besides, let-7 was shown to implicate cell-cycle regulation, cell proliferation, and differentiation. In cholestasis mice, enhancement of let-7 is able to promote liver repair by inhibiting Lin28 expression and facilitating cell functional maturation [42]. Moreover, let-7 was shown to prevent the initiation and development of HCC by repressing the stemness of cancer stem cells and promoting its differentiation [40]. In current data, a lower level of let-7a-5p was also found in liver tissue of ACLF murine, and transfusion of MSCs could induce let-7a-5p expression. Combined with findings that upregulation of let-7 could suppress the expression of inflammatory cytokines and chemokines, including IL-6, IL-1β, IL-8, CCL2, and TNF-α [43–45], it is conceivable to speculate that let-7a-5p could alleviate liver injury by attenuating the uncontrollable cytokine storm in ACLF. To validate this conjecture, we used interfering RNAs and showed that the severity of hepatic impairment and inflammation was significantly exacerbated by let-7a-5p knockdown in vitro. Furthermore, we have also discovered an unexpected and new phenomenon: an increased level of let-7a-5p can be led to cell death from more skewed toward apoptosis rather than necroptosis. As we know, necroptosis has long been considered a trigger for various inflammatory activities, and it presents features that distinguish it from apoptosis in cell morphology and biochemistry, including organelle swelling and rupture; membrane hyperpermeability and integrity disruption; and intercellular proinflammatory factors liberation. This may also partially explain the inflammatory cascade in the condition of ACLF, which exhibit a lower level of let-7a-5p, but the magnitude of the effect and the underlying mechanism remained to be elucidated. Currently, studies on TFEB posttranscriptional regulation mainly concern phosphorylation by mTOR and MAPK kinases [30–33]. In detail, TFEB is highly phosphorylated at Ser142, Ser211, and Ser3 and retained in the cytoplasm under basal conditions. However, under conditions of elevated stress, cytoplasmic TFEB is dephosphorylated and translocated into the nucleus, resulting in its target gene expression increased. Among that, mTOR complex 1 (mTORC1) phosphorylated TFEB at Ser142 and Ser211, creating a 14-3-3 consensus binding site orientated in cytosol [30, 33]. MAPK family members, ERK2 phosphorylates TFEB at Ser142, whereas JNK and p38 MAPK phosphorylates ZKSCAN3 and inhibit TFEB nuclear translocation [32]. Moreover, Hsu et al. revealed that MAP4K3, another member of MAPK pathway, was able to inactivate TFEB from both directly phosphorylating TFEB at Ser3 or indirectly phosphorylating TFEB at Ser211 and Ser142 by stimulating mTORC1 [31]. In this regard, let-7a-5p was recently found to bind with the MAP4K3 mRNA 3’-UTR and inhibit its translation. Consistent with previous literature [46], our data of dual-luciferase reporter assay determined that MAP4K3 was located in the seed region of a predicted microRNA binding site for let-7a-5p and thus directly alter its expression. In addition, we knock-downed let-7a-5p expression in MSC-Exo by anti-miR and obtained MSC-Exoanti-let-7a-5p, and our data provide exquisite evidence that knockdown of let-7a-5p could weaken the effect of MSC-Exo on promoting autophagic flux, accompanied with reduced TFEB nuclear translocation than that of MSC-Exo. Noteworthily, we further validated that inhibition of MAP4K3 expression by let-7a-5p is one important driver for elevated expression of TFEB in the nucleus, as the reduced nuclear presence of TFEB in MSC-Exoanti-let-7a-5p group partially reversed after knocking down MAP4K3 in hepatocytes. The above results indicate that let-7a-5p is a crucial mediator in MSCs-induced TFEB nuclear translocation and autophagic flux restoration. Nevertheless, it should be noted that mechanisms investigated in vitro may not always reflect events in biologically relevant events, the pro-autophagic effect and hepatoprotective role of let-7a-5p and the dynamics change of let-7a-5p and autophagic activation affect disease severity throughout the course of ACLF still need to be validated in further in vivo studies. In summary, our study demonstrated for the first time that MSCs could promote autophago-lysosomal fusion at the end-stage of autophagic flux and thus restrict inflammation and alleviate liver injury in the model of ACLF. Mechanistically, we show that the pro-autophagic effects of MSCs were partly beneficial from its exosomal let-7a-5p to induce nuclear localization of TFEB by targeting MAP4K3. These results open a novel insight into the functional linkage between autolysosome maturation and liver inflammation and suggest that let-7a-5p could be a potential target in the treatment of ACLF.
Figure S1 Figure S2 supplementary table 1 supplementary table 2 supplementary materials and mathods supplementary figure legend full and uncropped western blots Reproducibility Checklist | true | true | true |
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PMC9557158 | Jinquan Bai,Zhenzhou Shi,Shuting Wang,Hong Pan,Tong Zhang | MiR-21 and let-7 cooperation in the regulation of lung cancer | 29-09-2022 | lung cancer,miR-21,let-7,K-ras,cooperative regulation | Background Lung cancer occurs and develops as a result of a complicated process involving numerous genes; therefore, single-gene regulation has a limited therapeutic effect. We discovered that miR-21 expression was high in lung cancer tissues and cells, whereas let-7 expression was low, and it is unclear whether their combined regulation would be superior to therapy involving single regulation. The goal of our research was to investigate this situation and the regulatory mechanism that exists between these genes. Methods To regulate the levels of miR-21 and let-7 in these two types of lung cancer cells, we transfected miRNA mimics or inhibitors into A549 and H460 cells. Lung cancer cells were tested for proliferation, apoptosis, migration, and invasion. The results were verified using a Western blot and a qRT-PCR assay. Bioinformatics was used to investigate their potential regulatory pathways, and luciferase assays were used to confirm the binding sites. Results The expression of miR-21 was increased and that of let-7 was decreased in lung cancer tissues and cells compared with paracancerous tissues and normal lung cells (p < 0.01). Tumor cells were inhibited by downregulation of miR-21 and upregulation of let-7, and cooperative regulation showed a better effect. Upregulation of miR-21 and downregulation of let-7 promoted tumor cells, and this tumor-promoting effect was amplified by cooperative regulation. MiR-21 regulated lung cancer cells directly via the Wnt/-catenin pathway, and let-7 exerted its effects via the PLAG1/GDH1 pathway. MiR-21 and let-7 cooperated to regulate lung cancer cells via the K-ras pathway. Conclusions The effect of cooperative regulation of miR-21 and let-7 on lung cancer is greater than that of a single miRNA. MiR-21 and let-7 are important differentially expressed genes in lung cancer that are regulated by the K-ras pathway. As a result, for multigene lung cancer, the cooperative regulation of two miRNAs will provide a new target and direction for lung cancer treatment in the future. | MiR-21 and let-7 cooperation in the regulation of lung cancer
Lung cancer occurs and develops as a result of a complicated process involving numerous genes; therefore, single-gene regulation has a limited therapeutic effect. We discovered that miR-21 expression was high in lung cancer tissues and cells, whereas let-7 expression was low, and it is unclear whether their combined regulation would be superior to therapy involving single regulation. The goal of our research was to investigate this situation and the regulatory mechanism that exists between these genes.
To regulate the levels of miR-21 and let-7 in these two types of lung cancer cells, we transfected miRNA mimics or inhibitors into A549 and H460 cells. Lung cancer cells were tested for proliferation, apoptosis, migration, and invasion. The results were verified using a Western blot and a qRT-PCR assay. Bioinformatics was used to investigate their potential regulatory pathways, and luciferase assays were used to confirm the binding sites.
The expression of miR-21 was increased and that of let-7 was decreased in lung cancer tissues and cells compared with paracancerous tissues and normal lung cells (p < 0.01). Tumor cells were inhibited by downregulation of miR-21 and upregulation of let-7, and cooperative regulation showed a better effect. Upregulation of miR-21 and downregulation of let-7 promoted tumor cells, and this tumor-promoting effect was amplified by cooperative regulation. MiR-21 regulated lung cancer cells directly via the Wnt/-catenin pathway, and let-7 exerted its effects via the PLAG1/GDH1 pathway. MiR-21 and let-7 cooperated to regulate lung cancer cells via the K-ras pathway.
The effect of cooperative regulation of miR-21 and let-7 on lung cancer is greater than that of a single miRNA. MiR-21 and let-7 are important differentially expressed genes in lung cancer that are regulated by the K-ras pathway. As a result, for multigene lung cancer, the cooperative regulation of two miRNAs will provide a new target and direction for lung cancer treatment in the future.
Mutations in coding genes and noncoding gene disorders are the primary causes of lung cancer occurrence and progression (1). The targeted drug therapy strategy for lung cancer is primarily aimed at the type of gene mutation (2), but drug resistance caused by frequent gene mutation has always been a difficult problem in lung cancer treatment (3, 4). As a result, the regulation of noncoding genes involved in lung cancer treatment has emerged as a research focus. The expression of some miRNAs increases or decreases during the progression of lung cancer, and these miRNAs regulate the expression of coding genes (5). In contrast to other RNAs, miRNAs are endogenous, noncoding, single-stranded small RNAs composed of approximately 20 nucleotides that can regulate the expression of mRNA genes. They can be used to regulate related target genes for tumor therapy because they can always maintain a high degree of conservation (5). Previous research has concentrated on treating lung cancer by regulating a negative regulatory target gene mRNA, a pathway involving miRNA (6); however, some miRNAs can also indirectly positively regulate mRNA by regulating other cytokines (7). There are thousands of human miRNAs. Previous research on the high expression of miR-21 and low expression of let-7 in lung cancer tissue and cells indicates poor patient survival and promotes tumor progression (8–10). MiR-21 is the most commonly overexpressed miRNA in cancer (11), and it is related to cell proliferation, apoptosis, migration, and invasion (12). It is thought to be a carcinogenic gene because it is involved in tumor promotion. Overexpression of miR-21 removes multiple inhibitors of the RAS/MEK/ERK pathway and promotes tumor progression, whereas knocking down miR-21 inhibits the transformation driven by the RAS gene, thereby inhibiting the development of lung cancer (10, 13). Let-7 is a gene that has been conserved from worms to humans during evolution (14), and it is downregulated in lung cancer (13, 15–17). It is a common RAS family direct negative regulatory factor (13) and can indirectly regulate the target gene K-ras via Lin28A/B (18, 19). Let-7 upregulation may slow the growth of lung tumors in mice (20). As a result, in this study, we chose the miR-21 and let-7 genes, which are commonly studied in lung cancer research (13) and predicted that the effect of cooperative regulation of miR-21 and let-7 on lung cancer is more significant than the regulation of a single miRNA alone.
All lung cancer tissue samples (42 cases) were collected from the Fourth Affiliated Hospital of Harbin Medical University from August 2020 to July 2022 ( Table 1 ). The samples were immediately frozen in liquid nitrogen for further analysis. These patients had not received any therapy before sample collection. Before collecting clinical samples, all patients provided written informed consent. This study was performed in accordance with the standards established by the Declaration of Helsinki. The study protocol was approved by the Ethics Committee of the Fourth Affiliated Hospital of Harbin Medical University.
The human lung cancer cell lines A549 and H460 and the human bronchial epithelial cell line HBE were cultured in a 1640 medium containing 10% fetal bovine serum (FBS) at 37°C in a 5% CO2 incubator. Using LipofectamineTM 2000 (Lipo2000) as a transfection reagent, a miR-21 inhibitor, miR-21 mimic, let-7 mimic, let-7 inhibitor, NC-inhibitor, and NC-mimic were transfected into A549 and H460 cell lines ( Table 2 ). The specific operational procedure of the experiment is based on the Lipofectamine 2000 (Thermo Fisher) (aoheng biotechnology development Co. Ltd. , Harbin City, China) product manual. The sequences of miRNA mimics and miRNA inhibitors are listed in Table 3 .
Total RNA was extracted from lung cancer tissue and cells using the TRIzol reagent. The specific experimental operational procedure of cDNA library construction was carried out according to the product manual of the Transcriptor First-Strand cDNA Synthesis Kit (Roche). All the reaction reagents were melted on ice and mixed lightly. For the SYBR gene detection technology, the specific operation procedure was based on the Roche SYBR-ROX product manual, and the reaction system was prepared according to the operation steps of the kit. The reaction system utilized the 7500 Real-Time PCR instrument (Applied Biosystems), with GAPDH and U6 used as the internal references. The expression level of the qRT-PCR products was calculated by the 2−ΔΔCt method. RT-PCR primers were designed as follows: K-ras F 5′-TGTGGTAGTTGGAGCTGGTG-3′ and R 5′-TCCAAGAGACAGGTTTCTCCA-3′; pleomorphic adenoma gene 1 (PLAG1) F 5′-ATCACCT CCATACACACGACC-3′ and R 5′-AGCTTGGTATTGTAGTTCTTGCC-3′; β-catenin F 5′-GGAAGGTCTCCTTGGGACTC-3′ and R 5′-ATACCACCCACTTGGCA GAC-3′; miR-21 F 5′-GGGGTAGCTTATCAGACTG-3′ and R 5′-TGGAGTCGGCA ATTGCACTG-3′; let-7 F 5′-TGGAAGACTAGTGATTTTGTTGTT-3′ and R 5′-A TCCAGTGCAGGGTCCGAGG-3′; U6 F 5′-TCCCAGGGCGAGGC TTAT CC ATT-3′ and R 5′-GAACGCAGTCCCCCACTACCACAAA-3′; and GAPDH F 5′-CCCACTCC TCCACCTTTGAC-3′ and R 5′-CATACCAGGAAATGAGCTTGACAA-3′.
A549 and H460 cells were inoculated into a 96-well plate and incubated at 37°C for 48 h. According to the manufacturer’s instructions, the cell disposal treatment was performed, and the culture medium of each well was changed before adding CCK-8 reagent to each well to reduce the effect of cell metabolites on the assay. Ten microliters of CCK-8 reagent was added to each well to avoid producing air bubbles and affect the assay results. The culture plate was incubated in the incubator for 2 h. The absorbance of each well in the culture plate at 450 nm was determined by a multifunction enzyme labeling instrument, and the data were analyzed by Excel.
Cells from the logarithmic growth phase were plated in 24-well plates. A total of 100 μl of EdU medium was then added to each well, and the cells were incubated in a 37°C incubator for 2 h. The EdU medium was removed, and the cells were washed with PBS. The cells were fixed with a 4% paraformaldehyde solution at room temperature for 30 min. The formaldehyde fixing solution was removed by pipette, and images were obtained by fluorescence microscopy to analyze the results.
The cell extracts were prepared by lysing cells in RIPA buffer containing a complete protease inhibitor mix (Biyuntian Co. Ltd.). The protein concentration of the cell extracts was measured by a BCA Protein Assay Kit (Biyuntian Co. Ltd.). We separated the molecular weight of the protein samples into different bands by polyacrylamide electrophoresis and then transferred the protein bands on the PAGE gel to the NC membrane. The membranes were treated with anti-PLAG1 antibody (rabbit-derived polyclonal, 1:200, Abcam Corp.) and anti-p-β-catenin antibody (rabbit-derived polyclonal, 1:200, Cell Signaling Technology Corp.) and then incubated with goat anti-mouse secondary antibodies (1:10,000, Alexa Fluor 800). The film was assessed by an infrared fluorescence scanning system. GAPDH (mouse-derived polyclonal, 1:1,000, Santa Cruz Biotechnology) was used as the internal reference. Pictures were taken, and the optical density integral was analyzed by image analysis software Odyssey1.2.
A549 and H460 cells were grown on slides. The TUNEL reaction mixture was prepared according to the instructions from Roche. Fifty microliters of TUNEL reaction mixture was added to each slide, and the slides were placed into a dark wet box and reacted at 37°C for 1 h. The slides were washed twice with PBS for 5 min each time, after which DAPI was added, followed by incubation in an incubator at 37°C for 10 min. The slides were observed and counted under a fluorescence microscope.
A549 and H460 cells were inoculated into six-well plates and cultured until 100% confluency was achieved. The cells were randomly divided into four groups, which were transfected with miR-21 inhibitor, let-7 mimic, miR-21 inhibitor + let-7 mimic, and control group. Subsequently, a p200 pipette tip was used to create a scratch. A culture medium without FBS was added. The cells were imaged using a microscope at 0 and 48 h after wounding.
The A549 and H460 cells were inoculated at the top of the 24-well chamber with a pore diameter of 8 μm that had been precoated with 80 μl Matrigel (BD, China). The lower chamber contained 800 μl of culture medium with 10% fetal bovine serum (FBS). After 24 h of culture, the cells on the upper surface of the chamber were removed with cotton swabs, and the cells invading the lower surface of the chamber were fixed with a 4% paraformaldehyde fixation solution (Beyotime, China). A total of 0.5% crystal violet (Beyotime, China) was then added to stain the cells, which were counted under a microscope (Olympus CKX53, Japan).
The luciferase reporter gene vector containing wild type (WT) and mutant type (MT) was constructed according to the let-7 binding site predicted by starBase v2.0 and TargetScan. The control mimic and let-7 mimic were synthesized and cotransfected with the luciferase reporter gene and gene fragment into H460 cells by the transfection reagent. The luciferase activities were measured with the luciferase reporter assay system.
Data analysis was performed with SAS 9.4 software and GraphPad Prism software (GraphPad Software, La Jolla, CA, USA). Values are presented as the mean ± standard deviation (SD). The Student’s t-test was used for statistical analysis. A paired t-test was used to assess the expression of miRNAs in lung cancer and paracancerous tissues. The three groups of cell lines were first analyzed by one-way ANOVA, and the difference was statistically significant. Dunnett’s t-test was then performed. Factorial design ANOVA and individual effect comparison were used to analyze the differences between regulatory groups. A one-sample t-test was used to analyze the differences between the NC group and the regulatory group. A p < 0.05 (two-tailed) was considered a significant difference. All experiments were repeated in triplicate at a minimum.
In this study, 42 patients with lung cancer were analyzed, with an average age of 60.8 years (43-85). The male-to-female ratio was 1:1, with TNM stages of I–IV ( Table 1 ). We used qRT-PCR to analyze the expression of miR-21 and let-7 in 42 cases of lung cancer. The results showed that the expression of miR-21 was significantly higher than that in paracancerous tissues (4.985 ± 2.226 vs. 3.695 ± 1.897; p = 0.0015; Figure 1A ); in contrast, let-7 showed a low expression (3.969 ± 2.471 vs. 5.468 ± 2.720; p = 0.001; Figure 1B ). Similar results were obtained in cell lines. Compared with human normal bronchial epithelial cells (HBEs), the H460 and A549 cell lines showed a high expression of miR-21 (p = 0.001 and p <0.001, respectively) and a low expression of let-7 (p = 0.004 and p = 0.001, respectively) ( Figure 1C ). This finding is consistent with previous studies on the high expression of miR-21 and the low expression of let-7 in lung cancer (11, 13, 15, 16).
After transfection of the miR-21 inhibitor into H460 and A549 cells, the transfection efficiency was measured by qRT-PCR assay. The expression level of miR-21 was lower than that of the control group (p = 0.0038 and p = 0.0023, respectively), but the expression of miR-21 increased after transfection of the miR-21 mimic (p = 0.0075 and p = 0.0098, respectively) ( Figure 1D ). The same results were obtained after transfection with a let-7 inhibitor and mimic ( Figure 1E ). This demonstrates that the two miRNAs can be stably expressed in cells.
The proliferation of cancer cells in every group of cell lines was analyzed by the CCK-8 and EdU cell proliferation assays. The inhibitory rate of miR-21 on tumor growth in the let-7 mimic group compared to the NC group was 43.65% and 41.27%, respectively, and that of the 21 in+7 mimic group showed an average value of 69.32% for the two groups of cell lines (n = 3, p < 0.001) ( Figures 2A–C ). Upregulation of miR-21 and downregulation of let-7 promoted the proliferation of lung cancer cells, especially in the 21 mimic group, which was 1.54 times that of the NC group. The effect of cooperative regulation of the two kinds of miRNA was 2.37 times that of the NC group in promoting the proliferation of lung cancer cells ( Figures 2D–F ).
In the apoptosis experiment, the TUNEL incorporation assay showed that the proportion of apoptotic cells in the miR-21 inhibitor group and let-7 mimic group was three to five times higher than that in the control group, indicating that miR-21 inhibited tumor cell apoptosis and let-7 promoted tumor cell apoptosis, while the effect of cooperative regulation of the two kinds of miRNAs was greater ( Figures 3A, B ). The flow cytometry results in the Q2 and Q3 quadrants also showed similar results ( Figures 3C, D ). Furthermore, we demonstrated changes in the expression of Bax, Bcl-2, cyclin D1, and cyclin E1 by Western blotting (21–23), which supported the above results. The Bax protein expression in the miR-21 inhibitor group and let-7 mimic group was higher than that in the control group, especially in the miR-21 inhibitor+let-7 mimic group (n = 3, p < 0.001, Figures 4A, B ). The expression of Bcl-2, cyclin D1, and cyclin E1 was lower than that in the control group, and the expression in the miR-21 inhibitor+let-7 mimic group was more obvious (n = 3, p < 0.001, Figures 4C–H ).
Downregulation of miR-21 and upregulation of let-7 inhibited the migration and invasion of lung cancer cells in wound-healing and Transwell assays, and the effect of combined regulation was better than that of single regulation ( Figures 5A–D ). Upregulation of miR-21 and downregulation of let-7 promoted the invasion of lung cancer cells in the Transwell assay (p < 0.01), and the effect of regulating both miRNAs was more obvious (p < 0.001, Figures 5E, F ).
The Wnt/β-catenin pathway plays an important role in the progression of cancers, including lung cancer (24). Previous research has shown that the Wnt/β-catenin signaling pathway is positively correlated with miR-21 in lung cancer (25). Therefore, we divided the cells in this experiment into a miR-21 inhibitor group and a control group. qRT-PCR was used to determine the expression of β-catenin in lung cancer cells (H460 and A549) in the miR-21 inhibitor group. Western blot experiments were carried out with GAPDH as an internal reference to observe the protein expression of β-catenin. The results showed that the expression of phosphorylated β-catenin in the two kinds of lung cancer cells in the miR-21 inhibitor group was significantly lower than that in the control group. (p < 0.001, Figures 6A–C ), but the expression of total β-catenin (T-β-catenin) was not inhibited (p = 0.7953, Figures 6D, E ). It has been proven that p-β-catenin is a key molecule for miR-21. In previous studies, the expression of T-β-catenin was not significantly changed after the downregulation of miR-21, but the relationship between p-β-catenin and miR-21 was not analyzed (25).
By using miRBase and TargetScan, it was predicted that the target of let-7 may be PLAG1. We used qRT-PCR to determine the expression of PLAG1 in 42 cases of lung cancer. The results showed that the expression of PLAG1 in lung cancer tissues was significantly higher than that in adjacent tissues (the difference between the means was 1.408 ± 0.4914, p = 0.0053, Figure 7A ). Similar results were obtained in cell lines (p < 0.01, Figure 7B ). The cells were divided into the let-7 inhibitor group, let-7 mimic group, and control group. Western blotting was then carried out using tubulin as an internal reference to observe the protein expression of PLAG1 in H460 and A549 cells. The results of the Western blot assay showed that in the two kinds of lung cancer cells, the expression of PLAG1 in the let-7 inhibitor group was higher than that in the control group, while the expression of PLAG1 in the let-7 mimic group was decreased (p < 0.001, Figures 7C, D ), which proved that PLAG1 was regulated by let-7. To further verify that PLAG1 was the direct target of let-7 and to demonstrate the binding site between let-7 and PLAG1, we carried out a luciferase experiment. The results showed that let-7 inhibited the expression of the luciferase reporter gene when transfected with PLAG1 MT in HEK293T cells but had no inhibitory effect when transfected with PLAG1 MT and NC ( Figure 7E ).
Si-K-ras were introduced into lung cancer cells (H460 and A549) to knock down K-ras, resulting in a significant decrease in gene expression by qRT-PCR (p < 0.001, Figure 8A ). Further research showed that when tubulin was used as a reference for Western blot experiments, the protein expression of K-ras was decreased in the two kinds of lung cancer cells (p < 0.001, Figures 8B, C ). After the downregulation of K-ras, the expression of miR-21 in lung cancer cells decreased, and the expression of let-7 increased (p < 0.01 and p < 0.001, Figures 8D, E ). It is suggested that K-ras positively regulates miR-21, while K-ras negatively regulates let-7.
At present, the high incidence and low survival rate of lung cancer is a common problem for humans (26). There are many endogenous and exogenous reasons, and the most fundamental reason is tumor heterogeneity (27), which makes it difficult to treat. MiR-21 can promote the growth and migration of lung cancer cells as an oncogene (28). It has been proven that miR-21 inhibitors can suppress the development of lung cancer (29). In contrast, Let-7 is an important tumor suppressor gene discovered in recent years. Let-7 mimics can induce apoptosis of lung cancer cells and reduce tumor cell invasiveness (30). According to previous research results, we found that the expression of miR-21 in lung cancer tissues and cells was upregulated, while the expression of let-7 was downregulated. This shows that miR-21 and let-7 are involved in the occurrence and development of lung cancer, which is consistent with the report of Choudhury et al. (13). The activation of β-catenin promotes the proliferation and survival of lung cancer cells, induces angiogenic factors that promote tumor angiogenesis, and maintains cell integrity (31). Downregulation of miR-21 leads to the downregulation of p-β-catenin, which plays an inhibitory role in lung cancer. We found that upregulation of let-7 suppressed the expression of PLAG1, while PLAG1 could promote apoptosis resistance and metastasis of lung cancer by regulating glutamate dehydrogenase 1 (GDH1) (32). Studies have shown that GDH1 promotes tumor growth by activating the reactive oxygen species (ROS)-scavenging enzyme glutathione peroxidase 1 and regulating redox homeostasis through its product a-ketoglutarate (a-KG) and the subsequent metabolite fumarate (32). The binding site of let-7 and PLAG1 was verified by luciferase experiments in our experiment. Therefore, upregulation of let-7 suppressed PLAG1, which targets GDH1 to inhibit lung cancer cells. Downregulation of miR-21 and upregulation of let-7 at the same time showed a more obvious antitumor effect, indicating that there is a feedback regulation loop between miR-21 and let-7 to coordinate the regulation of lung cancer. We found that knocking down K-ras can inhibit the expression of miR-21 and promote the expression of let-7, and therefore, K-ras may be a common target gene involved in the synergistic regulation of miR-21 and let-7 in lung cancer. Previous studies have shown that miR-21 indirectly positively regulates RAS genes through multiple negative regulators of the RAS pathway, of which Spry1, Spry2, Btg2, and Pdcd410 have been confirmed, and miR-21 also positively regulates the downstream gene AP1 of K-ras by inhibiting Spry1/2 or Pdcd4 (13, 33, 34). In contrast, it has been proven that let-7 can directly inhibit K-ras expression within the binding site of the K-ras 3′UTR (13, 35, 36) or indirectly by inhibiting LIN28A/B (13, 17). These reports support our research that miR-21 and let-7 participate in the regulation of lung cancer through K-ras. In summary, miR-21 and let-7 are important differentially expressed genes in lung cancer tissues and cells. Downregulation of miR-21 or upregulation of let-7 can both inhibit the development of lung cancer, but the cooperative regulation of miR-21 and let-7 exerts a more significant effect. These genes participate in the regulation of lung cancer through the K-ras gene to form a feedback pathway ( Figure 9 ). For multigene-involved lung cancer, cooperative regulation of the two miRNAs will provide new targets and directions for lung cancer treatment in the future.
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.
The studies involving human participants were reviewed and approved by the Ethics Committee of the Fourth Affiliated Hospital of Harbin Medical University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.
TZ designed the study. JB, ZS, SW, and HP performed the experiments and analyzed the data. JB contributed to drafting the manuscript. All authors read and approved the final manuscript.
This work was supported by the Beijing Cihua Medical Development Foundation Project (Research on CT-assisted diagnosis of coronary heart disease based on artificial intelligence).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9557189 | 36247364 | Da-Ru Wang,Xiao-Wei Zhang,Rui-Rui Xu,Gui-Luan Wang,Chun-Xiang You,Jian-Ping An | Apple U-box-type E3 ubiquitin ligase MdPUB23 reduces cold-stress tolerance by degrading the cold-stress regulatory protein MdICE1 | 03-08-2022 | Abstract Cold stress limits plant growth, geographical distribution, and crop yield. The MYC-type bHLH transcription factor ICE1 is recognized as the core positive regulator of the cold-stress response. However, how ICE1 protein levels are regulated remains to be further studied. In this study, we observed that a U-box-type E3 ubiquitin ligase, MdPUB23, positively regulated the cold-stress response in apple. The expression of MdPUB23 increased at both the transcriptional and post-translational levels in response to cold stress. Overexpression of MdPUB23 in transgenic apple enhanced sensitivity to cold stress. Further study showed that MdPUB23 directly interacted with MdICE1, promoting the ubiquitination-mediated degradation of the MdICE1 protein through the 26S-proteasome pathway and reducing the MdICE1-improved cold-stress tolerance in apple. Our results reveal that MdPUB23 regulates the cold-stress response by directly mediating the stability of the positive regulator MdICE1. The PUB23–ICE1 ubiquitination module may play a role in maintaining ICE1 protein homeostasis and preventing overreactions from causing damage to plants. The discovery of the ubiquitination regulatory pathway of ICE1 provides insights for the further exploration of plant cold-stress-response mechanisms. | Apple U-box-type E3 ubiquitin ligase MdPUB23 reduces cold-stress tolerance by degrading the cold-stress regulatory protein MdICE1
Cold stress limits plant growth, geographical distribution, and crop yield. The MYC-type bHLH transcription factor ICE1 is recognized as the core positive regulator of the cold-stress response. However, how ICE1 protein levels are regulated remains to be further studied. In this study, we observed that a U-box-type E3 ubiquitin ligase, MdPUB23, positively regulated the cold-stress response in apple. The expression of MdPUB23 increased at both the transcriptional and post-translational levels in response to cold stress. Overexpression of MdPUB23 in transgenic apple enhanced sensitivity to cold stress. Further study showed that MdPUB23 directly interacted with MdICE1, promoting the ubiquitination-mediated degradation of the MdICE1 protein through the 26S-proteasome pathway and reducing the MdICE1-improved cold-stress tolerance in apple. Our results reveal that MdPUB23 regulates the cold-stress response by directly mediating the stability of the positive regulator MdICE1. The PUB23–ICE1 ubiquitination module may play a role in maintaining ICE1 protein homeostasis and preventing overreactions from causing damage to plants. The discovery of the ubiquitination regulatory pathway of ICE1 provides insights for the further exploration of plant cold-stress-response mechanisms.
Plants are constantly subjected to various environmental stimuli during their growth and development, such as extreme temperature, drought, waterlogging, and high salinity [1–3]. To adapt to harsh environmental challenges, plants have evolved elaborate regulatory mechanisms [4–6]. Cold stress is one of the most important abiotic stresses affecting plant growth, geographical distribution, and crop yield. It affects plant metabolism by directly inhibiting the expression of genes related to metabolic enzymes [7–9]. Cold stress rapidly activates the expression of a series of transcription factors, among which C-repeat-binding factors (CBFs) are the most thoroughly studied. They directly induce the expression of downstream cold-responsive (COR) genes, regulating the response to cold stress [7–13]. Three CBF genes (AtCBF1–AtCBF3) were identified in Arabidopsis, and five (MdCBF1–MdCBF5), in apple [14–17]. In Arabidopsis, the CBF genes are regulated by many upstream transcription factors, including INDUCER OF CBF EXPRESSION1/2 (ICE1/2), CALMODULIN-BINDING TRANSCRIPTION ACTIVATOR1–5 (CAMTA1–5), MYB15, PHYTOCHROME-INTERACTING FACTOR3/4/7 (PIF3/4/7), PSEUDO RESPONSE REGULATORS (PRRs), CIRCADIAN CLOCK-ASSOCIATED1 (CCA1), LATE ELONGATED HYPOCOTYL (LHY), ETHYLENE INSENSITIVE3 (EIN3), CESTA, BRASSINAZOLERESISTANT1 (BZR1), and BRI1-EMS-SUPPRESSOR1 (BES1) [18–32]. ELONGATED HYPOCOTYL5 (MdHY5), MdMYB23, BASIC HELIX–LOOP-HELIX33 (MdbHLH33), and B-box37 (MdBBX37) have been identified as positive regulators of MdCBF genes in apple [33–37]. Among them, the ICE1–CBF–COR regulatory module plays a particularly essential role in the cold-stress response [11, 18, 38, 39]. ICE1 interacts with many cold-stress regulatory proteins to jointly regulate the cold-stress response. In Arabidopsis, ICE1 directly interacts with MYB15, a negative regulator of cold stress [19]. The jasmonic acid (JA)-signaling repressors JASMONATE ZIM-DOMAIN1 (JAZ1) and JAZ4 interact with ICE1, inhibiting the transcriptional activity of ICE1 [40]. HIGH OSMOTIC EXPRESSION1 (HOS1), MITOGEN-ACTIVATED PROTEIN KINASE3/6 (MPK3/6), and BRASSINOSTEROID-INSENSITIVE2 (BIN2) negatively regulate cold-stress tolerance through interaction with ICE1 and attenuate the protein stability of ICE1 [41–44]. By contrast, SAP and Miz1 (SIZ1) and OPEN STOMATA 1 (OST1) enhance the protein stability of ICE1 in the cold-stress response [28, 45]. Rice OsMAPK3 enhances the stability of OsICE1 by inhibiting OsICE1 degradation via OsHOS1 [46]. In banana fruit, JA-signaling regulators called MaMYC2s may mediate cold-stress tolerance by interaction with MaICE1 [47]. SEVEN IN ABSENTIA1 (MaSINA1) may negatively regulate the cold-stress response by reducing the protein stability of MaICE1 [48]. MdBBX37 and ABSCISIC ACID INSENSITIVE4 (MdABI4), as interaction partners of MdICE1, positively regulate the transcriptional activity of MdICE1 in apple [37, 49]. Post-translational modifications, such as ubiquitination, phosphorylation, methylation, and sumoylation, play key roles in the regulation of protein stability and biological activity [50–54]. Among them, ubiquitination has been well studied. The ubiquitination cascade requires the coordination of three components: E1 ubiquitin-activating enzymes, E2 ubiquitin-conjugating enzymes, and E3 ubiquitin ligases [55, 56]. In particular, E3 ubiquitin ligases play a decisive role in the specificity of target proteins [57, 58]. In Arabidopsis, more than 1400 genes encode E3 ubiquitin ligases [57, 59]. According to the characteristic domain of ubiquitin ligases and the mechanism of ubiquitin’s transfer to target proteins, E3 ubiquitin ligases are mainly divided into three categories: homologous to E6AP COOH terminus (HECT)-type E3 ubiquitin ligases, really interesting new gene (RING)-finger-type E3 ubiquitin ligases, and U-box-type E3 ubiquitin ligases [60–62]. Plant U-box-type E3 ubiquitin ligases (PUBs) play a broad role in the regulation of plant growth and development and stress responses [63–65]. In Arabidopsis, PUB2/4/12/13/22/23/24/25/26 are involved in plant immune regulation [66–70]. PUB11/22/23/46/48 mediate the drought-stress response [71–74]. PUB10/12/13/18/19/40 play key roles in plant responses to multiple hormonal signals [75–80]. A recent study showed that PUB25 and PUB26 positively regulated the cold-stress response by mediating MYB15 protein degradation [81]. In apples, MdPUB24 and MdPUB29 regulate fruit quality [82, 83]. In addition, MdPUB29 may also be involved in the regulation of the plant immune response to fungal pathogens [84]. However, the roles of PUB proteins in apple remain to be further studied. In this study, we report that the U-box-type E3 ubiquitin ligase MdPUB23 is a negative regulator of the cold-stress response in apple. MdPUB23 interacts with MdICE1, a key regulator of cold stress, and negatively regulates the cold-stress response by promoting the protein stability of MdICE1. This study reveals a new post-translational regulatory mechanism that maintains the protein stability of ICE1 in the cold-stress response.
ICE1 is considered a key positive regulator of the cold-stress response [18, 38]. However, the post-translational regulation of the ICE1 protein has not been fully studied. To study the post-translational regulatory mechanism of MdICE1 in apple, the MdICE1-GFP protein was extracted from MdICE1-overexpressing apple calli (MdICE1-GFP) [37] and analysed by mass spectroscopy. The U-box E3 ubiquitin ligase MdPUB23 was isolated as a potential interaction partner of MdICE1. To test the interaction between MdPUB23 and MdICE1, we performed Y2H assays. The results showed that yeast cells transformed with MdPUB23 or MdICE1 alone could not grow on selective medium (−T/−L/−H/−A), and only the yeast cells transformed with MdPUB23 and MdICE1 could grow normally on selective medium (Fig. 1A), suggesting that MdPUB23 and MdICE1 interact with each other in yeast cells. Next, in vitro pull-down assays were performed to confirm the interaction. The purified MdPUB23-HIS fusion protein was pulled down using MdICE1-GST (Fig. 1B), indicating that MdPUB23 physically interacted with MdICE1 in vitro. We further verified the interaction between MdPUB23 and MdICE1 by BiFC assays. Fluorescence detection results showed that only onion epidermal cells co-expressed MdPUB23 and MdICE1 could produce a strong fluorescence signal (Fig. 1C). These data reveal that MdPUB23 interacts with MdICE1. Moreover, coimmunoprecipitation (Co-IP) assays showed that MdPUB23 interacted with MdICE1 in vivo (Fig. 1D). Further Y2H assays showed that MdPUB23 specifically interacted with MdICE1 in yeast cells (Fig. 1E).
Identification and amino acid sequence analysis revealed that the cDNA sequence of MdPUB23 comprised 1221 bp and encoded 406 amino acids with a predicted U-box motif in the N-terminal region (Fig. 2A). MdPUB23 showed high sequence similarity with PUB23 proteins in nine other species, especially the conserved U-box motif (Fig. 2B). Among them, MdPUB23 shared the lowest sequence identity with AtPUB23 (58.07%) and the highest sequence identity with PbPUB23 (97.04%). The phylogenetic tree analysis showed that MdPUB23 and PbPUB23 had the closest relationship (Fig. 2C), suggesting that there may be functional similarities between the two.
Because MdPUB23 acts as an interaction partner of MdICE1, we hypothesized that MdPUB23 might be involved in the cold-stress response. To confirm this hypothesis, we first detected the expression of MdPUB23 in response to cold stress. Previous transcriptome data showed that cold stress induced MdPUB23 expression (Fig. 3A) [34]. qRT-PCR results showed that the expression of MdPUB23 increased gradually after cold-stress treatment (4°C), and the expression was the highest after 6 h of cold-stress treatment (Fig. 3B). These results demonstrate that cold stress promotes the expression of MdPUB23. To identify the biological function of MdPUB23 in the cold-stress response, we generated stable MdPUB23 transgenic apple calli (MdPUB23-OX-1 and MdPUB23-OX-2, MdPUB23-overexpressing apple calli; MdPUB23-Anti-1 and MdPUB23-Anti-2, apple calli expressing the MdPUB23 antisense construct; Supplementary Fig. S1A). Although there was no significant difference in the growth status of wild-type (WT) and MdPUB23 transgenic apple calli at room temperature (24°C), after cold-stress treatment, the overexpression of MdPUB23 inhibited the growth of calli compared with the WT control, while the suppression of MdPUB23 expression contributed to the growth of calli (Fig. 4A–B). Gene expression analysis showed that the overexpression of MdPUB23 inhibited and the suppression of MdPUB23 increased the expression of MdCBF1 and MdCBF2 and its target genes (Fig. 4C). To evaluate its function in intact plant tissues, transient transgenic apple seedlings and leaves overexpressing MdPUB23 were generated and subjected to cold-stress treatment (Supplementary Fig. S1B, C). After cold-stress treatment, the chlorophyll loss of transgenic apple seedlings was determined, and the transgenic apple leaves were stained with reactive oxygen species (ROS) dye to determine the degree of damage to the seedlings or leaves caused by the cold stress. The results showed that, compared with the empty-vector control (EV), the chlorophyll loss and ROS content in the MdPUB23 transgenic leaves were higher after cold-stress treatment (Fig. 4D–G), indicating that MdPUB23 negatively regulates cold-stress tolerance. Furthermore, we obtained MdPUB23 transgenic Arabidopsis seedlings and used them for cold-stress assays (Supplementary Fig. S1D). The survival rate of MdPUB23-overexpressing Arabidopsis was lower than that of the Col-0 after cold-stress treatment (Fig. 4H, I). These results indicate that MdPUB23 negatively regulates cold-stress tolerance.
Given that MdPUB23 encodes a E3 ubiquitin ligase and MdICE1 acts as an interaction partner of MdPUB23, we questioned whether MdPUB23 could mediate the ubiquitination of the MdICE1 protein. In vitro ubiquitination assays showed that only when ATP, ubiquitin, E1, E2, and MdPUB23-HIS were present at the same time would ubiquitin-modification bands appear for MdICE1-GST (Fig. 5A), suggesting that MdICE1 is a direct target of MdPUB23 ubiquitination. In addition, we detected the ubiquitination of MdICE1 by MdPUB23 in vivo. Apple calli of single transgenic MdICE1 and co-transgenic MdICE1 and MdPUB23 were prepared (Supplementary Fig. S1A and E). The MdICE1-GFP protein was immunocoprecipitated with GFP antibody and detected with GFP and ubiquitin antibodies. The results showed that the overexpression of MdPUB23 significantly increased the degree of polyubiquitination of MdICE1 (Fig. 5B), demonstrating that MdPUB23 mediates the ubiquitination of MdICE1 in vivo. Moreover, we found that cold stress enhanced MdICE1 ubiquitination and this process was dependent on MdPUB23 (Fig. 5C).
To assess whether MdPUB23 affected the protein stability of MdICE1, in vitro protein-degradation assays were performed. The MdICE1-GST fusion protein was incubated with total proteins extracted from WT and MdPUB23 transgenic apple calli. Western blotting analysis showed that the degradation rate for MdICE1-GST was higher in MdPUB23-overexpressing calli than in the WT control, while the suppression of MdPUB23 expression reduced the degradation rate for the MdICE1 (Fig. 6A). When the proteasome inhibitor MG132 was applied, degradation of MdICE1 was completely abolished (Fig. 6A), indicating that MdPUB23 promotes MdICE1 degradation via the 26S-proteasome pathway. Next, we detected the protein abundance of MdICE1 in the MdICE1 single and MdICE1–MdPUB23 co-transformed apple calli using a GFP antibody. The results showed that the overexpression of MdPUB23 decreased, while the suppression of MdPUB23 increased the abundance of the MdICE1 protein (Fig. 6B). These results suggest that MdPUB23 targets MdICE1 for ubiquitinated degradation. Moreover, we found that cold stress promoted MdICE1 degradation and this process was dependent on MdPUB23 (Fig. 6C and Supplementary Fig. S2).
Because MdPUB23 mediates the ubiquitin degradation of MdICE1 and negatively regulates cold-stress tolerance, we further investigated whether MdPUB23 played a role in MdICE1-mediated cold-stress resistance. Apple calli co-transformed for MdICE1 and MdPUB23 were prepared and used for cold-stress assays (Supplementary Fig. 1E). After cold-stress treatment, the overexpression of MdPUB23 inhibited the growth of calli compared with the WT control, while the suppression of MdPUB23 expression contributed to the growth of calli (Fig. 4A–B). After cold-stress treatment, the overexpression of MdICE1 increased calli growth compared with the WT control, which was consistent with previous research results (Fig. 7A, B) [37]. The overexpression of MdPUB23 on the basis of MdICE1-OX inhibited MdICE1-mediated cold resistance, while the suppression of MdPUB23 expression further improved MdICE1-induced cold resistance (Fig. 7A–B), suggesting that MdPUB23 negatively regulates MdICE1-increased cold-stress tolerance. In parallel, we generated apple leaves and Arabidopsis seedlings co-transformed with MdICE1 and MdPUB23 (Supplementary Fig. 1F and G). As expected, cold-stress assays showed that the overexpression of MdPUB23 reduced MdICE1-induced cold-stress tolerance in apple leaves and Arabidopsis seedlings (Fig. 7C–F). Taking these data together, we conclude that MdPUB23 negatively regulates MdICE1-induced cold-stress tolerance by targeting MdICE1 for ubiquitinated degradation.
As one of the most productive and consumed fruits in the world, apples are popular for their rich nutritional value. In the process of apple cultivation and management, extreme-low-temperature disasters result in inestimable losses in fruit-tree production. Preventing and reducing the harm to fruit trees caused by extreme low temperatures is a prerequisite for stable and high yields for fruit trees. Therefore, it is of great practical significance to study the mechanism of the response to low-temperature stress in apple. In the present study, an apple U-box-type E3 ubiquitin ligase, MdPUB23, induced by cold stress at the transcriptional level (Fig. 3), acted as a negative regulator of the cold-stress response (Fig. 4). ICE1 is recognized as a key regulator of the cold-stress response that enhances the cold-stress resistance of plants by directly mediating the expression of CBFs [18,38, 39]. The ICE1–CBF module plays an important role in the regulation of plant growth and development and the cold-stress response [11, 38, 39]. As a core regulator of the cold-stress response, the protein abundance of ICE1 remains dynamically stable in plants. In Arabidopsis, the protein kinases MPK3/6 and BIN2 negatively regulate the stability of the ICE1 protein, whereas OST1 increases the stability of ICE1 [28, 42–44]. In addition, the SUMO E3 ligase SIZ1 also enhances the protein stability of ICE in the cold-stress response [45]. In addition to phosphorylation and sumoylation, ubiquitination plays an essential role in the regulation of protein stability and activity of ICE1. The E3 ubiquitin ligase HOS1 targets ICE1 for degradation, thus negatively regulating the cold-stress response in Arabidopsis and rice [41, 46]. The banana fruit SINA E3 ubiquitin ligase MaSINA1 interacts with MaICE1 and attenuates its protein stability, reducing cold-stress tolerance [48]. Besides HOS1 and SINA1, no other E3 ubiquitin ligases have been found to regulate the protein stability of ICE1. Here, we used MdICE1 as the bait protein to obtain an E3 ubiquitin ligase, MdPUB23, which may be an interaction partner of MdICE1. The direct interaction between MdPUB23 and MdICE1 was verified by Y2H, pull-down, and BiFC assays (Fig. 1). PUBs encode a class of E3 ubiquitin ligase proteins characterized by a specific U-box domain [65, 85]. As a typical U-box protein, MdPUB23 contains a U-box motif in the N-terminal region (Fig. 2A). Sequence alignment and phylogenetic tree analysis showed that MdPUB23 shared the highest sequence identity and the closest relationship with PbPUB23 (Fig. 2B–C). PUB E3 ubiquitin ligases are involved in the regulation of multiple stress responses, including the cold-stress response [63–65]. OsPUB2 and OsPUB3 positively regulate the low-temperature-stress response in rice [86]. In Vitis pseudoreticulata, VvPUB24 enhances cold-stress tolerance by alleviating the ubiquitin degradation of VvICE1 by VvHOS1 [87]. A recent study showed that Arabidopsis PUB25 and PUB26 enhanced the cold-stress response by promoting the degradation of MYB15, a negative regulator of cold stress [81]. However, the mechanism of the PUB-mediated cold-stress response remains unclear, especially in apple. Different from the results for V. pseudoreticulata showing that VvPUB24 interacts with VvICE1 but cannot directly regulate the stability of VvICE1 [87], we found that MdPUB23 directly interacted with MdICE1 to promote the ubiquitination degradation of MdICE1 in apple, thus negatively regulating MdICE1-induced cold-stress tolerance (Figs 5, 6 and 7), which suggests that the functions and regulatory mechanisms of proteins in the same family may be also different in different species. Previous studies on the functions of PUB23 have focused on plant immunity and drought stress [66, 71, 73]. The study of PUB23’s involvement in the cold-stress response in this work will further enrich the knowledge of its biological functions. A hypothetical model is proposed to demonstrate the role of MdPUB23 in the cold-stress response (Fig. 8). Under cold-stress conditions, MdICE1 enhances cold-stress tolerance through the ICE1–CBF–COR transcription cascade pathway. In addition, cold stress can also promote the expression of MdPUB23, which targets the MdICE1 protein for degradation through the 26S-proteasome pathway, thus maintaining ICE1-protein homeostasis and preventing overreactions from causing damage to plants. This study reveals the ubiquitination regulation of the ICE1 protein, providing new insights for further enriching knowledge on and studying the regulatory pathways of plant cold-stress responses.
The plant materials used in this study included apple calli (Malus domestica, Orin), apple tissue culture seedlings (M. domestica, GL-3), and Arabidopsis seedlings (Arabidopsis thaliana, Col-0). The detached apple leaves were collected from apple tissue culture seedlings. The growth conditions of plant materials can be queried in previous studies in our laboratory [33].
MdICE1 and MdPUB23 genes were cloned by using PCR technology from the apple tissue culture seedlings GL-3. To construct the MdICE1 and MdPUB23 overexpression recombinant plasmids, full-length MdICE1 and MdPUB23 were cloned into pCXSN-GFP and pRI101 vectors, respectively. The fragment of MdPUB23 was cloned into the pCXSN vector to construct the MdPUB23 suppression expression recombinant plasmid. Transgenic apple calli and leaves were obtained as previously described in our laboratory [37]. The primers used in this study are listed in Supplementary Table S1.
The MdICE1-GFP protein was extracted from MdICE1-overexpressing apple calli and analysed by mass spectroscopy to screen the MdICE1-interacting proteins [88].
TRIzol RNA extraction solution (Thermo Fisher Scientific, Waltham, MA, USA) and a PrimeScript™ RT kit (Takara, Dalian, China) were used for RNA extraction and reverse transcription, respectively, as previously described in our laboratory [88]. qRT-PCR analysis was performed to determine the expression levels of cold-stress-responsive genes.
The interaction between MdPUB23 and MdICE1 was studied by Y2H, pull-down, BiFC, and Co-IP assays. Detailed experimental methods can be found in the Supplementary Experimental Procedures 1–4.
Cold-stress assays of apple calli, detached apple leaves, and Arabidopsis seedlings were performed as previously described in our laboratory [37]. After cold-stress treatment, the fresh weight of the calli, reactive oxygen species (ROS) staining of the leaves, and survival rate of the Arabidopsis seedlings were determined.
The ROS of apple leaves after cold-stress treatment were dyed with diaminobenzidine (DAB) and nitroblue tetrazolium (NBT) as previously described in our laboratory [37].
In vitro ubiquitination and protein-degradation assays were performed as previously described in our laboratory [37].
MdPUB23, MD14G1040300 (MDP0000773851); MdPUB26, MDP0000448457; MdICE1, MDP0000662999; MdCBF1, HM992942; MdCBF2, MDP0000198054; MdCBF3, Genomic position: MDC023575.38:2048.0.2752; MdCBF4, MDP0000154764; MdCBF5, Genomic position: MDC001207.483:32385.0.33047; MdMYB23, MDP0000230141; MdMYB308L, MDP0000950559; MdbHLH3, MDP0000225680; MdbHLH33, MDP0000309179; MdBBX37, MDP0000157816; MdABI4, MD01G1155400; MdHY5, MDP0000586302; MdKIN1, MDP0000165526; MdRD29A, MDP0000598443; MdCOR47, MDP0000529003; MdACTIN, EB136338.
This work was financially supported by grants from the China postdoctoral Science Foundation (2022 M710086), the Natural Science Foundation of China (32172538), and the Open Project Programme of the State Key Laboratory of Crop Biology (2021KF06).
J.-P.A. conceived and designed the experiments. D.-R.W. and J.-P.A. performed the research. X.-W.Z., R.-R.X., G.-L.W., and C.-X.Y. analysed the data. J.-P.A. wrote the paper.
All the data generated or analysed during this study are included in this published article.
The authors declare no competing interests.
Supplementary data is available at Horticulture Research online.
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PMC9557225 | Jun-Yan Liu,Jing Yao,Jia-Jia Liu,Tao He,Fang-Jie Wang,Tian-Yu Xie,Jian-Xin Cui,Xiao-Dong Yang | LASTR is a novel prognostic biomarker and predicts response to cancer immunotherapy in gastric cancer | 29-09-2022 | lncRNA LASTR,ferroptosis,prognosis,biomarker,gastric cancer | Gastric cancer (GC), a malignant tumor of digestive tract, is characterized by a high death rate. Thus, it is of particular importance to clarify the mechanisms of GC and gain new molecular targets for the sake of preventing and treating GC. It was reported that long non-coding RNAs (IncRNAs) are prognostic factors to cancer. Ferroptosis refers to a process of programmed cell death dependent on iron. This study sets out to investigate the expression and function of ferroptosis-related lncRNA (FRlncRNA) in GC. TCGA datasets offered RNA-seq data for 375 GC patients and clinical data for 443 GC patients. Based on Pearson’s correlation analysis, we studied their expression and identified the FRlncRNAs. Differentially expressed prognosis related to FRlncRNA were determined with the help of the Wilcoxon test and univariate Cox regression analysis. To evaluate the accuracy of the prognostic capacity, researchers used the Kaplan-Meier technique, as well as univariate and multivariate Cox regression and receiver operating characteristic (ROC) curve studies. We also carried out the real-time PCR and CCK8 assays to examine the expression and function of FRlncRNA. In this study, we identified 50 ferroptosis-related DEGs which were involved in tumor progression. In addition, we identified 33 survival-related FRlncRNAs. Among them, lncRNA associated with SART3 regulation of splicing(LASTR) was confirmed to be highly expressed in GC specimens compared to non-tumor specimens in this cohort. Survival assays illuminated that the high LASTR expression predicted a shorter overall survival and progression-free survival of GC patients. Based on multivariate Cox regression analyses, it was confirmed that the GC had a worse chance of surviving the disease overall if their tumors expressed LASTR, which was an independent prognostic indication. Then, Loss-of-function tests showed that knocking down LASTR had a significant effect on reducing the proliferation of GC cells. Finally, we found that the expression of LASTR was negatively associated with CD8 T cells, T cells, Th17 cells, and T helper cells. Overall, our findings identified a novel survival-related FRlncRNA, LASTR which possibly can serve as a novel prognostic biomarker predicting response to cancer immunotherapy and therapeutic target for GC patients. | LASTR is a novel prognostic biomarker and predicts response to cancer immunotherapy in gastric cancer
Gastric cancer (GC), a malignant tumor of digestive tract, is characterized by a high death rate. Thus, it is of particular importance to clarify the mechanisms of GC and gain new molecular targets for the sake of preventing and treating GC. It was reported that long non-coding RNAs (IncRNAs) are prognostic factors to cancer. Ferroptosis refers to a process of programmed cell death dependent on iron. This study sets out to investigate the expression and function of ferroptosis-related lncRNA (FRlncRNA) in GC. TCGA datasets offered RNA-seq data for 375 GC patients and clinical data for 443 GC patients. Based on Pearson’s correlation analysis, we studied their expression and identified the FRlncRNAs. Differentially expressed prognosis related to FRlncRNA were determined with the help of the Wilcoxon test and univariate Cox regression analysis. To evaluate the accuracy of the prognostic capacity, researchers used the Kaplan-Meier technique, as well as univariate and multivariate Cox regression and receiver operating characteristic (ROC) curve studies. We also carried out the real-time PCR and CCK8 assays to examine the expression and function of FRlncRNA. In this study, we identified 50 ferroptosis-related DEGs which were involved in tumor progression. In addition, we identified 33 survival-related FRlncRNAs. Among them, lncRNA associated with SART3 regulation of splicing(LASTR) was confirmed to be highly expressed in GC specimens compared to non-tumor specimens in this cohort. Survival assays illuminated that the high LASTR expression predicted a shorter overall survival and progression-free survival of GC patients. Based on multivariate Cox regression analyses, it was confirmed that the GC had a worse chance of surviving the disease overall if their tumors expressed LASTR, which was an independent prognostic indication. Then, Loss-of-function tests showed that knocking down LASTR had a significant effect on reducing the proliferation of GC cells. Finally, we found that the expression of LASTR was negatively associated with CD8 T cells, T cells, Th17 cells, and T helper cells. Overall, our findings identified a novel survival-related FRlncRNA, LASTR which possibly can serve as a novel prognostic biomarker predicting response to cancer immunotherapy and therapeutic target for GC patients.
Gastric cancer (GC) is the third leading cause of cancer-related death (1). Globally, it is the fifth most common cancer with up to 1 million new gastric cancer cases and 783, 000 deaths projected in 2018 (2). While the number of inpatient admissions for GC has been dropping in the last few decades, the healthcare burden and expenditure it brought about experienced a tremendous growth (3, 4). There are many factors accounting for the occurrence of GC, including alcoholic abuse, irregular dieting, incorrect dieting habit and gene heredity (5, 6). Whether the perioperative chemotherapy and radiotherapy are implemented or not, the prognosis of GC patients are still poor (7, 8). An integrated understanding of the molecular mechanism of GC is conducive to develop efficient therapeutic methods and to ameliorate the clinical results of GC patients (9, 10). At present, surgical resection and chemotherapy are the first choices of GC treatments, since they can considerably avoid the recurrence and metastasis of GC. Consequently, to find out a sensitive diagnostic approach for the early gastric caner and facilitate prognosis, it is necessary to elucidate the molecular biological mechanism of this cancer. Growing evidences from high-throughput sequencing have demonstrated that <2% of genes have protein-coding capacity, while >75% of gene transcripts are non-coding RNAs (11, 12). Therefore, concentrating on protein-coding genes may be ineffective to explore the mechanisms associated with tumorigenesis. A collection of non-coding transcripts that are more than 200 nucleotides long are known as long non-coding RNAs (lncRNAs) (13). While they are extremely similar in genetic organization, they play a variety of roles at the cellular level, such as regulating transcription and translation, altering gene expression and regulating the expression of chromosomally neighboring genes (14, 15). According to the findings of a number of studies, lncRNAs are at the center of a wide variety of physiological and pathological processes, including the progression of the cell cycle, the occurrence of apoptosis during the process of cellular differentiations, and immune function (16, 17). They are essential components in the processes of post-transcriptional control, transcriptional repression and chromatin remodeling (18, 19). In addition, more and more studies have reported that some functional lncRNAs possibly can serve as novel diagnostic and prognostic biomarkers for tumor patients (20, 21). However, to date, only few studies have documented lncRNAs in GC and the underlying mechanisms remain largely unknown. Ferroptosis refers to a form of iron-dependent programmed cell death, featuring lipid peroxidation (22). With the development of study, ferroptosis is engaged in various crucial biological processes, such as cancer, ischemia-reperfusion injury, and neurodegenerative maladies (23). Ferroptosis is a crucial regulatory mechanism for tumor growth, and it is central to the chemoradiotherapy and immunotherapy treatment of malignancies, according to several studies that were conducted not too long ago (24, 25). Thus, these therapeutic approaches, when paired with drugs that target iron death signals, assist to increase their overall effectiveness against tumors. In gastric cancer, it was shown that the lncRNA known as PVT1 was elevated and had a significant relationship to both high microvessel density and a bad prognosis. Based on the gain- and loss-of PVT1 expression, PVT1 was found to be able to evidently trigger angiogenesis within tumors, apart from enhancing tumor growth by means of modulating the STAT3/VEGFA axis in vitro and in vivo. It should be noted that the carcinogenesis of lncRNA PVT1 is linked to ferroptosis (26). Up till now, it is not yet known in its entirety how ferroptosis-related lncRNAs contribute to the advancement of GC, and it is imperative that their vital significances in GC treatment and prognosis be further defined in the future. This study identified 33 survival-related Ferroptosis-Related lncRNAs(FRlncRNA). Among them, our attention focused on lncRNA associated with SART3 regulation of splicing(LASTR) which was highly expressed in our cohort and TCGA datasets. Moreover, we analyzed the prognostic value of LASTR expression among patient with GC and the potential function in vitro experiments. These findings may provide a new a prognostic marker and therapeutic target for patients with GC.
This study was composed of 11 GC specimens and the matched 11 para-tumorous specimens. Three pathologists were responsible for the confirmation of the histologic diagnosis. Patients participating in the study received surgery at The First Medical Center, Chinese PLA General Hospital, and the fresh tissues were snap-frozen in liquid nitrogen and preserved at −80°C for the next studies. We also gained the written informed consent of all patients and the approval of the Ethics Committee of The First Medical Center, Chinese PLA General Hospital.
The Type Culture Collection of the Chinese Academy of Medical Science supplied the control human GES-1 gastric mucosa epithelial cells as well as the four GC cell lines (HGC-27, BGC-823, AGS and MGC-803). In a humidified incubator with 5 percent CO2, RPMI-1640 medium (Hyclone, Massachusetts, USA) with 10 percent fetal bovine serum (Hyclone) and penicillin/streptomycin was used to cultivate the cells. Oligonucleotides, including negative control siRNA and LASTR siRNA were synthesized by GenePharma (Shanghai, China). Lipofectamine 3000 was employed to transfect GC cells for in vitro assays. 48 hours after this transfection, cells were collected for the downstream analyses.
TRIzol (Invitrogen; Thermo Fisher Scientific, Inc.) was applied to extract total RNA from GC samples and cells, and then the total RNA was reverse-transcribed into cDNA using SuperScript Reverse Transcriptase III (Invitrogen, China) in accordance with the instructions provided by the manufacturer. The following parameters were utilized for quantitative PCR reactions that were carried out using an ABI 7500 PCR System with the use of SYBR-Green Supermix (Applied Biosystems; Thermo Fisher Scientific, Inc.): Initial denaturation at 95 degrees Celsius for thirty seconds, followed by forty cycles of denaturation at 95 degrees Celsius for five seconds, annealing at 60 degrees Celsius for thirty seconds, and then a study of the melting curve. Fluorescent signals detection was carried out after every cycle. Using the 2−ΔΔCq methods, relative mRNA expression levels were determined after being normalized to either GAPDH. The primer sequences were presented in Table 1 .
Cells that were in the log phase were collected 24 hours after the transfection and planted into a 96-well plate at a density of 5 x 103 cells per well, with 100 μL of media present in each well. At certain time intervals (24 h, 48 h, and 72 h), 10 μL of CCK-8 was added, and the mixture was then incubated with the cells for an additional 2 hours. In the end, the optical density(OD) values of the cells were examined at a wavelength of 450 nm using a MultiskanTM FC microplate reader manufactured in the United States by Thermo ScientificTM. The abscissa represented the passage of time, whereas the ordinate was denoted by OD value.
The Genomic Data Commons Data Portal was used to obtain the RNA-sequencing and clinical information for the GC samples that were part of the TCGA (GDC1). Additionally, we downloaded a “HTSeq-FPKM” workflow type of transcriptome profiling for the TCGA-STAD project. This workflow type of transcriptome profiling included the gene expression profiles of 375 cancer tissue samples and 32 normal tissue samples. The “bcr xml” file type was used to obtain the clinical information for all 443 GC tissues that came from the TCGA-STAD.
FerrDb is the first manually curated resource for regulators and markers of ferroptosis, and it was launched in December 2019; we were able to obtain 259 gene sets linked with ferroptosis from this database (22). Our group applied the limma package in R for the identification of the ferroptosis-associated lncRNAs that were found based on the correlation analysis between ferroptosis-related genes and IncRNA expressions in the GC samples. This analysis was based on the fact that there was a positive correlation between these two factors. After calculating the Pearson correlation coefficients, the threshold was determined to be a correlation coefficient of > 0.4 and a probability value of < 0.001.
The DEGs between GC specimens and non-tumor specimens were filtered in light of specific criteria (|log2FC| ≥ 2 and FDR < 0.05). On the basis of these DEGs, GO and KEGG analyses were accomplished with the help of the “clusterProfiler” package (27).
Ferroptosis-related lncRNAs related to survival were assessed by means of univariate Cox regression analysis.
The survival date from the samples of TCGA was also available. Overall survival (OS) and progression-free survival(PFS) were thought to be the indicators for the exploration of relevancy between LASTR expression and patient prognosis. With respect to survival analyses, the Kaplan-Meier method and log-rank test were adopted in each cancer type. The survival curves were drawn using R packages “survival” and “survminer”. Besides, the R packages “forestplot” was used to figure out the relationship between LASTR expression and survival in pan-cancer.
R statistical software version 4.0.4 and strawberry-perl-5.32.0.1 were employed to conduct all the statistical analyses. The two independent groups were compared using the Student’s t-test. We also conducted the univariate Cox regression analysis and multivariate Cox regression analysis to determine OS’s independent prognostic factors. Moreover, we carried out time-dependent ROC curve analysis to assess the predictive accuracy of the prognostic model for OS. Statistical significance was defined as p value <0.05 with all p values two-tailed.
Firstly, we screened ferroptosis-related DEGs between GC specimens and non-tumor specimens on the basis of TGCA datasets, and identified 50 ferroptosis-related DEGs, including 20 down-regulated ferroptosis-related DEGs and 30 upregulated ferroptosis-related DEGs. Then, we used these genes to fulfill GO and KEGG assays. We found that the 50 ferroptosis-related DEGs were mainly associated with reaction to oxidative stress, cellular reaction to chemical stress, reactive oxygen species metabolic process, oxidoreductase complex, NADPH oxidase complex, endocytic vesicle, oxidoreductase activity, acting on NAD(P)H, iron ion binding and superoxide-generating NAD(P)H oxidase activity ( Figure 1A ). KEGG assays revealed that the 50 ferroptosis-related DEGs were mainly concentrated in Fluid shear stress and atherosclerosis, Lipid and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, Kaposi sarcoma-associated herpesvirus infection, HIF-1 signaling pathway, Human T-cell leukemia virus 1 infection and Human cytomegalovirus infection ( Figure 1B ).
We uncovered 1336 ferroptosis-related lncRNAs. To identify the survival-related FRlncRNAs, Univariate Cox regression analysis was conducted and 33 survival-related FRlncRNAs were identified ( Figure 2 ). Among the above lncRNAs, it has been reported that some of them participant in the progression of several tumors, such as GC.
In order to screen critical FRlcnRNAs, we performed RT-PCR using four survival-related FRlncRNAs, including LINC0711, LINC01094, LINC01614 and LASTR. We found that the expression of LINC0711, LINC01094 and LINC01614 failed to exhibit an apparent difference between GC samples and non-tumor samples( Figures 3A-C ). However, LASTR expressions were evidently increased in GC specimens ( Figure 3D ). Then, our attention focused on LASTR.
Then, to further identify LASTR’s expression in GC, TCGA datasets were analyzed. Consequently, it was found that the expression of LASTR was distinctly increased in GC specimens compared to non-tumor specimens ( Figure 4A ). Moreover, efforts were made to study the relationship between LASTR expressions and clinical factors in GC patients. However, it was found that LASTR expression was not associated with age ( Figure 4B ), gender ( Figure 4C ), grade ( Figure 4D ), clinical stage ( Figure 4E ), T stage ( Figure 4F ), M stage ( Figure 4G ) and N stage ( Figure 4H ).
A Kaplan-Meier survival analysis and log-rank tests were employed. The results revealed that patients in high LASTR expression group showed poorer OS(p=0.020, Figure 5A ) and PFS(p=0.004, Figure 5B ) compared with those in low LASTR expression group (p = 0.0010). Moreover, the time-dependent ROC curve was conducted for the estimation of the performance of the risk prediction model. The AUC of LASTR was 0.571, 0.574, and 0.757 at 1, 3, and 5 years, respectively ( Figure 5C ). To further examine the clinical value of LASTR expressions in GC patients, univariate and multivariate assays were carried out based on Cox’s proportional hazard model. According to the univariate analysis, age, clinical stage, and LASTR expression were greatly linked to the overall survival of GC patients ( Figure 6A ). Moreover, through the multivariate Cox regression analyses, it was confirmed that the LASTR expression was an independent prognostic indicator to the overall survival (HR = 1.557; 95% CI, 1.147-2.113; p = 0.005) among GC patients ( Figure 6B ). These outcomes showed that LASTR expression might be consider as an important independent prognostic factor.
To investigate whether LASTR knockdown inhibited GC cell growth, at first, the expression of LASTR in four GC cells was examined using RT-PCR, and it was found that LASTR expression was greatly increased in four GC cells compared to GES-1 ( Figure 7A ). Because LASTR exhibited a higher level in BGC-823 and HGC-27 cells, we chose them for further in vitro experiments. To probe the biological function of LASTR, we designed small interfering RNAs (siRNAs) that can specifically target LASTR. As shown in Figure 7B , LASTR was effectively silenced by siRNA. Then, we assessed whether the knockdown of LASTR could affect the biological function of BGC-823 and HGC-27. The outcomes of CCK-8 assay revealed that knockdown of LASTR greatly restrained the proliferation of BGC-823 and HGC-27 cells ( Figures 7C, D ).
Then, we explored the correlation between immune infiltration and LASTR expression. As shown in Figure 8 , we found that the expression of LASTR was negatively associated with TFH, B cells, CD8 T cells, Treg, T cells, Th17 cells and T helper cells.
Since GC is a highly heterogeneous malady featuring a high death rate and imperceptible symptoms, patients tend to be diagnosed with it until the late stage (28). Though the treatments for GC is updated continuously, the 5‐year survival rate remains disappointing. The first choice for better foreseeing tumor behavior and instructing the treatment scheme is to determine the informative diagnostic and prognostic biomarkers of GC (29, 30). So far, scientists have found that lncRNAs regulate target gene expression and acts as oncogenes or tumor suppressors. As the fast growth of high throughput genomic sequencing technologies, lncRNAs prove to be valuable biomarkers to more accurately assess the prognosis of various tumors. Mounting research reveals a connection between autophagy and ferroptosis and tumor growth, as these two RCD subtypes are inextricably linked (22). Nevertheless, the involvement of lncRNAs in GC autophagic and ferroptotic processes was under-studied. This study screened ferroptosis-related DEGs between GC specimens and non-tumor specimens on the basis of TGCA datasets, and identified 50 ferroptosis-related DEGs, including 20 down-regulated ferroptosis-related DEGs and 30 upregulated ferroptosis-related DEGs. Furthermore, KEGG assays illuminated that the 50 ferroptosis-related DEGs were mainly concentrated in Fluid shear stress and atherosclerosis, Lipid and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, Kaposi sarcoma−associated herpesvirus infection, HIF-1 signaling pathway, Human T-cell leukemia virus 1 infection and Human cytomegalovirus infection, suggesting these ferroptosis-related DEGs play a central part in the development of tumors. Then, 33 survival-related FRlncRNAs were identified. We chose LINC0711, LINC01094, LINC01614 and LASTR to demonstrate their expression in GC. Interestingly, we only found that LASTR expression was significantly increased in GC specimens in this cohort, which was further confirmed in TCGA datasets. These findings supported that LASTR was an important player in GC. In recent years, only a few studies mentioned the function of LASTR in some tumors. For example, it was reported that the expressions of LASTR in lung cancer samples (LUAD and LUSC) were significantly higher than those in neighboring normal tissue. Patients whose LASTR expression levels were higher had a shorter overall survival and worse clinical characteristics, as determined by the Kaplan-Meier survival analysis, in comparison to patients whose LASTR expression levels were lower. This resulted in a lower overall survival rate. Knockdown of LASTR considerably curbed the proliferation and metastatic ability of lung cancer cells through the miRNA-137/TGFA axis (31). After that, the further analysis of the prognostic value of LASTR expression in GC patients found that high LASTR expression was related to shorter OS and PFS in GC patients. More importantly, through multivariate Cox regression analysis, it was confirmed that the LASTR expression was an independent prognostic indicator to the overall survival of GC patients. Finally, the loss of function experiments was performed and it was observed that the knockdown of LASTR greatly restrain the proliferation of GC cells, indicating that it is an oncogenic lncRNA in GC progression. The tumor microenvironment, which harbors multiple immune and stromal cell types, is a key determinant of tumor progression and antitumor immunity (32). Growing studies have reported the positive associations between lncRNAs and TME immune cell infiltration (33, 34). In our study, we also observed the expression of LASTR was negatively associated with TFH, B cells, CD8 T cells, Treg, T cells, Th17 cells and T helper cells. Our findings suggested that LASTR may be a potential biomarker for predicting response to cancer immunotherapy. One limitation of this study was that since it is a retrospective study, missing data and selection biases were unavoidable. Another limitation was that, values of gene expressions obtained from RNA‐seqs or microarrays were all relative. Hence, it was impossible to determine the absolute thresholds of stratifications in different cohorts. With median cutoff values involved in each data, there will be a need for accurate external validations. In addition, we just performed in vitro experiments to test the function of LASTR knockdown on the proliferation of GC cells, more in vivo experiments were needed to further confirm our findings.
We found LASTR as an overexpressed lncRNA in GC. Meanwhile, LASTR was validated to be a novel prognostic biomarker for patients with GC. Moreover, knockdown of LASTR was confirmed to inhibit the proliferation of GC cells. The facts above pointed out that LASTR might be quite vital for the diagnosis and development of GC, and could even become an important therapeutic target for GC patients.
The original contributions presented in the study are included in the article/supplementary materials. Further inquiries can be directed to the corresponding authors.
The studies involving human participants were reviewed and approved by The First Medical Center, Chinese PLA General Hospital. The patients/participants provided their written informed consent to participate in this study.
J-YL, JY, J-XC and X-DY designed the research. J-YL, J-JL, TH and F-JW performed the research and collected the data. JY, F-JW and T-YX analyzed the data. J-Y: and JY drafted the manuscript. All authors contributed to the article and approved the submitted version.
This work was supported by the State Key Program of National Natural Science Foundation of China(No. NO.62133010).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9557250 | Hong Ma,Peng Ye,Ai-kai Zhang,Wan-de Yu,Song Lin,Ya-guo Zheng | Upregulation of miR-335-5p Contributes to Right Ventricular Remodeling via Calumenin in Pulmonary Arterial Hypertension | 04-10-2022 | Right ventricular (RV) failure determines the prognosis in pulmonary arterial hypertension (PAH), but the underlying mechanism is still unclear. Growing evidence has shown that microRNAs participate in RV remodeling. This study is undertaken to explore the role of miR-335-5p in regulating RV remodeling induced by PAH. Two PAH models were used in the study, including the monocrotaline rat model and hypoxia/su5416 mouse model. miRNA sequencing and RT-qPCR validation identified that miR-335-5p was elevated in the RV of PAH rats. In vitro, miR-335-5p expression was increased after angiotensin II treatment, and miR-335-5p inhibition relieved angiotensin II-induced cardiomyocyte hypertrophy. The luciferase reporter assay showed that calumenin was a target gene for miR-335-5p. Pretreatment with miR-335-5p inhibitors could rescue calumenin downregulation induced by angiotensin II in H9C2 cells. Moreover, intracellular Ca2+ concentration and apoptosis were increased after angiotensin II treatment, and miR-335-5p inhibition decreased intracellular Ca2+ accumulation and apoptosis. Finally, in vivo miR-335-5p downregulation (antagomir miR-335-5p) attenuated RV remodeling and rescued calumenin downregulation under conditions of hypoxia/su5416 exposure. Our work highlights the role of miR-335-5p and calumenin in RV remodeling and may lead to the development of novel therapeutic strategies for right heart failure. | Upregulation of miR-335-5p Contributes to Right Ventricular Remodeling via Calumenin in Pulmonary Arterial Hypertension
Right ventricular (RV) failure determines the prognosis in pulmonary arterial hypertension (PAH), but the underlying mechanism is still unclear. Growing evidence has shown that microRNAs participate in RV remodeling. This study is undertaken to explore the role of miR-335-5p in regulating RV remodeling induced by PAH. Two PAH models were used in the study, including the monocrotaline rat model and hypoxia/su5416 mouse model. miRNA sequencing and RT-qPCR validation identified that miR-335-5p was elevated in the RV of PAH rats. In vitro, miR-335-5p expression was increased after angiotensin II treatment, and miR-335-5p inhibition relieved angiotensin II-induced cardiomyocyte hypertrophy. The luciferase reporter assay showed that calumenin was a target gene for miR-335-5p. Pretreatment with miR-335-5p inhibitors could rescue calumenin downregulation induced by angiotensin II in H9C2 cells. Moreover, intracellular Ca2+ concentration and apoptosis were increased after angiotensin II treatment, and miR-335-5p inhibition decreased intracellular Ca2+ accumulation and apoptosis. Finally, in vivo miR-335-5p downregulation (antagomir miR-335-5p) attenuated RV remodeling and rescued calumenin downregulation under conditions of hypoxia/su5416 exposure. Our work highlights the role of miR-335-5p and calumenin in RV remodeling and may lead to the development of novel therapeutic strategies for right heart failure.
Pulmonary arterial hypertension (PAH) is a progressive lethal disease which is manifested as right heart failure and premature death [1]. Right ventricular (RV) adaptation and failure dramatically impact the prognosis of PAH [2]. The right ventricle exposed to chronic pressure overload adaptively exhibits concentric hypertrophy and maintains normal cardiac output. However, if the pathologic condition persists, it transits to maladaptive hypertrophy, presented as excessive fibrosis, decreased cardiac output, and right heart failure [3]. Current PAH therapies focus on pulmonary vascular remodeling; no RV-specific therapies exist. Therefore, exploring the underlying mechanisms of RV remodeling is urgent. MicroRNAs (miRNAs) are a class of small noncoding ribonucleic acids which regulate gene expression at post-transcriptional level. Several studies have demonstrated that miRNAs are etiologically implicated in RV remodeling [4, 5]. They exhibit essential roles in hypertrophy and apoptosis of cardiomyocytes, proliferation, and migration of fibroblasts as well as angiogenesis of cardiac microvascular endothelial cells. Several miRNAs have been reported [6–9], including upregulated miR-21, miR-214, miR-199a, and miR-199b and downregulated miR-126, miR-223, miR-208, and miR-34. In the present study, through the use of RNA sequencing, we found that miR-335-5p was significantly increased in the RV of PAH rats, indicating that miR-335-5p may be implicated in RV hypertrophy and fibrosis induced by PAH. miR-335-5p is a regulated intronic miRNA which is encoded by the second intron of the mesoderm-specific transcript gene. It has been related to certain types of cancer and participates in many oncogenic signaling pathways [10, 11]. It is a tumor suppressor gene and inhibits tumor cell proliferation, migration, and invasion. miR-335-5p was highly expressed in cardiomyocytes, and it was involved in cardiac differentiation through regulating mesoderm and progenitor marker expression via WNT and TGF-β signaling pathways [12]. Bioinformatics analysis also suggested that miR-335-5p might be associated with left ventricular remodeling after myocardial infarction [13]. But the role of miR-335-5p in RV remodeling remains unclear. In the present study, we noted that miR-335-5p was significantly increased in the RV at 4 weeks following monocrotaline injection. Meanwhile, miR-335-5p expression was upregulated in angiotensin II-induced cardiomyocyte hypertrophy, whereas knockdown of miR-335-5p suppressed these responses. In addition, calumenin (CALU) was shown as a target of miR-335-5p. In the hypoxia/su5416 mouse model, in vivo miR-335-5p downregulation with antagomir miR-335-5p attenuated PAH-induced RV hypertrophy and fibrosis. Collectively, our findings indicated that miR-335-5p promoted RV remodeling, and therefore inhibition of miR-335-5p might be useful for the treatment of right heart failure induced by PAH.
Animals were supplied by the animal center of Nanjing Medical University. We followed the guide for the care and use of laboratory animals, and all the experimental protocols were permitted by the institutional animal care and use committee of Nanjing Medical University. Two PAH models were used in the study, including the monocrotaline (MCT) rat model and hypoxia/su5416 mouse model. Sixteen adult male SD rats at 6 weeks were randomly divided into two groups: the control group (n = 8) and the PAH group (n = 8). Monocrotaline (60 mg/kg, Sigma, St Louis, MO) and vehicle were intraperitoneally injected in each group, respectively. After 28 days, the rats underwent right heart catheterization and echocardiographic assessments. Hypoxia/su5416 mouse model was established according to our previous study [14]. Male C57/BL6 mice at 8 weeks were subcutaneously injected with 20 mg/kg su5416 and then exposed to chronic hypoxia (10% O2) for the subsequent 4 weeks. Twenty-four mice were randomly divided into three groups (n = 8): normoxia control, hypoxia+antagomir NC, and hypoxia+antagomir-335-5p. Antagomir specific for miR-335-5p and a non-specific negative control (NC) were designed as described [15] and synthesized by GenePharma Co., Ltd (Shanghai, China). The sequence of antagomir-335-5p was 5′-mA(s)mC(s)mAmUmUmUmUmUmCmGmUmUmAmUmUmGmCmUmCmU(s)mU(s)mG(s) mA (s)-Chol-3′. The antagomir NC group and antagomir-335-5p group were injected, respectively, via the tail vein with NC and antagomir-335-5p oligonucleotides at 80 mg/kg for 3 consecutive days. After the injection of oligonucleotides, the mice were placed in the hypoxia chamber. Hemodynamic and echocardiographic assessments were performed at day 28 after hypoxia exposure.
Right heart catheterization was performed following our previous published methods [14, 16]. For rats, the polyethylene catheter was inserted into the main pulmonary artery through the right internal jugular vein to acquire mean pulmonary arterial pressure (mPAP). As the catheter could not get into the pulmonary artery for the mice, only right ventricular systolic pressure (RVSP) was measured in the hypoxia/su5416 model. After catheterization, all the animals were sacrificed, and the heart and lung tissues were harvested. The right ventricle (RV) was separated from the left ventricle plus ventricular septum (LV + S) and weighted, respectively. The ratio of RV/(LV + S) was calculated as the right ventricular hypertrophy index (RVHI).
Echocardiography was performed as previously described [17]. After anesthesia, the Vevo 2100 imaging system (Visual Sonics, Toronto, Canada) was used to obtain the echocardiographic images. The following parameters were assessed including RV free wall thickness (RVWT) from the parasternal long-axis view, RV internal diameter, and tricuspid annular plane systolic excursion (TAPSE) from the apical four-chamber view. We also measured pulmonary artery acceleration time (PAAT) and pulmonary artery ejection time (PAET). The PAAT/PAET ratio was then calculated as an indirect measure of systolic PAP.
The lung and heart were fixed in 4% paraformaldehyde solution for light microscopy or 2% glutaraldehyde for transmission electron microscopy. The tissues were dehydrated and embedded in paraffin, and then cut into 5 μm slices for hematoxylin-eosin (HE) and Masson stain. Images were acquired using a light microscope (Nikon, Tokyo, Japan).
Total RNA was extracted from three randomly selected right ventricle tissue samples using Trizol (Invitrogen, CA, USA). Sequencing libraries were prepared with NEBNext® Multiplex Small RNA Library Prep Set for Illumina and sequenced using the Illumina Hiseq 2500/2000 platform. After quality evaluation (FastQC) and data filtering (Cutadapt), the small RNA tags were mapped to a reference sequence using Bowtie without mismatch, to analyze their expression and distribution on the reference sequences. miRNA expression levels were quantified in TPM (transcript per million). DESeq R package was used to analyze the differential expression of miRNA levels between the two groups. The P values were then corrected with the Benjamini-Hochberg method.
H9C2 cells from ATCC were maintained in Dulbecco's modified Eagle's medium (DMEM) which is supplemented with 10% fetal bovine serum. When the cell lines reached 80% confluence, they were digested with 0.05% trypsin-EDTA and plated in a 6-well plate with 3 × 105 cells per well. Next day, the cells were transfected with miR-335-5p inhibitor (5′-ACAUUUUUCGUUAUUGCUCUUGA-3′) or scramble control (5′-CAGUACUUUUGUGUAGUACAA-3′) (GenePharma, Shanghai, China) for 6 hours and then incubated with angiotensin II (0.1 μmol/L, Sigma) to induce cardiomyocyte hypertrophy as described previously [18]. After 48 hours, cells were harvested for gene and protein expression analysis.
Three different algorithms (TargetScan, miRanda, and PicTar) were used to predict target gene of miR-335-5p. All three algorithms suggested that calumenin (CALU) was the downstream target of miR-335-5p. The segments of CALU 3′-UTR containing the putative miR-335-5p binding sites were PCR-amplified, and the amplification product was inserted into the pGL3 vector, resulting in the wild-type pGL3-CALU-3′UTR. The corresponding mutant vectors were formed by using mutated calumenin sequence. HEK293 cells were co-transfected with wild-type and mutated pGL3-CALU-3′UTR with miR-335-5p mimics or negative control, respectively. At 48 h after transfection, the cells were harvested, and dual-luciferase reporter assay kit was used to determine luciferase activity.
After deparaffinizing, heat-mediated antigen retrieval was achieved by incubating sections in sodium citrate buffer (pH 6.0) for 20 minutes. Then, the slices were treated with 3% hydrogen peroxide to quench endogenous peroxidase activity and successively incubated with the primary antibody (rabbit anti-calumenin monoclonal antibody from Abcam Corporation) at 4 °C overnight. After washing three times, the sections were subsequently incubated with biotinylated secondary antibody (Zhongshan Jinqiao Biotechnology) for 30 minutes at room temperature. Finally, diaminobenzidine was added, and the brown color indicated a positive reaction. H9C2 cells were stained with antibodies against ɑ-SMA (Sigma, St. Louis, MO) to measure cardiomyocytes size. After permeabilization with 0.3% Triton X-100 for 10 minutes, non-specific sites were blocked with 1% bovine serum albumin (BSA) for 1 hour. Primary antibody to ɑ-SMA actin was applied at 4 °C overnight. Then, the cells were incubated with the respective secondary antibody at room temperature for 1 hour and followed by DAPI counterstaining. Images were acquired using laser scanning confocal microscopy (LSM 710; Carl Zeiss, Germany).
Total RNA was isolated from the heart tissues and H9C2 cells, and reverse transcription was performed according to the instructions. qPCR was carried out using SYBR Premix Master Mix (Thermo Fisher Scientific Inc., Shanghai, China). The primer sequences were listed in Supplemental Table 1. miRNA analysis was performed using TaqMan MicroRNA Assay (GenePharma, Shanghai, China), and U6 was used as a reference gene.
Total protein was extracted from the heart tissues and H9C2 cells. After protein concentration measurement, these proteins were separated by SDS-PAGE and subsequently transferred to PVDF membranes. Then, the filter membranes were incubated overnight at 4 °C with the primary antibody (Calumenin from Abcam, Collagen I and Collagen III from Cell Signaling). The membranes were further incubated with corresponding secondary antibody for two hours at room temperature and detected using the enhanced chemiluminescence (ECL) system. β-Actin was used as a loading control. The bands were analyzed by the quantity one.
TUNEL Apoptosis Assay Kit (Beyotime Biotechnology, Beijing, China) was used to detect the apoptotic cells. The nuclei were counterstained with DAPI. The positive cells were characterized by green nuclei. The imagines were observed with LSM710 confocal laser scanning microscope (LSM 710; Carl Zeiss, Germany). The cell apoptotic rate was calculated as the percentage of TUNEL-positive cells.
H9C2 cardiomyocytes were incubated with Fluo-3/AM (Beyotime Biotechnology, Beijing, China) at 37 °C for 60 min based on the instructions. The Ca2+ Fluorescence was monitored at 488 nm with LSM710 confocal laser scanning microscope (LSM 710; Carl Zeiss, Germany).
All continuous variables are expressed as mean ± SD (standard deviation). Student's t test was used to determine the statistical difference between the two groups. Differences between multiple groups were compared with ANOVA followed by Bonferroni's post hoc test. All analyses were performed using SPSS version 22.0 (SPSS Inc., Chicago, IL). p value < 0.05 was considered statistically significant.
According to our previous study [16], we established the MCT-induced PAH model. PAH rats displayed significant right ventricular hypertrophy and dysfunction and manifested as decreased TAPSE and increased RVHI, RVWT, and RVID (Figures 1(b), 1(d), 1(e), and 1(g)). HE staining suggested myocyte hypertrophy, focal myolysis, cellular necrosis, and vacuolar degeneration (Figure 1(a)). Moreover, apparent right ventricular fibrosis was also observed in PAH rats (Figure 1(c)). Electron microscopy revealed that there were significant functional mitochondrial changes in right ventricle, characterized by mitochondrial swelling and decreased matrix density (Figure 1(a)).
RNA-Seq results for six right ventricular tissues (n = 3 in each group) were used for a comprehensive analysis. In total, 151 miRNAs (74 upregulated and 77 downregulated) were differentially expressed in PAH rats compared with controls (Figure 2(a)). The top 10 upregulated and downregulated miRNAs are shown in Supplementary Table 2. To verify the reliability of the sequencing results, we selected three upregulated and three downregulated miRNAs for RT-qPCR. The result suggested that miR-212-3p, miR-1247-3p, and miR-335-5p were significantly upregulated, while miR-3592, miR-382-3p, and miR-411-3p were significantly downregulated, in PAH rats compared with the controls (Figure 2(b)). These findings were consistent with the RNA-Seq data, potently validating their reliability. miR-335-5p was highly expressed in cardiomyocytes. Previous studies have demonstrated that miR-335-5p was involved in cardiac differentiation and left ventricular remodeling after myocardial infarction [12, 13]. Therefore, we chose miR-335-5p for further study.
The cell surface area was significantly increased in angiotensin II-induced cardiomyocyte hypertrophy. Compared to the control, miR-335-5p levels were significantly increased in angiotensin II-induced cardiomyocyte hypertrophy (Figure 3(e)). Pretreatment with miR-335-5p inhibitors could decrease the cell surface area induced by angiotensin II (Figures 3(a) and 3(b)). Similarly, miR-335-5p inhibition could also decrease the expression of ANP and β-MHC in in angiotensin II-induced cardiomyocyte hypertrophy (Figures 3(c) and 3(d)). Therefore, angiotensin II could facilitate miR-335-5p expression, and its pro-hypertrophy effects on cardiomyocytes were inhibited by pretreatment with miR-335-5p inhibitor.
We used three online databases, including Targetscan, miRanda, and PicTar, to predict the target gene of miR-335-5p. Combined with previous reported genes involved in cardiomyocyte hypertrophy, we focused on calumenin as a potential target. The luciferase assay was performed to evaluate if miR-335-5p overexpression affected the luciferase activity of different reporter vectors containing wild-type or mutant calumenin 3′UTR (Figures 4(a) and 4(b)). The result suggested that miR-335-5p overexpression could decrease luciferase activity of calumenin wide-type constructs, but not calumenin mutant constructs. Furthermore, the expression of calumenin was decreased in angiotensin II-induced cardiomyocyte hypertrophy, and pretreatment with miR-335-5p inhibitors could rescue calumenin downregulation in H9C2 cells (Figures 4(c), 4(d), and 4(e)). Calumenin significantly alleviated endoplasmic reticulum (ER) stress and Ca2+ overload and thus inhibited cellular apoptosis in rat cardiomyocytes [19, 20]. The apoptosis and intracellular Ca2+ accumulation of H9C2 cardiomyocytes were evaluated by TUNEL assay and fluo-3/AM determination (Figure 5(a)). The result showed that the apoptotic rate and the intensity of Ca2+ fluorescence were significantly increased after angiotensin II treatment. However, pretreatment with miR-335-5p inhibitors could decrease the increase of apoptosis and intracellular Ca2+ accumulation (Figures 5(b) and 5(c)).
To investigate the role of miR-335-5p on right ventricular dysfunction, miR-335-5p antagomir was injected via tail vein for 3 consecutive days prior to hypoxia/su5416 exposure. After 4 weeks, treatment with antagomiR-335-5p resulted in a significant reduction of miR-335-5p in the right ventricle (RV) (Figure 6(b)). Echocardiography revealed that RV dilatation and RV thickness were attenuated in antagomiR-335-5p-treated mice (Figures 6(e) and 6(f)). Moreover, antagomiR-335-5p administration could prevent PAH-induced increases in RV hypertrophy index (Figure 6(d)). Interestingly, RVSP and pulmonary vascular remodeling were unchanged between groups, indicating that in vivo knockdown of miR-335-5p had no effect on pulmonary histopathological changes (Figure 6(a)). Histologic analysis also revealed that antagomiR-335-5p administration attenuated the enlargement in cardiomyocyte cross-sectional areas after hypoxia exposure (Figures 7(a) and 7(b)). Myocardial hypertrophy marker genes ANP and β-MHC were also decreased after miR-335-5p inhibition (Figures 7(c) and 7(d)). As cardiac fibrosis was critical in the progression of cardiac remodeling, we also quantified the extent of fibrosis by Masson staining. RV collagen deposition was obviously reduced in PAH mice treated with antagomiR-335-5p when compared to those treated with antagomir NC (Figures 7(a) and 7(e)). Moreover, TUNEL assay suggested that the apoptotic rate was significantly increased in the RV of PAH mice and miR-335-5p inhibition could decrease the increase of apoptosis (Figures 7(a) and 7(f)). Consistent with the results of Masson staining, myocardial fibrosis markers including collagen I and collagen III were upregulated in the right ventricle of PAH mice, and antagomiR-335-5p treatment could obviously reduce the expression of collagen I and III (Figures 8(a), 8(e), and 8(f)). As calumenin is the target gene of miR-335-5p, we also investigated the changes of calumenin mRNA and protein levels. We found that calumenin was located in the cytoplasm of cardiomyocyte and calumenin expression was significantly decreased in PAH mice (Figures 8(a) and 8(b)). However, antagomiR-335-5p treatment could rescue the downregulation of calumenin induced by hypoxia/su5416 exposure (Figures 8(c) and 8(d)).
Although the initial insult involves pulmonary vascular, RV function is the main determinant of prognosis in PAH [2]. When exposed to increased afterload, the RV transfers from initial adaptive transformation to subsequent maladaptive transformation, leading to adverse morphological changes and functional decline, which is defined as RV remodeling [4, 8]. The process is complex, and it depends not only on the severity of PAH, but also on changes in myocardial metabolism, neurohormonal activation, rate of myocardial hypertrophy and fibrosis, as well as genetic and epigenetic factors. This multifactorial interplay likely explains the variability of RV function among PAH patients. Monocrotaline (MCT) rat model is a commonly used experimental model of RV failure [8]. Apart from clinical signs, including cachexia, dyspnea, ascites, and congestion, apparent RV enlargement, fibrosis, systolic dysfunction, and mitochondrial changes were also observed. Abnormal miRNA expression has been shown in this model. For example, miR-126 and miR-208 were found to be downregulated and miR-155 upregulated in MCT-induced PAH [8, 21]. Using miRNA sequencing, we identified 151 differentially expressed miRNAs in the RV of PAH rats. We focused on miR-335-5p as it was associated with cardiac fibrosis and hypertrophy. miR-335-5p participated in the pathogenesis of myocardial ischemia, and miR-335-5p overexpression alleviated myocardial ischemia reperfusion injury [22]. Kay et al. [12] found that miR-335-5p was involved in cardiac differentiation through inducing mesoderm and progenitor marker expression. Furthermore, miR-335-5p could also regulate angiotensin II-induced cardiac fibrosis and hypertrophy by targeting galectin-3 [23]. These studies suggested that miR-335-5p might act as a protective factor in cardiac fibrosis and hypertrophy. We found miR-335-5p was obviously upregulated in the right ventricle of PAH rats. miR-335-5p levels were also increased in an in vitro model of cardiac hypertrophy, and inhibition of miR-335-5p attenuated angiotensin II-induced cardiomyocyte hypertrophy. Similarly, Goncalves et al. [24] have showed that miR-335-5p is upregulated in post myocardial infarction myocardium and angiotensin II stimulated H9C2 cells. Our findings indicated that miR-335-5p might be a pro-hypertrophic factor in right heart failure. This discrepancy can be explained by the complex tissue- and cell-based specific roles of miR-335-5p in right and left heart failure. Right ventricle (RV) is different from left ventricle (LV) in terms of embryologic origin, metabolism, vascularity, and the response to pressure overload [25]. There are interesting differences in microRNA expression between the RV and LV, and this difference is maintained during afterload stress. In a murine model of pulmonary artery constriction, Reddy et al. [9] have reported four RV-specific microRNAs which are not increased in LV hypertrophy. Moreover, miR-208a expression has been shown to be maintained in LV failure, while its levels decreased during RV failure, suggesting a chamber-specific regulatory mechanism [21, 26]. Therefore, the differential role of miR-335-5p in RV failure is a novel finding. Antagomirs are widely used to antagonize endogenous miRNAs both in vivo and in vitro studies [27]. A long-lasting but reversible inhibition of miR-335-5p function was achieved after repeated intravenous systemic administration of antagomir-335-5p in a mouse model of PAH. Our results suggested that antagomir miR-335-5p effectively reduced PAH-induced right ventricular hypertrophy and fibrosis. We also found that miR-335-5p inhibition had no effect on right ventricular systolic pressure and pulmonary arteriole pathology, suggesting that the cardioprotective effect was independent of pulmonary vascular changes. RV failure was associated with myocardial apoptosis, and increasing myocardial apoptosis led to deteriorated cardiac function, therefore taking part in the pathological processes of RV remodeling [28, 29]. TUNEL staining indicated less cardiomyocyte apoptosis in antagomiR-335-5p group than in the NC group. Therefore, we supposed that miR-335-5p inhibition improved PAH-induced right ventricular remodeling through reducing cardiomyocyte apoptosis. Pharmacological modulation of miR-335-5p expression could be exploited for new therapeutic measures for RV remodeling in PAH. We also identified that calumenin (CALU) was a target of miR-335-5p. Calumenin is an endoplasmic reticulum resident Ca2+-binding protein and acts as a molecular chaperone to maintain homeostasis of calcium cycling in mammalian hearts [30]. It has been involved in many pathophysiologic processes including vascular calcification, thrombosis, and cell apoptosis. Calumenin interacts with endoplasmic reticulum Ca2+-ATPase in rat cardiac ER, and its overexpression in rat neonatal cells showed decreased ER Ca2+ uptake and decreased fractional Ca2+ release [31, 32]. In neonatal rat ventricular cardiomyocytes, calumenin overexpression ameliorated ER stress and inhibited ER stress induced apoptosis [19]. Calumenin can also relieve ER stress-initiated apoptosis in viral myocarditis [20]. Recently, Zhang et al. [33] identified that calumenin was downregulated in dilated cardiomyopathy. In this study, our results revealed that calumenin levels were decreased in the RV of PAH mice and miR-335-5p antagomir could rescue the downregulation of calumenin, indicating that miR-335-5p might regulate RV remodeling via calumenin. Consistent with calumenin changes, we also found that intracellular Ca2+ concentration and apoptosis were increased after angiotensin II treatment, and miR-335-5p inhibition decreased intracellular Ca2+ accumulation and apoptosis. Therefore, we supposed that RV pressure overload induced by PAH increased cardiomyocyte expression of miR-335-5p, subsequently caused calumenin downregulation, leading to Ca2+ overload and ER stress, and finally contributed to cardiomyocyte apoptosis and right ventricular remodeling (Figure 9). But the direct relationship between calumenin and Ca2+ accumulation and their functional roles in cardiomyocyte apoptosis were not established and required further confirmation. There are several limitations of this study. Firstly, H9C2 cells were used in this study, but it should be better to measure the effects in rat neonate cardiomyocytes. Secondly, fibroblast proliferation was also involved in right ventricular remodeling, but we did not measure the effects of miR-335-5p on RV fibroblast proliferation. Thirdly, we found that miR-335-5p downregulation caused less apoptosis and less calcium accumulation in angiotensin II induced cardiomyocyte hypertrophy. CALU was the target gene of miR-335-5p and had function in Ca2+ overload and cardiomyocyte apoptosis. But these experiments could not confirm the direct relationship between CALU/miR-335-5p/apoptosis. miR-335 downregulation could also lead to the reduction of apoptosis and Ca2+ accumulation through other factors. Therefore, further studies are still needed to confirm the relation of miR-335-5p/CALU and downstream phenotypes.
Our results revealed that miR-335-5p expression was elevated in the right ventricle of PAH. miR-335-5p inhibition exhibited protective effects on PAH-induced right ventricular remodeling through targeting calumenin, implying that miR-335-5p along with calumenin signaling might provide novel sight for a better understanding of RV remodeling. However, the role of miR-335-5p requires to be confirmed in future studies. | true | true | true |
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PMC9557318 | Dominik Walczak,Artur Sikorski,Daria Grzywacz,Andrzej Nowacki,Beata Liberek | Characteristic 1H NMR spectra of β- d -ribofuranosides and ribonucleosides: factors driving furanose ring conformations† † Electronic supplementary information (ESI) available. CCDC 2164567 . For ESI and crystallographic data in CIF or other electronic format see DOI: https://doi.org/10.1039/d2ra04274f | 13-10-2022 | A series of β- d -ribofuranosides and ribonucleosides fused with 2,3-O-isopropylidene ring was synthesized and studied in terms of their conformational preferences. Based on the 1H NMR spectra, DFT calculations, and X-ray analysis the E0-like and E4-like conformations adopted by these furanosides are identified. The 3E-like and 2E-like conformations are assigned to ribonucleosides without the 2,3-O-isopropylidene group. The studies are supported by analysis of the structural data of β- d -ribofuranosides and ribonucleosides deposited in the Cambridge Crystallographic Data Center (CCDC) database.† Finally, the factors influencing the conformational preferences of the furanose ring with the β- d -ribo configuration are indicated. These are the unfavorable ecliptic orientation of the 2-OH and 3-OH groups, the 1,3-pseudodiaxial interaction of the aglycone and terminal hydroxymethyl group and the endo-anomeric effect. It is also proved that the exo-anomeric effect acts in β- d -ribofuranosides. | Characteristic 1H NMR spectra of β- d -ribofuranosides and ribonucleosides: factors driving furanose ring conformations† † Electronic supplementary information (ESI) available. CCDC 2164567 . For ESI and crystallographic data in CIF or other electronic format see DOI: https://doi.org/10.1039/d2ra04274f
A series of β-d-ribofuranosides and ribonucleosides fused with 2,3-O-isopropylidene ring was synthesized and studied in terms of their conformational preferences. Based on the 1H NMR spectra, DFT calculations, and X-ray analysis the E0-like and E4-like conformations adopted by these furanosides are identified. The 3E-like and 2E-like conformations are assigned to ribonucleosides without the 2,3-O-isopropylidene group. The studies are supported by analysis of the structural data of β-d-ribofuranosides and ribonucleosides deposited in the Cambridge Crystallographic Data Center (CCDC) database.† Finally, the factors influencing the conformational preferences of the furanose ring with the β-d-ribo configuration are indicated. These are the unfavorable ecliptic orientation of the 2-OH and 3-OH groups, the 1,3-pseudodiaxial interaction of the aglycone and terminal hydroxymethyl group and the endo-anomeric effect. It is also proved that the exo-anomeric effect acts in β-d-ribofuranosides.
β-d-Ribofuranosides are commonly found in living organisms both in the form of N- and O-glycosides. Ribonucleosides, are perhaps the best known representatives of this group of compounds because they play essential functions in living organisms. In the form of 5′-phosphates (nucleotides) they are involved in intermediary metabolism, cell signaling, and the biosynthesis of macromolecules. Importantly, nucleotides serve as monomeric units of RNA, a macromolecule essential for all life forms on Earth. Thus, ribonucleosides are responsible for encoding, transmitting, and expressing genetic information in living organisms. Therefore, ribonucleosides and their derivatives are profoundly explored in medicine as anticancer, antibacterial, and antiviral agents. Molnupiravir, a ribonucleoside (Fig. 1A) with proven activity against a number of RNA viruses is currently tested against SARS-CoV-2. β-d-Ribofuranosides, which are not as common as their nitrogen analogues, are also found in natural compounds. Some aminoglycoside-aminocyclitol antibiotics, namely ribostamycin, butirosin B, neomycin, and paromomycin contain an O-β-d-ribofuranoside ring in their structure (Fig. 1B). It has been suggested that the presence of the ribofuranose ring in these antibiotics may improve the bacterial ribosome selectivity. Benzyl β-d-ribofuranoside was isolated from Euphorbia humifusa Willd and its ability to inhibit the LPS-induced NO and TNF-α production in RAW 264.7 cells was demonstrated. ADP-ribosylation, the post-translational modifications of proteins involved in many cellular processes, relies on the creation of an O-glycosidic bond between d-ribose and l-serine or l-threonine. Phosphorylated glycoconjugates of β-d-ribofuranoside were achieved synthetically. Simple β-d-ribofuranosides are often used as intermediate products in the syntheses of more sophisticated ribose derivatives. β-d-Ribofuranosides possessing phenolic aglycones were synthesized and found to exhibit the Src kinase inhibitory activity. Generally, glycosidation of d-ribose is of interest to organic chemists. A good understanding of the biological processes in which β-d-ribofuranosides and ribonucleosides participate requires an understanding of their conformational preferences. There are reports indicating that the interactions of nucleosides and their analogues with the target site depend on the furanose ring conformation. In order to require a specific conformation of the furanose ring in nucleosides, its structure is often modified at the 2′-position or bridged with an additional ring. The investigation of the conformationally restricted nucleosides led to the discovery of potent antiviral agents. It was also demonstrated that changes in the conformation of ribose have an impact on the nucleic acid conformation and function. From the chemical point of view, it has to be mentioned that the sugar ring conformation of nucleosides influences their reactivity. To avoid the torsion strains present in the flat furanose ring, this adopts one of ten possible envelope (E) or ten possible twist (T) conformations. The descriptors used at the conformation symbol indicate which atoms are placed below (subscript) or above (superscript) the plane formed by the remaining ring atoms (Fig. 2A). The pseudorotation phase angle P was introduced to precisely indicate the conformational state of the furanose ring. This parameter is defined to be zero for the 3T2 conformation. The transition from P = 0° to P = 360° exhausts all possible conformational states of the furanose ring, which is illustrated by the pseudorotational wheel (Fig. 2B). The conformation of the furanose ring is difficult to recognize because the five-membered ring is relatively labile. Despite such an inconvenience, much attention has been paid to the conformational analysis of the furanose ring. Respective studies have been carried out based on the X-ray crystallography, NMR data, quantum mechanical calculations, and other techniques. It does not change the fact that inferring the sugar ring conformation from the 1H NMR data, which is rather simple in the case of pyranosides, is still challenging in the case of furanosides. In our previous studies, it was demonstrated that a bicyclic structure of D-glucofuranurono-6,3-lactones and their glycosides causes the furanose ring to adopt specific conformations both in the crystal lattice and solution. In the case of β-D-glucofuranurono-6,3-lactones and their O-glycosides it was the 1T2-like conformation. In the case of the N-glycoside of α-D-glucofuranurono-6,3-lactone it was the 3T2/3E conformation. Thereby, it was proved that the characteristic 1H NMR spectra recorded for β-D-glucofuranurono-6,3-lactones and their O-glycosides are indicative of the 1T2-like conformation for all furanoses both with the β-D-gluco configuration as well as with the β-D-xylo and α-l-ido configurations. In turn, the characteristic 1H NMR spectrum recorded for N-(α-D-glucofuranurono-6,3-lactone) is indicative of the 3T2/3E conformation for all furanoses with the α-D-gluco, α-D-xylo, and β-L-ido configurations. In this paper we demonstrate how the 2,3-isopropylidene protecting group influences the conformational preferences of β-d-ribofuranosides and ribonucleosides. For the group of 2,3-O-isopropylidene-β-d-ribofuranosides and 2,3-O-isopropylideneribonucleosides, the 1H NMR spectra are presented. These are found to be very distinctive. Based on these spectra the specific conformations of the furanose ring are recognized. We opt for the specific conformation of the presented furanoses, instead of the usually postulated state of the conformational equilibrium, because the recorded 1H NMR signals are sharp. Furthermore, the recorded coupling constants indicative of a given conformation are not sensitive to the change in both the aglycone and the solvent. The conformations diagnosed based on the 1H NMR spectra are proved to be the most stable in the density functional theory (DFT) optimizations. Additionally, the search of β-d-ribofuranosides and ribonucleosides, with and without the 2,3-O-isopropylidene group, from the CCDC database is presented. Finally, analysis of the factors influencing the conformational preferences of the furanose ring with the β-D-ribo configuration is carried out.
The 1H and 13C NMR spectra were recorded on a Varian Mercury 400 (400.49/100.70 MHz) or Bruker AVANCE III 500 (500.13/125.76 MHz) instruments, using standard experimental conditions in CDCl3 or DMSO-d6 with internal Me4Si.
1H NMR (400 MHz, CDCl3): δ 4.97 (s, 1H, H1), 4.83 (d, 1H, J2,3 5.86 Hz, H3), 4.58 (d, 1H, J2,3 5.86 Hz, H2), 4.42 (t, 1H, J4,5 2.93 Hz, H4), 3.71 (dt, 1H, J4,5 = J5,OH 2.56 Hz, J5,5′ 12.45 Hz, H5), 3.61 (ddd, 1H, J4,5′ 3.30 Hz, J5′,OH 10.25 Hz, J5,5′ 12.45 Hz, H5′), 3.43 (s, 3H, OCH3), 3.18 (dd, 1H, J5,OH 10.62 Hz, J5′,OH 2.93 Hz, 5-OH), 1.48, 1.31 (2s, 2 × 3H, (CH3)2C); 13C NMR (100 MHz, CDCl3): δ 112.33 (CMe2), 110.22 (C1), 88.59 (C4), 86.04 (C2), 81.70 (C3), 64.22 (C5), 55.70 (OCH3), 26.57, 24.93 (2 × CH3).
1H NMR (400 MHz, CDCl3): δ 5.07 (s, 1H, H1), 4.84 (d, 1H, J2,3 5.86 Hz, H3), 4.59 (d, 1H, J2,3 6.23 Hz, H2), 4.41 (t, 1H, J4,5 2.57 Hz, J4,5′ 2.92 Hz, H4), 3.81 (dq, 1H, Jw 6.96 Hz, Jg 9.89 Hz, CH), 3.70 (dd, 1H, J4,5 1.83 Hz, J5,5′ 12.45 Hz, H5), 3.63 (m, 1H, J4,5′ 2.93 Hz, H5′), 3.57 (dq, 1H, Jw 6.96 Hz, Jg 9.89 Hz, CH′), 3.37 (bd, 1H, J5,OH 9.89 Hz, 5-OH), 1.48, 1.31 (2s, 2 × 3H, (CH3)2C), 1.23 (t, 3H, CH3); 13C NMR (100 MHz, CDCl3): δ 112.26 (CMe2), 108.75 (C1), 88.54 (C4), 86.25 (C2), 81.75 (C3), 64.24 (C5, CH2), 26.56, 24.90 (2 × CH3), 15.16 (CH3).
1H NMR (400 MHz, CDCl3): δ 5.06 (s, 1H, H1), 4.84 (d, 1H, J2,3 5.86 Hz, H3), 4.60 (d, 1H, J2,3 5.86 Hz, H-2), 4.41 (t, 1H, J4,5 2.93 Hz, J4,5′ 2.57 Hz, H4), 3.71 (dt, 1H, Jw 6.59/6.96 Hz, Jg 9.52/9.89 Hz, CH), 3.69 (dd, 1H, J4,5 2.93 Hz, J5,5′ 9.89 Hz, H5), 3.62 (bt, 1H, H5′), 3.44 (dt, 1H, Jw 6.59/6.96 Hz, Jg 9.52 Hz, CH′), 3.35 (bd, 1H, J5,OH 9.89 Hz, 5-OH), 1.61 (hex, 2H, Jw 6.96/7.32 Hz, CH2), 1.48, 1.31 (2s, 2 × 3H, (CH3)2C), 0.92 (t, 3H, Jw 7.32 Hz, CH3); 13C NMR (100 MHz, CDCl3): δ 112.26 (CMe2), 109.11 (C1), 88.53 (C4), 86.23 (C2), 81.79 (C3), 70.60 (CH2), 64.25 (C5), 26.56, 24.90 (2 × CH3), 22.90 (CH2), 10.66 (CH3).
1H NMR (400 MHz, CDCl3): δ 5.17 (s, 1H, H1), 4.85 (d, 1H, J2,3 5.86 Hz, H3), 4.56 (d, 1H, J2,3 5.86 Hz, H2), 4.39 (t, 1H, J4,5 2.20, J4,5′ 2.57 Hz, H4), 3.98 (q, 1H, Jw 6.22 Hz, CH), 3.70 (dd, 1H, J4,5 2.20 Hz, J5,5′ 12.08 Hz, H5), 3.61 (b, 1H, H5′), 3.51 (b, 1H, 5-OH), 1.48, 1.31 (2s, 2 × 3H, (CH3)2C), 1.23 (d, 3H, Jw 6.22 Hz, CH3), 1.19 (d, 3H, Jw 5.86 Hz, CH3′); 13C NMR (100 MHz, CDCl3): δ 112.18 (CMe2), 107.24 (C1), 88.47 (C4), 86.66 (C2), 81.87 (C3), 71.22 (CH), 64.19 (C5), 26.56, 24.87 (2 × CH3), 23.34, 21.86 (2 × CH3).
1H NMR (400 MHz, CDCl3): δ 5.05 (s, 1H, H1), 4.83 (d, 1H, J2,3 6.23 Hz, H3), 4.59 (d, 1H, J2,3 5.86 Hz, H2), 4.40 (t, 1H, J4,5 2.56, J4,5′ 2.93 Hz, H4), 3.75 (dt, 1H, Jw 6.59 Hz, Jg 9.52 Hz, CH), 3.69 (dd, 1H, J4,5 1.83 Hz, J5,5′ 12.45 Hz, H5), 3.61 (bt, 1H, H5′), 3.48 (dt, 1H, Jw 6.59/6.96 Hz, Jg 9.52 Hz, CH′), 3.36 (bd, 1H, J5,OH 9.89 Hz, 5-OH), 1.56 (qu, 2H, Jw 6.96 Hz, CH2), 1.47, 1.31 (2s, 2 × 3H, (CH3)2C), 1.36 (hex, 2H, Jw 7.32 Hz, CH2), 0.91 (t, 3H, Jw 7.32 Hz, CH3); 13C NMR (100 MHz, CDCl3): δ 112.25 (CMe2), 109.10 (C1), 88.51 (C4), 86.22 (C2), 81.79 (C3), 68.72 (CH2), 64.26 (C5), 31.67 (CH2), 26.56, 24.90 (2 × CH3), 19.40 (CH2), 13.94 (CH3).
1H NMR (400 MHz, CDCl3): δ 4.97 (s, 1H, H1), 4.66 (dd, 1H, J2,3 5.86 Hz, J3,4 0.73 Hz, H3), 4.59 (d, 1H, J2,3 5.86 Hz, H2), 4.35 (td, 1H, J4,5 7.69 Hz, J4,5′ 6.59 Hz, J3,4 1.10 Hz, H4), 4.11 (dd, 1H, J4,5 7.69 Hz, J5,5′ 11.35 Hz, H5), 4.09 (dd, 1H, J4,5′ 6.59 Hz, J5,5′ 11.35 Hz, H5′), 3.31 (s, 3H, OCH3), 2.08 (s, 3H, OAc), 1.48, 1.31 (2s, 2 × 3H, (CH3)2C); 13C NMR (100 MHz, CDCl3): δ 170.76 (C PBM data was replaced with SVG by xgml2pxml: <glyph-data id="z.dbd" format="PBM" resolution="300" x-size="8" y-size="10" xml:space="preserve"> 00000000 00000000 00000000 00000000 11111111 00000000 11111111 00000000 00000000 00000000 </glyph-data> <svg xmlns="http://www.w3.org/2000/svg" version="1.0" width="13.200000pt" height="16.000000pt" viewBox="0 0 13.200000 16.000000" preserveAspectRatio="xMidYMid meet"><metadata> Created by potrace 1.16, written by Peter Selinger 2001-2019 </metadata><g transform="translate(1.000000,15.000000) scale(0.017500,-0.017500)" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg> O), 112.79 (CMe2), 109.64 (C1), 85.43 (C2), 84.48 (C4), 82.12 (C3), 64.87 (C5), 55.14 (OCH3), 26.65, 25.22 (2 × CH3), 21.01 (CH3Ac).
1H NMR (400 MHz, CDCl3): δ 5.08 (s, 1H, H1), 4.67 (dd, 1H, J2,3 5.86 Hz, J3,4 0.74 Hz, H3), 4.61 (d, 1H, J2,3 5.86 Hz, H2), 4.34 (td, 1H, J4,5 7.33 Hz, J4,5′ 6.96 Hz, J3,4 0.73 Hz, H4), 4.13 (dd, 1H, J4,5 7.33 Hz, J5,5′ 11.35 Hz, H5), 4.10 (dd, 1H, J4,5′ 6.96 Hz, J5,5′ 11.35 Hz, H5′), 3.70 (dq, 1H, Jw 7.32 Hz, Jg 9.52 Hz CH), 3.44 (dq, 1H, Jw 6.96 Hz, Jg 9.89 Hz CH′), 2.08 (s, 3H, OAc), 1.48, 1.32 (2s, 2 × 3H, (CH3)2C), 1.16 (t, 3H, Jw 7.32/6.96 Hz, CH3); 13C NMR (100 MHz, CDCl3): δ 170.75 (CO), 112.74 (CMe2), 108.18 (C1), 85.58 (C2), 84.34 (C4), 82.19 (C3), 64.98 (C5), 63.36 (CH2), 26.66, 25.20 (2 × CH3), 21.03 (CH3Ac), 15.06 (CH3).
1H NMR (400 MHz, CDCl3): δ 5.07 (s, 1H, H1), 4.67 (dd, 1H, J2,3 5.86 Hz, J3,4 0.74 Hz, H3), 4.62 (d, 1H, J2,3 6.23 Hz, H2), 4.34 (td, 1H, J4,5 7.69 Hz, J4,5′ 6.59 Hz, J3,4 1.10 Hz, H4), 4.12 (dd, 1H, J4,5 7.32 Hz, J5,5′ 11.35 Hz, H5), 4.08 (dd, 1H, J4,5′ 6.59 Hz, J5,5′ 11.35 Hz, H5′), 3.61 (dt, 1H, Jw 6.96/6.59 Hz, Jg 9.52 Hz CH), 3.32 (dt, 1H, Jw 6.59 Hz, Jg 9.52 Hz CH′), 2.07 (s, 3H, OAc), 1.55 (hex, 2H, Jw 6.96, CH2), 1.48, 1.32 (2s, 2 × 3H, (CH3)2C), 0.89 (t, 3H, Jw 7.32 Hz, CH3); 13C NMR (100 MHz, CDCl3): δ 170.74 (CO), 112.73 (CMe2), 108.50 (C1), 85.54 (C2), 84.28 (C4), 82.21 (C3), 69.72 (CH2), 64.99 (C5), 26.64, 25.19 (2 × CH3), 22.81 (CH2), 21.02 (CH3Ac), 10.77 (CH3).
1H NMR (400 MHz, CDCl3): δ 5.19 (s, 1H, H1), 4.66 (dd, 1H, J2,3 5.86 or 6.23 Hz, J3,4 0.73 or 1.10 Hz, H3), 4.58 (d, 1H, J2,3 5.86 Hz, H2), 4.32 (td, 1H, J4,5 7.32 Hz, J3,4 0.74 Hz, H4), 4.11 (d, 2H, J4,5 6.96 Hz, H5), 3.88 (hep, 1H, Jw 6.22 Hz, CH), 2.07 (s, 3H, OAc), 1.48, 1.31 (2s, 2 × 3H, (CH3)2C), 1.14 (d, 3H, Jw 5.86 Hz, CH3), 1.13 (d, 3H, Jw 5.86 Hz, CH3′); 13C NMR (100 MHz, CDCl3): δ 170.76 (CO), 112.67 (CMe2), 106.35 (C1), 85.92 (C2), 84.22 (C4), 82.35 (C3), 69.44 (CH), 65.15 (C5), 26.66, 25.19 (2 × CH3), 23.35, 21.29 (2 × CH3), 21.03 (CH3Ac).
1H NMR (400 MHz, CDCl3): δ 5.06 (s, 1H, H1), 4.66 (dd, 1H, J2,3 5.86 Hz, J3,4 0.73 Hz, H3), 4.61 (d, 1H, J2,3 5.86 Hz, H2), 4.33 (td, 1H, J4,5 7.33 Hz, J4,5′ 6.59 Hz, J3,4 0.74 Hz, H4), 4.12 (dd, 1H, J4,5 7.69/7.32 Hz, J5,5′ 11.35/10.98 Hz, H5), 4.09 (dd, 1H, J4,5′ 6.96/6.59 Hz, J5,5′ 11.35/10.98 Hz, H5′), 3.65 (dt, 1H, Jw 6.96/6.59 Hz, Jg 9.89/9.52 Hz CH), 3.35 (dt, 1H, Jw 6.96/6.59 Hz, Jg 9.89/9.52 Hz, CH′), 2.07 (s, 3H, OAc), 1.50 (m, 2H, CH2), 1.47, 1.31 (2s, 2 × 3H, (CH3)2C), 1.34 (m, 1H, CH2), 0.90 (t, 3H, Jw 7.32 Hz, CH3); 13C NMR (100 MHz, CDCl3): δ 170.73 (CO), 112.72 (CMe2), 108.52 (C1), 85.54 (C2), 84.28 (C4), 82.21 (C3), 67.84 (CH2), 64.99 (C5), 31.64 (CH2), 26.64, 25.19 (2 × CH3), 21.01 (CH3Ac), 19.47 (CH2), 14.00 (CH3).
1H NMR (500 MHz, DMSO-d6): δ 11.30 (b, 1H, NH), 7.88 (d, 1H, J 8.24 Hz, HUr), 5.78 (d, J1,2 5.49 Hz, 1H, H1), 5.64 (d, 1H, J 7.93 Hz, HUr), 5.36 (d, 1H, J2,OH 5.80 Hz, 2OH), 5.09 (t, 1H, J5,OH, = J5′,OH, 5.19 Hz, 5OH), 5.08 (d, 1H, J3,OH 5.19 Hz, 3OH), 4.02 (q, 1H, J1,2 5.49 Hz, J2,3 5.19 Hz, J2,OH 5.49 Hz, H2), 3.96 (dt, 1H, J2,3–J3,OH 4.88/5.19 Hz, J3,4 3.97 Hz, H3), 3.84 (q, 1H, J3,4 3.66 Hz, J4,5 = J4,5′ 3.36 Hz, H4), 3.62 (ddd, 1H, J4,5 3.36/3.05 Hz, J5,OH 5.19 Hz, J5,5′ 12.21/11.90 Hz, H5), 3.54 (ddd, 1H, J4,5′ 3.36 Hz, J5′,OH 5.19/4.88 Hz, J5,5′ 12.21/11.90 Hz, H5′).
1H NMR (500 MHz, DMSO-d6): δ 8.35 (s, 1H, HAd), 8.14 (s, 1H, HAd), 7.34 (s, 2H, NH2), 5.88 (d, J1,2 6.41 Hz, 1H, H1), 5.43 (d, 1H, J2,OH 6.10 Hz, 2OH), 5.42 (dd, 1H, J5,OH, 4.28 Hz, J5′,OH, 7.02 Hz, 5OH), 5.17 (d, 1H, J3,OH 4.57 Hz, 3OH), 4.61 (q, 1H, J1,2 6.11 Hz, J2,OH 6.10 Hz, J2,3 5.19 Hz, H2), 4.14 (dt, 1H, J2,3 4.88 Hz, J3,OH 4.57 Hz, J3,4 3.05 Hz, H3), 3.96 (q, 1H, J3,4 = J4,5 = J4,5′ 3.36 Hz, H4), 3.67 (dt, 1H, J4,5 3.96 Hz, J5,OH 4.28 Hz, J5,5′ 11.91 Hz, H5), 3.55 (ddd, 1H, J4,5′ 3.66 Hz, J5′,OH 7.32 Hz, J5,5′ 11.91 Hz, H5′).
1H NMR (500 MHz, DMSO-d6): δ 7.84 (d, 1H, J 7.63 Hz, HCy), 7.16, 7.09 (2 × s, 2H, NH2), 5.76 (d, J1,2 3.97 Hz, 1H, H1), 5,70 (d, 1H, J 7.63 Hz, HCy), 5.27 (b, 1H, 2OH), 5.03 (b, 1H, 5OH), 4.97 (b, 1H, 3OH), 3.93 (b, 2H, H2, H3), 3.81 (q, 1H, J3,4 4.57 Hz, J4,5–J4,5′ 3.36 Hz, H4), 3.65 (dt, 1H, J4,5–J5,OH 3.56 Hz, J5,5′ 11.96 Hz, H5), 3.54 (dt, 1H, J4,5′–J5′,OH 3.56 Hz, J5,5′ 11.96 Hz, H5′).
1H NMR (500 MHz, DMSO-d6): δ 10.62 (b, 1H, NH), 7.93 (s, 1H, HGu), 6.45 (b, 2H, NH2), 5.69 (d, J1,2 5.80 Hz, 1H, H1), 5.38 (d, 1H, J2,OH 6.10 Hz, 2OH), 5.11 (d, 1H, J3,OH 4.58 Hz, 3OH), 5.03 (t, 1H, J5,OH = J5′,OH 5.49 Hz, 5OH), 4.39 (q, 1H, J1,2 5.80 Hz, J2,OH 6.11 Hz, J2,3 5.18 Hz, H2), 4.08 (dt, 1H, J2,3 4.89 Hz, J3,OH 4.58 Hz, J3,4 3.36 Hz, H3), 3.87 (q, 1H, J3,4 3.36 Hz, J4,5 4.28 Hz, J4,5′ 3.96 Hz, H4), 3.61 (ddd, 1H, J4,5 4.28 Hz, J5,OH 5.37 Hz, J5,5′ 11.90 Hz, H5), 3.52 (ddd, 1H, J4,5′ 3.96 Hz, J5′,OH 5.90 Hz, J5,5′ 11.90 Hz, H5′).
1H NMR (500 MHz, DMSO-d6): δ 11.37 (s, 1H, NH), 7.80 (d, 1H, Jw 8.24 Hz, CHUr), 5.84 (d, 1H, J1,2 2.75 Hz, H1), 5.64 (d, 1H, Jw 8.24 Hz, CHUr), 5.08 (t, 1H, J5,OH = J5′,OH 5.19 Hz, OH), 4.90 (dd, 1H, J1,2 2.75 Hz, J2,3 6.41 Hz, H2), 4.75 (dd, 1H, J2,3 6.41 Hz, J3,4 3.66 Hz, H3), 4.07 (dt, 1H, J4,5 = J4,5′ 4.27, J3,4 3.97 Hz, H4), 3.60 (dt, 1H, J4,5–J5,OH 4.58 Hz, J5,5′ 11.91 Hz, H5), 3.56 (dt, 1H, J4,5′–J5,OH 4.58 Hz, J5,5′ 11.91 Hz, H5′), 1.49, 1.30 (2s, 2 × 3H, (CH3)2C); 13C NMR (125 MHz, DMSO-d6): δ 163.65 (C2′), 150.80 (C4′), 142.38 (C6′), 113.44 (CMe2), 102.21 (C5′), 91.58 (C1), 86.98 (C4), 84.15 (C2), 80.95 (C3), 61.74 (C5), 27.52, 25.66 (2 × CH3).
1H NMR (500 MHz, DMSO-d6): δ 8.35 (s, 1H, HAd), 8.16 (s, 1H, HAd), 7.34 (bs, 2H, NH2), 6.13 (d, 1H, J1,2 3.05 Hz, H1), 5.35 (dd, 1H, J1,2 3.05 Hz, J2,3 6.11 Hz, H2), 5.24 (t, 1H, J5,OH 5.49 Hz, J5′,OH 5.19 Hz, OH), 4.97 (dd, 1H, J2,3 6.11 Hz, J3,4 2.44 Hz, H3), 4.22 (td, 1H, J4,5 = J4,5′ 4.58 Hz, J3,4 2.75 Hz, H4), 3.58 (dt, 1H, J4,5 4.88 Hz, J5,OH 5.49 Hz, J5,5′ 11.60 Hz, H5), 3.53 (dt, 1H, J4,5′ 4.88 Hz, J5,OH 5.19 Hz, J5,5′ 11.91 Hz, H5′), 1.55, 1.33 (2s, 2 × 3H, (CH3)2C).
1H NMR (500 MHz, DMSO-d6): δ 7.71 (d, 1H, Jw 7.32 Hz, HCyt), 7.24, 7.19 (2 × s, 2H, NH2), 5.77 (d, 1H, J1,2 2.44 Hz, H1), 5.71 (d, 1H, Jw 7.32 Hz HCyt), 4.99 (t, 1H, J5,OH–J5′,OH 5.49/5.19 Hz, 5-OH), 4.85 (dd, 1H, J1,2 2.44 Hz, J2,3 6.41 Hz, H2), 4.75 (dd, 1H, J2,3 6.41/6.10 Hz, J3,4 3.97/3.66 Hz, H3), 4.04 (q, 1H, J4,5 = J4,5′ 4.58 Hz, J3,4 3.97 Hz, H4), 3.61 (dt, 1H, J4,5 4.58 Hz, J5,OH 4.88 Hz, J5,5′ 11.60 Hz, H5), 3.54 (dt, 1H, J4,5′ 4.88 Hz, J5,OH 5.49/5.19 Hz, J5,5′ 11.60 Hz, H5′), 1.48, 1.29 (2s, 2 × 3H, (CH3)2C); 13C NMR (125 MHz, DMSO-d6): δ 166.35 (C2′), 155.40 (C4′), 143.49 (C6′), 113.18 (CMe2), 94.54 (C5′), 93.09 (C1), 87.15 (C4), 84.57 (C2), 81.14 (C3), 61.96 (C5), 27.57, 25.68 (2 × CH3).
1H NMR (500 MHz, DMSO-d6): δ 10.69 (s, 1H, NH), 7.92 (s, 1H, CHGu), 6.51 (s, 2H, NH2), 5.93 (d, 1H, J1,2 2.75 Hz, H1), 5.20 (dd, 1H, J1,2 2.75 Hz, J2,3 6.10 Hz, H2), 5,04 (t, 1H, J5,OH = J5′,OH 5.49 Hz, 5-OH), 4.97 (dd, 1H, J2,3 6.10 Hz, J3,4 3.05 Hz, H3), 4.12 (td, 1H, J4,5–J4,5′ 5.19/4.88 Hz, J3,4 3.36/3.05 Hz, H4), 3.55 (dt, 1H, J4,5 5.19 Hz, J5,OH 5.49 Hz, J5,5′ 11.60 Hz, H5), 3.48 (dt, 1H, J4,5′ 5.19 Hz, J5,OH 5.49 Hz, J5,5′ 11.60 Hz, H5′), 1.52, 1.32 (2s, 2 × 3H, (CH3)2C); 13C NMR (125 MHz, DMSO-d6): δ 157.17 (C6′), 154.16 (C2′), 151.20 (C4′), 136.32 (C8′), 117.22 (C5′), 113.52 (CMe2), 88.89 (C1), 87.10 (C4), 84.05 (C2), 81.65 (C3), 62.08 (C5), 27.54, 25.71 (2 × CH3).
Diffraction data were collected on an Oxford Diffraction Gemini R ULTRA Ruby CCD diffractometer with MoKα (λ = 0.71073 Å) radiation at T = 295(2) K. The lattice parameters were obtained by least-squares fit to the optimized setting angles of the reflections collected by means of CrysAlis CCD. Data were reduced using CrysAlis RED software and applying multi-scan absorption corrections. The structure was solved with direct methods that carried out refinements by full-matrix least-squares on F2 using the SHELXL-2017/1 program. All H-atoms bound to N/O/C-atoms were located on a difference Fourier map and refined freely (H-atoms from the methyl group were positioned geometrically and refined using a riding model, with C–H = 0.96 Å and Uiso(H) = 1.5Ueq(C)). All interactions were calculated using the PLATON program (ver. 181115). The following programs were used to prepare the molecular graphics: ORTEPII, PLUTO-78, and Mercury (ver. 2020.2.0). Full crystallographic details for title compound have been deposited.†
The Molden program was used for preparation of all the initial geometries for calculations which were done under default conditions with the aid of the Gaussian 09 program. The B3LYP functional (Becke's three-parameter hybrid exchange functional involving the gradient-corrected correlation functional of Lee, Yang and Parr) combined with the 6-311+G** basis set was used to perform unconstrained geometry optimization of all prepared geometries. No imaginary frequencies could be found for optimized structures as revealed form the Hessians analysis that was done at the same level of theory. Zero-point vibrational energies, molecular entropies as well as thermal energy contributions were obtained form the Hessian calculations, according to statistical thermodynamics formulae which were used to estimate the contribution of each rotamer in equilibrium. The population of rotamers was calculated using the following equation:
A series of 2,3-O-isopropylidene derivatives of β-d-ribofuranosides (1–10) and ribonucleosides (15–18) was synthesized (Fig. 3). These furanosides constitute fused, bicyclic structures that have a limited freedom of rotation, particularly with regard to adopting the 3T2 and 2T3 conformations, which demand a C2–C3 bond twist. Therefore, 2,3-O-isopropylidene derivatives of ribofuranosides provide a good model for studying the furanose ring conformations other than 3T2 and 2T3. Alkyl 2,3-O-isopropylidene-β-d-ribofuranosides (1–5) were synthesized by the reaction of d-ribose with the respective alcohol, carried out in acetone with the addition of SnCl2. Their acetylation provided derivatives 6–10. 2,3-O-Isopropylidenenucleosides (15–18) were synthesized by the reaction of the respective nucleoside (11–14) with 2,2-dimethoxypropane in anhydrous DMF with the addition of p-toluenesulfonic acid (for experimental details see ESI†).
The 1H NMR spectra of alkyl 2,3-O-isopropylidene-β-d-ribofuranosides (1–5) are identical in terms of the coupling constants of the furanose ring protons (Table 1). These are characterized by the zero coupling constants between the trans-oriented H1 and H2 (J1,2) as well as the trans-oriented H3 and H4 protons (J3,4). The third significant J2,3 coupling constant for all these furanosides is always 5.86 Hz or 6.22 Hz which, within the limits of measurement error, can be considered the same value. The identity of the key coupling constants is indicative of the same conformation of the furanose ring in 1–5. The zero coupling constant between vicinal protons is an extremely useful hint in the conformational analysis of a furanose ring based on the 1H NMR spectra, typically recorded by every organic chemist. According to the Karplus curve, this zero coupling constant indicates that the torsion angle between vicinal protons comes within the 80–100° range. Such a situation is possible solely for the trans-oriented vicinal furanose ring protons when these come as close as possible to each other in the process of the conformational changes. In the case of furanosides 1–5, both the H1 and H2 as well as the H3 and H4 pairs of protons are trans-oriented, and for both, the respective coupling constant is ∼0 Hz. Using a Dreiding model, one may see that the E0 conformation is the only one that ensures the maximum approximation of both the H1 and H2 as well as the H3 and H4 protons. Previously presented data on the torsion angles in the optimized THF ring, confirm this assumption. According to them the H1–C1–C2–H2 torsion angle for the β-d-ribo configuration in the E0 conformation is 101°, whereas the H3–C3–C4–H4 torsion angle is −101°. In the E0 conformation, the cis-oriented H2 and H3 protons for the β-d-ribo configuration form the H2–C2–C3–H3 torsion angle that is equal to 0°. The recorded J2,3 = 5.86 Hz or 6.22 Hz coupling constants are in agreement with this value.
To verify the conclusions based on the 1H NMR spectra of 1–5, methyl 2,3-O-isopropylidene-β-d-ribofuranoside (1), representing this group of furanosides, was optimized using DFT methods. Taking into account the rotations around the C1–O1, C4–C5, and C5–O5 bonds as well as two (exo and endo) settings of the 2,3-O-isopropylidene group, 54 (2 × 33) rotamers of 1 in the 1E, E1, 3E, and E3 initial conformations, respectively, were prepared. During the optimization, the number of rotamers was significantly reduced, as some of the original structures transformed into the same final geometry. Finally, seven (I–VII) relatively stable structures of 1 were obtained with a population ranging from 56.02% to 1.20%. The geometrical parameters, relative free Gibbs energies, and populations of I–VII in a group of found rotamers of 1 are listed in Table 2. These data indicate that methyl 2,3-O-isopropylidene-β-d-ribofuranoside (1) prefers a really narrow 4T0/E0/1T0 conformational range, which corresponds to all optimized structures I–VII. This conformational range can be limited to the 4T0/E0 conformation with P = ∼260°, which is adopted by six of the seven optimized structures (I–IV, VI, and VII). These structures comprise 97.9% of the population of all optimized structures. The results of the optimizations confirm our considerations pertaining to the H1–C1–C2–H2 and H3–C3–C4–H4 torsion angles in 1–5. The mean values of these angles are 104.43° and −104.27°, respectively (Table 2). Importantly, these are almost the same and close to the range of 80–100°, which determines the vicinal coupling constant of ∼0 Hz. Thus, all the presented studies (the 1H NMR spectra and DFT calculations) show that 2,3-O-isopropylidene-β-d-ribofuranoside (1) adopts the 4T0/E0 conformation. Based on the identity of the ring coupling constants (Table 1), it can be concluded that all alkyl 2,3-O-isopropylidene-β-d-ribofuranosides (1–5) adopt the same 4T0/E0 conformation. This means that the set of coupling constants presented in Table 1 is diagnostic of the 4T0/E0 conformation for furanosides not only with the β-d-ribo configuration but also with the β-d-allo, α-l-talo, and β-d-psico configurations. The all mentioned configurations have the same proton arrangement in the furanose ring. It has to be mentioned that the lack of a fused 2,3-isopropylidene group clearly changes the conformational preferences of methyl β-d-ribofuranoside. The complex calculations of this compound demonstrated that it adopts the 3T2 conformation from the northern part of the pseudorotational wheel.
The 1H NMR spectra of alkyl 5-O-acetyl-2,3-O-isopropylidene-β-d-ribofuranosides (6–10) are very distinctive and do not differ substantially from each other. Importantly, with regard to the coupling constants of the furanose ring protons (Table 1), they differ very little from the 1H NMR spectra of their precursors (1–5). Like the latter, they are characterized by the zero coupling constant between the H1 and H2 protons (J1,2) and the same J2,3 coupling constant (5.86 Hz or 6.22 Hz). However, in the case of β-d-ribofuranosides 6–10, a weak J3,4 = 0.73 Hz or 1.10 Hz coupling constant was recorded (again, both values can be considered as the same within the limits of measurement error). There was the zero coupling in the case of β-d-ribofuranosides 1–5, which, as demonstrated above, adopt the 4T0/E0 conformation. The recorded J3,4 coupling constant for 6–10 indicates a slight increase in the H3–C3–C4–H4 torsion angle compared to the situation in 1–5. Such an increase takes place when the E0 conformation approaches the 1T0 conformation. The transition from the 4T0/E0 to the E0/1T0 conformation increases the H3–C3–C4–H4 torsion angle and, at the same time, decreases the H1–C1–C2–H2 torsion angle. The latter angle, however, is still in the range of 80–100°, therefore, zero coupling constant between the H1 and H2 protons is recorded. Adoption of the E0/1T0 conformation does not substantially affect the J2,3 coupling constant, which is still 5.86 Hz or 6.22 Hz, indicating that the H3–C3–C4–H4 torsion angle is close to 0°.
In order to identify the conformation adopted by β-d-ribofuranosides 6–10, the structure of methyl 5-O-acetyl-2,3-O-isopropylidene-β-d-ribofuranoside (6) was optimized using DFT methods. Taking into account the rotations around the C1–O1, C4–C5, and C5–O5 bonds as well as two (exo and endo) settings of the 2,3-O-isopropylidene ring and two settings of the OAc group 108 (2 × 2 × 33) rotamers of 6 in the 0E, E0, 3E, and E3 conformations, respectively, were prepared. The only two favorable settings of the OAc group were previously demonstrated. During the optimization, the number of rotamers was significantly reduced. Thus, eleven (I–XI) relatively stable structures of 6 were obtained with a population ranging from 33.71% to 1.16%. The geometrical parameters, relative free Gibbs energies, and populations of I–XI in a group of found rotamers of 6 are listed in Table 3. These data indicate that methyl 5-O-acetyl-2,3-O-isopropylidene-β-d-ribofuranoside (6) prefers the E0 conformation (P = 269.5–271.9°) with a slight deviation towards the 1T0 conformation (P = 274.5–282.3°). The E0 conformation represents 55.70% of the population of all optimized structures, whereas the E0/1T0 conformation represents 44.30%. Thus, it can be stated that methyl 5-O-acetyl-2,3-O-isopropylidene-β-d-ribofuranoside (6) adopts the E0/1T0 conformation, which is really close to the 4T0/E0 conformation adopted by 2,3-O-isopropylidene-β-d-ribofuranoside (1). While the 4T0/E0 conformation is characterized by the zero coupling constants between both the H1 and H2 as well as H3 and H4 protons, the E0/1T0 conformation shows no coupling between the H1 and H2 protons, but a slight coupling (0.73 or 1.10 Hz) between the H3 and H4 is recorded in this conformation. This tenuous difference in the values of the coupling constants is reflected in the calculated torsion angles (Table 3). The H3–C3–C4–H4 torsion angles are slightly, but clearly, greater than the H1–C1–C2–H2 torsion angles. The mean value for the former is 105.75°, whereas it is 100.00° for the latter. Thus, the transition from the 4T0/E0 conformation to the E0/1T0 conformation slightly increases the H3–C3–C4–H4 torsion angle and decreases the H1–C1–C2–H2 torsion angle. The same coupling constants recorded for all alkyl 5-O-acetyl-2,3-O-isopropylidene-β-d-ribofuranosides (6–10) allow for the assumption that all of them adopt the same E0/1T0 conformation. This means that the set of coupling constants recorded for 6–10 (Table 1) is diagnostic of the E0/1T0 conformation for furanosides not only with the β-d-ribo configuration, but also with the β-d-allo, α-l-talo, and β-d-psico configurations.
2,3-O-Isopropylideneribonucleosides (15–18) have the same β-d-ribo configuration as 2,3-O-isopropylidene-β-d-furanosides 1–10 discussed above; however, they belong to the class of the N-furanosides. Studies performed on 15–18 well illustrate how a change in the nature of the aglycone affects the conformational preferences of the furanose ring. Because 2,3-O-isopropylideneuridine (15) was obtained in a crystalline form, its geometry is analyzed first.
The synthesis and crystal structure of 15 were previously described by Satyanarayana et al. in 1976 (CSD REFCODE: ZZZAPA) and Katti et al. in 1981 (CSD REFCODE: ZZZAPA10). However, in the first case, 3D coordinates were not available, whereas in the second case, the position of the H-atom from the hydroxyl group was not defined. For the reasons above, we redetermined the crystal structure of 15. The diffraction data of 2,3-O-isopropylideneuridine (15) are listed in Table 4. The structure of 15 showing the atom numbering scheme and the selected torsion angles are presented in Fig. 4A and B, respectively. X-Ray analysis of 15 reveals that it has a bicyclic structure consisting of fused furanoside (O4/C1/C2/C3/C4) and five-membered 2,3-O-isopropylidene (O2/C2/C3/O3/C10) rings (Fig. 4A). The furanose ring in nucleoside 15 adopts a conformation close to the 4T3 with ring-puckering parametersθ = 0.212 Å and ϕ = 124.4(7)°, pseudorotation parametersP = 217.0(3)° and τm = 22.8(2)° for the C2–C3 reference bond, and delta parameterΔ = 434.0°. The five-membered isopropylidene ring adopts a conformation close to the 3E form with ring-puckering parametersθ = 0.300(2) Å and ϕ = 288.4(5)°, pseudorotation parametersP = 19.9(2)° and τm = 33.3(1)° for the C3–O3 reference bond, and delta parameterΔ = 39.9°. In the crystal of 15, molecules are held together by the N2–H2⋯O7, O5–H5⋯O7 and C1–H1⋯O6 intermolecular interactions to produce a 3D framework (Table 5 and Fig. S1†). The torsion angles of nucleoside 15 presented in Fig. 4B well illustrate the 4T3 conformation of the furanose ring. In this conformation, the O4, C1, and C2 atoms lay in one plane, whereas the C4 and C3 carbon atoms are located above and below this plane, respectively. Therefore, the torsion angles in which the O4, C1, and C2 atoms are involved are relatively small and amount to 7.47° (C4–O4–C1–C2) and 7.04° (O4–C1–C2–C3), respectively. The remaining torsion angles are larger. These angles formed by two consecutive atoms of those lying in one plane amount to −18.05° (C1–C2–C3–C4) and −19.01° (C3–C4–O4–C1), respectively. The C2–C3–C4–O4 torsion angle is the largest (22.63°) because this is the C3–C4 bond twisted in the 4T3 conformation.
Regarding the furanose ring coupling constants, the 1H NMR spectra of 2,3-O-isopropylidenenucleosides (15–18) are almost the same (Table 6), which indicates that conformations adopted by these compounds lay within the same range of the pseudorotational wheel. The same as in the case of 2,3-O-isopropylidenefuranosides discussed above, the J2,3 coupling constant for 15–18 is relatively large (6.10 Hz or 6.41 Hz). According to the Karplus curve, these values of coupling constant mean that the cis-oriented H2 and H3 protons form the torsion angle of about 10°. Such an angle is expected for 2,3-O-isopropylidene furanoses because, in their cases, the twist of the C2–C3 bond is stymied. According to the Dreiding model of a furanose ring and the previously reported data on the torsion angles in the optimized THF ring, one may see that the trans-oriented vicinal protons can maximally approach each other to form the H–C–C–H torsion angle close to 80–90° (3JH,H ∼0 Hz) or can maximally move away from each other to form the H–C–C–H torsion angle close to 170° (3JH,H ∼8 Hz). These are the extreme arrangements of trans-oriented protons in a furanose ring, and these take place when the trans-oriented protons are attached to the carbon atoms whose bond is twisted. The coupling constants of the trans-oriented H1 and H2 protons in 15–18 are in the narrow range of 2.44–3.05 Hz (2.75 Hz on average). The coupling constants of the trans-oriented H3 and H4 protons are slightly larger and fall within a slightly wider range of 2.44–3.97 Hz (3.36 Hz on average). This may indicate that the H4 proton has more freedom of rotation than the H1 proton. According to the Karplus curve as well as Serianni and Barker reports, the J1,2 and J3,4 coupling constants recorded for 15–18 are indicative of the respective torsion angles being included in the range of about 120–130°. Simultaneously, the H1–C1–C2–H2 torsion angle has to be slightly smaller than the H3–C3–C4–H4 torsion angle due to the smaller J1,2 coupling constant compared to the J3,4 coupling constant. The 4T3 conformation found in the crystal lattice of 15 with the H1–C1–C2–H2 and H3–C3–C4–H4 torsion angles of 122.27° and −100.59°, respectively, does not meet these requirements. It seems that the best fit is met in the E4-like conformation. This conformation requires the H1 and H2 protons to be ecliptically oriented with the H1–C1–C2–H2 torsion angle of about 120° and allows the H3–C3–C4–H4 torsion angle to be greater than 120°. Such a situation is well illustrated in the crystal structure of 2.3-O-isopropylideneuracil (JAWCEP, Table 8) where the H1–C1–C2–H2 and H3–C3–C4–H4 torsion angles are 113.35° and 129.44°, respectively. Table 6 also presents the coupling constants recorded for the basic nucleosides (11–14). These show that the furanose ring protons coupling constants of adenosine (12) and guanosine (14) are almost the same, indicating the same conformation. Importantly, the data recorded by us are in accordance with the literature NMR data, both recorded in DMSO and in D2O (Table 6). The conformation of the structurally non-restricted nucleosides is usually interpreted in terms of a two-state equilibrium between the North and the South conformations. Thus, Plavec et al., who recorded very similar coupling constants for 12 and 14 in D2O, stated that the equilibrium populations of the North form in 12 and 14 is 18% and 21%, respectively. We would like to propose the statement that the recorded coupling constants for 12 and 14 are indicative of the specific conformation from the southern part of the pseudorotational itinerary (Fig. 2B). According to the Karplus curve as well as to the Serianni and Barker reports, for the trans-oriented H1 and H2 protons in 12 and 14, the J1,2 coupling constant in the range of 6–6.45 Hz indicates the H1–C1–C2–H2 torsion angle of about 150°. In turn, for the trans-oriented H3 and H4 protons, the J3,4 coupling constant in the range of 3.1–3.58 Hz indicates the H3–C3–C4–H4 torsion angle in the range of 110–120°. The J2,3 coupling constant in the range of 4.83–5.2 Hz for the cis-oriented H2 and H3 protons indicates that the H2–C2–C3–H3 torsion angle reaches a value of 40°. Based on these estimated values of 150°, 40°, and 120° for the H1–C1–C2–H2, H2–C2–C3–H3, and H3–C3–C4–H4 torsion angles, respectively, one may state that adenosine (12) and guanosine (14) adopt the 2E-like conformation (the southern region). Our calculated for the THF ring torsion angles as well as the torsion angles found in the CCDC database also confirm that the 2E-like conformation fits well with these estimated angles. The ring proton coupling constants recorded for uridine (11, Table 6) do not differ much from those recorded for adenosine (12) and guanosine (14). Therefore, we assume that 11, like 12 and 14, adopts a conformation close to the 2E. However, the situation of cytosine (13) is different. The values of the J1,2 and J3,4 coupling constants recorded for 13 are inverted compared to the analogous coupling constants recorded for 11, 12, and 14, whereas the J2,3 coupling constant remained the same. Plavec et al. concluded that the equilibrium population of the North form in 13 is 71%. In our opinion, the estimated values of the torsion angles of about 120°, 40°, and 150° for the H1–C1–C2–H2, H2–C2–C3–H3, and H3–C3–C4–H4 torsion angles, respectively, indicate that cytosine (13) adopts the 3E-like conformation (the north region). This is confirmed by the values of the respective torsion angles that we calculated for the THF ring and found in the CCDC database (Table 8). As one may see, both the 2E the 3E conformations are typical for the crystal structure of the conformationally non-restricted nucleosides (Table 8).
To improve presented discussion, the ConQuest search of the Cambridge Structural Database (CSD, Version 5.43, November 2021 update) for the furanose ring with the β-d-ribo-like configuration was done.Table 7 presents geometric parameters of β-d-ribofuranosides whose conformational freedom is limited due to the fused 2,3-O-isopropylidene ring and β-d-ribofuranosides without such a restriction. Table 8 presents geometric parameters of ribonucleosides whose conformational freedom is limited due to the fused 2,3-O-ketal (isopropylidene or other) and ribonucleosides without such a restriction. Analysis of the data in Table 7 shows that β-d-ribofuranosides without 2,3-O-isopropylidene fused ring in a crystal structure mainly adopt the E2-like conformation from the northern part of the pseudorotation wheel (red dots in Fig. 5A). The E2 conformation of β-d-ribofuranosides is characterized by a relatively small torsion angle between the H1 and H2 protons, which is in the range of 74.79°–89.14° (82.06° on average). Such a torsion angle is the minimum angle that the trans-oriented protons can achieve in the furanose ring. In turn, the trans-oriented H3 and H4 protons in the E2 conformation of β-d-ribofuranosides move away from each other so that the H3–C3–C4–H4 torsion angle is in the range of 146.84–156.03°. The data in Table 7 clearly show how the H3–C3–C4–H4 torsion angle increases as the conformation changes from the 1T2 (140.27°) through the E2 (150.80° on average) to the 3T2 (169.45°). The last value of the torsion angle is almost the maximum that the trans-oriented protons in the furanose ring can achieve. The H2–C2–C3–H3 torsion angle in the E2 conformation of β-d-ribofuranosides is in the range of 33.05–44.00° (38.96° on average), which is typical of the cis-oriented protons, at least one of which is bound to the carbon laying out of the plane formed by the remaining furanose ring atoms. The maximum torsion angle between the cis-oriented protons is formed when both these protons are attached to the carbons involved in the twist of the furanose ring. This is the case of the H2 and H3 protons of β-d-ribofuranosides in the 3T2 or 2T3 conformations. Therefore, the 3T2 conformation is characterized by the highest values of the H2–C2–C3–H3 torsion angle (45.59° and 45.88°) formed between the cis-oriented H2 and H3 protons. The introduction of 2,3-O-isopropylidene to β-d-ribofuranosides definitively changes their conformational preferences (Table 7). Every 2,3-O-isopropylidene-β-d-ribofuranoside found in the CCDC database adopts the E0-like conformation (orange dots in Fig. 5A). The reasons for this behavior of the furanose ring are discussed in the next paragraph. Typically for the E0 conformation, the values of the H1–C1–C2–H2 torsion angle in the range of 91.58–104.50° (on average 96.99°) and the H3–C3–C4–H4 torsion angle in the range of 89.93–109.33° (on average 101.89°) are similar. The shift towards the 4T0 conformation slightly increases the H1–C1–C2–H2 torsion angle (110.15°) and slightly decreases the H3–C3–C4–H4 torsion angle (97.79°). The shift towards the 1T0 conformation does the opposite and slightly decreases the H1–C1–C2–H2 torsion angle (90.58° on average) and slightly increases the H3–C3–C4–H4 torsion angle (106.50° on average). Also, typically for the E0 conformation, the H2 and H3 protons are eclipsed, which is confirmed by the H2–C2–C3–H3 torsion angle in the range of 0.11–8.66° (4.39° on average). Both the shifts towards the 4T0 and the 1T0 conformations increase this torsion angle to the value of 11.02° and to the averaged value of 9.40°, respectively. All these findings concerning the E0-like conformation of 2,3-O-isopropylidene-β-d-ribofuranosides found in the CCDC database clearly confirm our findings concerning 1–10 based on the 1H NMR spectra and DFT calculations. The CCDC database search shows that the conformational preferences of ribonucleosides (Table 8) are different from that of β-d-ribofuranosides (Table 7). As long as the conformational changes of the furanose ring are not restricted by the 2,3-O-isopropylidene or other 2,3-O-ketal rings, the nucleosides in the crystal adopt the 3E-like or 2E-like conformation, from the North or South regions, respectively, of the pseudorotational itinerary (green dots in Fig. 5A). This finding is fully in agreement with Altona's reports, who indicates these two regions to be the most stable for nucleosides. In the 3E-like conformation, the trans-oriented H1 and H2 protons of the ribonucleosides approach each other by an average torsion angle of 95.53°. In turn, the trans-oriented H3 and H4 protons move away from each other by an average torsion angle of 161.75°. The mean value of the H2–C2–C3–H3 torsion angle in this conformation is 38.84°. This is typical of cis-oriented protons, one of which (H3) is bound to the carbon atom (C3) laying outside the plane formed by the other ring atoms. In the case of the 2E-like conformation, the trans-oriented H1 and H2 protons move away from each other by an average torsion angle of 160.67°. In turn, the trans-oriented H3 and H4 protons approach each other by an average torsion angle of 100.52°. The mean value of the H2–C2–C3–H3 torsion angle in this conformation is 38.71°, which again confirms that one of the protons involved in this torsion angle (H2) is bound to the carbon atom (C2) laying outside of the plane formed by the other ring atoms. The introduction of a 2,3-O-ketal (isopropylidene or other) into a nucleoside hinders their adoption of both the 3E and 2E conformations. However, ribonucleosides with the 2,3-O-ketal fused ring (blue dots for 2,3-O-isopropylidene derivatives, purple dots for other 2,3-O-ketals, and a black dot for 15 in Fig. 5A) clearly behave differently than β-d-ribofuranosides in an analogous situation (orange dots in Fig. 5A). The latter, regardless of their structure, always adopt the E0-like conformation, whereas the former do not have any privileged conformation and can be found throughout the entire range of the pseudorotation wheel.
Analyzing the presented results, we found that the first important factor influencing conformational preferences of the furanose ring are unfavourable ecliptic interactions between the substituents of the ring atoms lying in one plane. In the case of the ribofuranose ring, among possible ecliptic interactions, those between the 2-OH and 3-OH groups seem to be particularly unfavorable. In addition to typical torsion strains, these should generate repulsion of dipoles of polar bonds formed between respective carbon and oxygen atoms. From this point of view, the 3T2 and 2T3 conformations of the ribofuranose ring are the most favorable because these conformations allow the dipoles of the polar bonds to be as far apart as possible (Fig. 6A). In turn, the 0E and E0 conformations of the ribofuranose ring, in which the 2-OH and 3-OH groups are ecliptically oriented, are the most unfavorable. These considerations are fully in agreement with the Altona and Sundaralingam reports. It should be added that the best stabilization of the 3T2 and 2T3 conformations is often explained by the gauche effect. This effect is not taken into account herein because we are not convinced of its stabilizing action. The second factor influencing the conformational preferences of the furanose ring is an endo-anomeric effect, well known from the pyranose ring. The generalized endo-anomeric effect is defined as the preference of the gauche orientation (Fig. 6B) over the antiperiplanar orientation (Fig. 6C) in the C5–O5–C1–X (pyranose) or C4–O4–C1–X (furanose) atoms arrangement, where the X atom comes from an aglycone. This effect increases with increasing electronegativity of the X atom in line with the series: carbon < nitrogen < oxygen < halogen. In the case of a pyranose ring, the anomeric effect implies a preference for the axial orientation of the aglycone. One of the theories explaining the anomeric effect, known as the hyperconjugation model, assumes that the stabilization of the gauche (axial) conformer is attributed to the delocalization of the antiperiplanar lone-pair of electrons of the ring oxygen atom to the antibonding orbital of the C1–X bond. In a furanose ring, this delocalization is possible only in a relatively narrow range of conformations, other for α-furanoses and other for β-furanoses. Although, there are some reports that the magnitude of the endo-anomeric effect in furanoses is larger by 2.7 kJ mol−1 (on average) in comparison to analogous pyranoses, it seems to us that the tendency is opposite. This is because the delocalization necessary to speak of the anomeric effect in a furanose ring has to be limited compared to the analogous delocalization in the pyranose ring. This limitation results from the fact that the aglycone cannot be fully axially oriented in a furanose ring. In the furanose ring, the bonds can be at most pseudoaxial or pseudoequatorial or have an intermediate character. As shown by the data presented in Tables 7 and 8, the lowest value that the C4–O4–C1–X torsion angle can achieve is ∼80°. This means that in furanoses, the electronically advantageous gauche conformation of the C4–O4–C1–X segment cannot be fully achieved. It does not change the fact that the anomeric effect, although not as strong as in pyranoses, also occurs in furanoses. The most effective anomeric effect in the case of β-d-furanosides is expected in the 1T2/1E/1T0/E0 conformational range (Fig. 5B), where the aglycone is oriented more or less pseudoaxially and should be the strongest in the 1T0-like conformation. For the same reasons, the most effective anomeric effect in the case of α-d-furanosides is expected in the 2T1/E1/0T1/0E conformational range and should be the strongest in the 0T1 conformation. Consequently, any anomeric effect is expected in the 1T2/1E/1T0/E0 conformational range in the case of α-d-furanosides and in the 2T1/E1/0T1/0E conformational range in the case of β-d-furanosides. The third factor that influences the conformational preferences of furanoses with the β-d-ribo configuration is the unfavorable 1,3-pseudodiaxial interactions between the aglycone and terminal hydroxymethyl group. These are expected to be the strongest in the 4E/4T0/E0/1T0/1E conformational range (Fig. 5B) and the weakest in the E4/0T4/0E/0T1/E1 conformational range. In the former range of conformations, the substituents of the C1 (aglycone) and C4 (hydroxymethyl group) carbon atoms are closest to each other. In the latter range of conformations, these substituents are furthest to each other. As one may see, the region of action of these unfavorable 1,3-pseudodiaxial interactions overlaps with one of the regions where the unfavorable ecliptic interactions between the 2-OH and 3-OH groups take place (West side, Fig. 5B). In turn, the regions of action of both these unfavorable interactions overlap to some extent with the region of action of the anomeric effect. The analysis of the data presented herein fully confirms the influence of the above mentioned factors on the conformational preferences of furanosides with the β-d-ribo configuration. As shown by our search of the CCDC database, until the conformational changes of a furanose ring are not restricted by a fused 2,3-O-isopropylidene ring, β-d-ribofuranosides adopt the E2-like conformation, whereas ribonucleosides adopt the 3E-like or 2E-like conformations (Tables 7 and 8 and Fig. 5A). These three conformational spaces are placed in the North or South regions of the pseudorotation wheel where the above indicated unfavorable interactions are minimized (Fig. 5B). However, at least the 3E-like and 2E-like conformations (adopted by ribonucleosides) are not located in the region of action of the anomeric effect. It appears that in the case of ribonucleosides, the anomeric effect is weaker than the cumulative effects of the unfavorable ecliptic arrangement of the 2-OH and 3-OH groups and the 1,3-diaxial interactions of the nucleobase and the hydroxymethyl group. As a result, the 3E-like and 2E-like conformations become the most stable for ribonucleosides. In turn, the anomeric effect influences the conformational preferences of β-d-ribofuranosides (red dots). Their preferred E2-like conformation, compared to the 3E and 2E conformations of nucleosides (green dots), is clearly shifted towards the region where the anomeric effect is active. This is well illustrated by the O1–C1–O4–C4 torsion angle. The anomeric effect acts more efficiently the closer the angle reaches the value of 60° (gauche orientation). As shown by the crystal data of β-d-ribofuranosides without the 2,3-O-isopropylidene fused ring (Table 7), the transition from the 3T2 conformation, through the E2 conformation, to the 1T2 conformation decreases the O1–C1–O4–C4 torsion angle from −108.51°, via −91.98°, to −82.35°. In the case of a furanose ring, the latter value of the O1–C1–O4–C4 torsion angle is optimal for the action of the anomeric effect. Thus, the anomeric effect, stronger in the case of O-furanosides than in the case of N-furanosides, causes β-d-ribofuranosides to adopt the E2 conformation in a crystal lattice. The action of the anomeric effect is clearly observed in the case of 2,3-O-isopropylidene-β-d-ribofuranosides. The fused 2,3-O-isopropylidene ring hinders the adoption of the 3T2 and 2T3 conformations and favors the conformation in which the ring oxygen atom is placed out of the plane formed by the remaining atoms. However, all 2,3-O-isopropylidene-β-d-ribofuranosides, those that we synthesized (1–10) and those found in the CCDC database (Table 7), adopt solely the E0-like conformation (orange dots, Fig. 5A) and not the 0E-like conformation. The probable reason for this preference is that the E0-like conformation allows the anomeric effect to take place (Fig. 5B). As shown by the crystallographic data (Table 7), in the E0 conformation, the O1–C1–O4–C4 torsion angle is in the range of 77.65–89.65° (85.26° on average), and in the 1T0 conformation, this torsion angle is in the range of 79.18–85.48° (83.00° on average). In the optimized structures, the O1–C1–O4–C4 torsion angle is in the range of 87.38–100.01° (90.78° on average) in the case of 1 (Table 2) and in the range of 85.65–87.12° (86.38° on average) in the case of 6 (Table 3). Such values of the torsion angles mean that the aglycones in these furanosides are oriented pseudoaxially and that the anomeric effect acts optimally in the furanose ring. Our calculations also show that this anomeric effect can act better in the E0/1T0 conformation than in the E0/4T0 conformation because the value of 86.38° is closer to the gauche orientation than the value of 90.78°. This clear preference for the E0-like conformation may indicate that in the case of O-furanosides, the favorable anomeric effect is stronger than the unfavorable 1,3 pseudodiaxial interactions between the aglycone and terminal group. Regarding the conformational preferences, 2,3-O-ketal derivatives of nucleosides (blue and purple dots, Fig. 5A) behave completely different than their O-furanoside analogues. The 2,3-O-ketal protection group makes it difficult for nucleosides to adopt the 3E or 2E conformations that are most favorable for them. However, 2,3-O-ketalribonucleosides do not adopt the E0-like conformation, characteristic of the analogous β-d-ribofuranosides (orange dots, Fig. 5A). This means that the anomeric effect, in the case of ribonucleosides, is weaker than in the case of β-d-ribofuranosides and it cannot outweigh the unfavorable 1,3-pseudodiaxial interactions of the nucleobase and the terminal hydroxymethyl group. It is also possible that the latter interactions are stronger in the case of ribonucleosides than in the case of β-d-ribofuranosides. As a result, 2,3-O-ketal derivatives of ribonucleosides adopt various conformations in the crystal, which proves that none of them is especially privileged. It is important to add that the three factors influencing the conformation of the furanose ring listed herein were also noticed in molecular dynamics studies. Apart from the endo-anomeric effect, an exo-anomeric effect can also act in the sugar ring. This is caused by the exocyclic oxygen atom from the aglycone and means that the gauche orientation is preferred over the antiperiplanar orientation in the O5–C1–O1–C7 (pyranose) or O4–C1–O1–C6 (furanose) atoms arrangement (Fig. 6D). The exo-anomeric effect does not directly influence the pyranose or the furanose ring conformation. It affects the arrangement of the aglycone carbon atom linked to the glycosidic oxygen atom (C7 in pyranose or C6 in furanose). The action of the exo-anomeric effect is clearly visible in the β-d-ribofuranosides presented herein, both without and with the 2,3-O-isopropylidene fused ring. In the case of β-d-ribofuranosides without the 2,3-O-isopropylidene found in the CCDC database, the O4–C1–O1–C6 torsion angle (Table 7) is in the range of 44.82–85.27° (64.75° on average). In the case of β-d-ribo and β-d-allofuranosides with the 2,3-O-isopropylidene, this torsion angle is in the range of 61.82–76.65° (68.72° on average). In the case of β-d-ribofuranosides that we optimized, the O4–C1–O1–C6 torsion angle is in the range of 66.53–71.75° (69.65° on average) for 1 (Table 2) and in the range of 65.42–69.08° (67.80° on average) for 6 (Table 3). All these data clearly indicate that the O1–C1–O4–C4 atoms segment adopt the gauche conformation, which means that the exo-anomeric effect acts very well in the presented β-d-ribofuranosides.
Although the furanose ring is inherently labile, there are situations in which a given conformation of this ring is sufficiently stable to recognize it in the 1H NMR spectrum. These are the E0-like conformation adopted by 2,3-O-isopropylidene-β-d-ribofuranosides (1–10), 3E-like and 2E-like conformations adopted by the ribonucleosides (11–14), and the E4-like conformation adopted by 2,3-O-isopropylideneribonucleosides (15–18). The specific 1H NMR data for these four conformations of the furanose ring with the β-d-ribo configuration are presented. Importantly, this data, with regard to the ring proton coupling constants in the indicated conformations, also applies to furanoses with the β-d-allo, β-d-psico and α-l-talo configurations. The most characteristic feature of the presented spectra is the zero coupling between the trans-oriented vicinal protons. This takes place in the case of the H1 and H2 as well as the H3 and H4 pairs of protons in the 4T0/E0 conformation of 1–5 and in the case of the H1 and H2 protons in the E0/1T0 conformation of 6–10. Such a lack of coupling, possible solely for the trans-oriented protons in the furanose ring, indicates that the respective protons maximally approach each other to form the H–C–C–H torsion angle of about 90°. This is also an indication that the furanose ring adopts a specific conformation and does not exist in the conformational equilibrium. Arranged almost ecliptically, the cis-oriented H2 and H3 protons, with the 2,3-O-isopropylidene fused ring in 1–10 and 15–18, form the H2–C2–C3–H3 torsion angle in a range of 0–10°. The respective coupling constant is then in the range of 5.86–6.41 Hz. The same cis-oriented protons not restricted by the 2,3-O-isopropylidene ring can move apart to the torsion angle of about 40°. Then, the J2,3 coupling constant decreases, as in the case of 11–14, where it is in the range of 4.83–5.19 Hz. The main factor influencing the conformational preferences of the β-d-ribofuranose ring is the unfavorable ecliptic interaction of the 2-OH and 3-OH groups. This is the strongest in the E0 (West side) and 0E (East side) conformations and the weakest in the 3T2 (North side) and 2T3 (South side) conformations. In the case of furanosides with the β-D-ribo configuration on the West side of the pseudorotational wheel, the unfavorable 1,3-pseudodiaxial interaction between the aglycone and terminal hydroxymethyl group also takes place. Not restricted by the 2,3-O-isopropylidene ring ribonucleosides, both 11–14 and those found in the CCDC database, adopt the 3E-like or 2E-like conformations, where these two unfavorable interactions are the most limited. The endo-anomeric effect is too weak to have an influence on the conformational preferences of ribonucleosides. However, the endo-anomeric effect is an important factor in the case of β-d-ribofuranosides. It acts both in β-d-ribofuranosides that are conformationally unrestricted (CCDC database) and restricted by the fused 2,3-O-isopropylidene ring (1–10 plus CCDC database). The endo-anomeric effect causes the former group of O-furanosides to adopt the E2-like conformation and the latter group of O-furanosides to adopt the E0-like conformation. Ribonucleosides with the 2,3-O-ketal fused ring, both 15–18 and those found in the CCDC database, do not adopt the E0-like conformation. This is the best evidence that in their cases, the anomeric effect is not a determinative factor influencing the conformational preferences. In the case of the presented O-furanosides, the action of the exo-anomeric effect is also proved.
There are no conflicts to declare. | true | true | true |
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PMC9557906 | Sisi Chen,Binyun Ma,Xue Li,Kailang Zhang,Yankai Wei,Bei Du,Xun Liu,Ruihua Wei,Xiaorong Li,Hong Nian | MYC-mediated silencing of miR-181a-5p promotes pathogenic Th17 responses by modulating AKT3-FOXO3 signaling | 23-09-2022 | Biological sciences,Molecular biology,Immunology | Summary Pathogenic Th17 cells drive autoimmune pathology, but the molecular mechanisms underlying Th17 pathogenicity remain poorly understood. Here, we have shown that miR-181a-5p was significantly decreased in pathogenic Th17 cells, and it negatively regulated pathogenic Th17 cell responses in vitro and in vivo. Th17 cells overexpressing miR-181a-5p exhibited impaired ability to induce pathogenesis in an adoptive transfer model of experimental autoimmune uveitis (EAU). Mechanistically, miR-181a-5p directly targeted AKT3, diminishing AKT3-mediated phosphorylation of FOXO3, and thereby activating FOXO3, a transcriptional repressor of pathogenic Th17 cell program. Supporting this, decreasing miR-181a-5p and up-regulated AKT3 expression were found in uveitis patients. Furthermore, intravitreal administration of miR-181a-5p mimics in mice effectively attenuated clinical and pathological signs of established EAU. Collectively, our results reveal a previously unappreciated T cell-intrinsic role of miR-181a-5p in restraining autoimmunity and may provide a potential therapeutic target for uveitis treatment. | MYC-mediated silencing of miR-181a-5p promotes pathogenic Th17 responses by modulating AKT3-FOXO3 signaling
Pathogenic Th17 cells drive autoimmune pathology, but the molecular mechanisms underlying Th17 pathogenicity remain poorly understood. Here, we have shown that miR-181a-5p was significantly decreased in pathogenic Th17 cells, and it negatively regulated pathogenic Th17 cell responses in vitro and in vivo. Th17 cells overexpressing miR-181a-5p exhibited impaired ability to induce pathogenesis in an adoptive transfer model of experimental autoimmune uveitis (EAU). Mechanistically, miR-181a-5p directly targeted AKT3, diminishing AKT3-mediated phosphorylation of FOXO3, and thereby activating FOXO3, a transcriptional repressor of pathogenic Th17 cell program. Supporting this, decreasing miR-181a-5p and up-regulated AKT3 expression were found in uveitis patients. Furthermore, intravitreal administration of miR-181a-5p mimics in mice effectively attenuated clinical and pathological signs of established EAU. Collectively, our results reveal a previously unappreciated T cell-intrinsic role of miR-181a-5p in restraining autoimmunity and may provide a potential therapeutic target for uveitis treatment.
Th17 cells drive the pathogenesis of various autoimmune disorders, including uveitis and its animal model, experimental autoimmune uveitis (EAU) (Amadi-Obi et al., 2007; Chong et al., 2020; Zhong et al., 2021). The integrated cytokine signaling induced by TGF-β, IL-1β, IL-6, and IL-23 promote the expression of the lineage-defining transcription factor RORγt and subsequent Th17 cell program (Lee et al., 2012). Accumulating evidences demonstrate that Th17 cells induced by TGF-β and IL-6 secrete immunoregulatory cytokine IL-10 and are largely nonpathogenic (McGeachy et al., 2007), and Th17 cells require IL-23 for their pathogenic effector functions (Ghoreschi et al., 2010; Lee et al., 2012). Compared to nonpathogenic Th17 cells, pathogenic Th17 cells express high levels of Il23r, Il1r1, Csf2 and Ccl5 (Hu et al., 2017; Lee et al., 2012). Yet, despite extensive studies conducted both in vivo and in vitro, the molecular mechanisms underlying pathogenic Th17 cell function are insufficiently understood. miRNAs (miRs), a class of small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level, have been reported to affect autoimmunity (Mehta and Baltimore, 2016; Singh et al., 2014). Deficiency of Dicer leads to the development of autoimmune diseases (O'Connell et al., 2010). Moreover, published works have verified that certain miRs play a pivotal role in pathogenic Th17 cells. Knocking out or knocking down miR-183C or miR-301a results in decreased pathogenic Th17 cell responses in vitro and in vivo (Ichiyama et al., 2016; Mycko et al., 2012). However, the roles of miRs in regulation of pathogenic Th17 cells induced by IL-23 are still largely unknown. miR-181a has been implicated in immune responses (Kim et al., 2021). miR-181a-5p is the main mature form of miR-181a precursor (Griffiths-Jones et al., 2008). It restrains M1 macrophage polarization (Bi et al., 2016), promotes CD4+ T cell differentiation toward the Treg and Th2 subsets and inhibits Th1 differentiation (Liu et al., 2019; Sang et al., 2015). Recently, it has been linked to Th17 cell differentiation (He et al., 2022; Sang et al., 2015). However, the cell-intrinsic function of miR-181a-5p in the regulation of pathogenic Th17 cells remains unclear. In this study, we showed that pathogenic Th17 cell function was regulated by miR-181a-5p. Furthermore, miR-181a-5p targeted AKT3 to control pathogenic Th17 cell responses via modulating AKT3-regulated FOXO3-dependent gene expression program. Th17 cells overexpressing miR-181a-5p displayed impaired ability to induce EAU. Notably, local administration of miR-181a-5p effectively ameliorated clinical and pathological signs of established EAU. Collectively, our findings reveal a previously unrecognized role of miR-181a-5p in autoimmunity, which may have clinical implications.
To uncover potential EAU-suppressor miRs that are significantly down-regulated in EAU, we performed miRNA microarray analysis in EAU CD4+ T cells and naive CD4+ T cells. As shown in Figure 1A, we found that 14 miRs were down-regulated at least 2-fold in EAU CD4+ T cells compared to controls. Among these, miR-181a-5p was the most down-regulated miR, which was further confirmed by real-time qRT-PCR (Figures 1B and S1). Given that it was also significantly decreased in uveitis patients by excavating miRNA microarray data in GSE145191 (Figure 1C), we focused on miR-181a-5p in the subsequent studies. We examined the expression of miR-181a-5p in several Th subsets and found that it was significantly decreased in Th17 cells compared with that in Th1 and Th0 cells (Figure 1D). Further analysis revealed that IL-23 inhibited miR-181a-5p expression in a dose-dependent way (Figure 1E). We next determined the relevance between miR-181a-5p level and the disease process of EAU, and found that miR-181a-5p expression was significantly reduced in Th17 cells during the course of EAU and was closely correlated with disease severity (Figure 1F). To examine the role of miR-181a-5p in IRBP-Th17 responses, CD4+ T cells from EAU mice transfected with miR-181a-5p mimics, inhibitor or their corresponding controls were co-cultured with antigen-presenting cells (APCs) and immunizing antigen (IRBP1-20) or irrelevant antigen (OVA323-339) under Th17-polarizing conditions. As shown in Figure 1G, T cells overexpressing miR-181a-5p exhibited significantly reduced IL-17 production, when T cells were restimulated with IL-23 and APCs in the presence of IRBP1-20, but not in the presence of OVA323-339. Consistent with the change of IL-17 secretion, Th17 cell percentages (Figure 1H) and the expression of pathogenic Th17 signature genes, such as Il17, Csf2, Ccl5, Il23r, and Il1r1 (Figure 1I), were also significantly decreased in miR-181a-5p mimics-transfected cells relative to control group. In addition, knockdown of miR-181a-5p dramatically promoted the production of IL-17 (Figure 1J) and the expression of Il17, Csf2, Ccl5, Il23r, and Il1r1 mRNA (Figure 1K). These data indicate that miR-181a-5p serves as a negative regulator of pathogenic Th17 responses in vitro.
To investigate the in vivo effect of miR-181a-5p on EAU pathogenesis, we overexpressed miR-181a-5p by intravenous injecting with approximately 5 × 107 transducing units (TU) of lentivirus-miR-181a (LV-181a) into C57BL/6 mice before EAU induction (Du et al., 2009) (Figure 2A). As shown in Figure S2B, administration of LV-181a resulted in a significant increase of miR-181a-5p in several organs. After immunization, severe vasculitis, multiple chorioretinal lesions and papilledema were observed in LV-Ctrl-infected mice, whereas LV-181a-infected mice exhibited significantly attenuated EAU (Figure 2B). Histological analysis showed that inflammatory infiltration and retinal damage were also dramatically reduced in LV-181a-infected mice compared with the control group (Figure 2C). We then sought to determine whether the attenuated EAU induced by miR-181a-5p was because of the altered Th17 responses. To this end, CD4+ T cells isolated from different groups were restimulated with IRBP1-20 and APCs under Th17 cell polarizing conditions, and we found that relative to the control group, IRBP-specific Th17 responses from LV-181a-infected mice were reduced as shown by significantly reduced percentages of Th17 cells and greatly decreased IL-17 production (Figures 2D and 2E). Further analysis revealed that signature genes of pathogenic Th17 cells, including Il17, Rorc, Csf2, Il23r, Ccl5, and Tbx21, were also significantly down-regulated (Figure 2F), whereas genes related to Treg cell subsets, such as Il10, Tgfb, Ahr, and Foxp3, were markedly up-regulated in T cells from LV-181a-infected mice (Figure 2G). In line with the change of Treg-related gene expression, the proportion of Treg cells in the T cells from LV-181a-infected mice was increased when compared to the control group (Figure 2H). Moreover, miR-181a-5p treatment significantly decreased the expression of proinflammatory cytokines including Il1b, Il23, Il6, and Il12 (Figure 2I). Collectively, these findings suggest a critical role for miR-181a-5p in suppressing pathogenic Th17 cells and EAU.
To assess CD4+ T cell-intrinsic function of miR-181a-5p, we utilized the adoptive transfer model of EAU (Nian et al., 2012). CD4+ T cells isolated from IRBP1-20-immunized C57BL/6 mice were transfected with Ctrl or miR-181a-5p mimics and restimulated with IRBP1-20 in the presence of APCs under Th17-polarizing conditions. Two days later, activated Th17 cells were adoptively transferred into naive C57BL/6 mice which were monitored for EAU score by fundus examination (Figure 3A). As shown in Figure 3B, the mice that received Th17 cells transfected with miR-181a-5p mimics developed significantly attenuated EAU compared with those that received Ctrl mimics-transfected Th17 cells. This trend was also seen at the level of histopathology. The inflammatory infiltration and retinal damage were significantly reduced in mice receiving Th17 cells overexpressing miR-181a-5p relative to the control group (Figure 3C). In addition, the secretion of IL-17 and IFN-γ (Figures 3D and 3E), as well as the relative expression of Il17 and Ifng mRNA (Figure 3F), were significantly decreased in T cells from the mice that received miR-181a-5p mimics-transfected Th17 cells. Further analysis revealed that the expression of Foxp3 and Ahr mRNA, as well as the percentage of Treg cells in the T cells from mice receiving Th17 cells overexpressing miR-181a-5p were increased when compared to the control group (Figures 3F and 3G). miR-181a-5p overexpression in IRBP-specific Th17 cells leads to a significantly less pathogenic EAU phenotype, strongly confirming the T cell-intrinsic role of miR-181a-5p in pathogenic Th17 function.
To understand how miR-181a-5p regulates pathogenic Th17 cell function, we sought to identify the potential miR-181a-5p targets using TarBase, Pictar, StarBase, and Targetscan databases (Figure 4A). Among the predicted targets, Akt3 attracted our attention due to its role in regulating CD4+ T cell function (DuBois et al., 2019). Akt3 mRNA has a highly conserved miR-181a-5p binding site within its 3′UTR among vertebrates (Figure 4B). To determine whether Akt3 is a direct target of miR-181a-5p, luciferase reporter constructs were generated with wildtype (WT) or mutant (mut) Akt3 3′UTR. As shown in Figure 4C, luciferase activity was suppressed by miR-181a-5p mimics in HEK293T cells transfected with Akt3-WT 3′UTR but not those transfected with Akt3-mut 3′UTR. In addition, real-time qRT-PCR and western blot analysis revealed that AKT3 expression was decreased in miR-181a-5p overexpressing Th17 cells (Figures 4D and 4E), but was increased after miR-181a-5p inhibitor transfection (Figure 4F). Consistent with in vitro results, T cells from LV-181a-infected EAU mice also displayed a significantly decreased AKT3 expression (Figure 4G). Further analysis revealed that Akt3 expression showed a negative correlation with miR-181a-5p expression in Th17 cells during EAU (Figures 4H and 4I). Together, these data indicate that AKT3 is a functional target of miR-181a-5p. To test whether AKT3 is functionally important for miR-181a-5p-mediated reduced Th17 responses, CD4+ T cells from EAU or mouse T-cell lymphoma cell line EL4 T cells were transfected with siRNA specific for Akt3 or control siRNA and cultured in Th17 polarizing conditions. As shown in Figure 4J, AKT3 was indeed knockdown by Akt3 siRNA with a reduction of IL-17 secretion (Figure 4K) and decreased expression of Il17, Rorc, Il23r, Il1r1, Ccl5 and Tbx21 mRNA (Figure 4L). Similarly, the expression of Il17, Rorc, Csf2, and Il23r was also repressed in siAkt3-transfected EL4 T cells compared with the control group (Figure 4M). Besides, inhibiting AKT3 activity partially counteracted increased IL-17 production, Il23r and Ccl5 expression induced by miR-181a-5p inhibitor (Figures 4N and 4O). These results suggest that AKT3 may partially mediate the inhibitory effect of miR-181a-5p on pathogenic Th17 cells.
Because FOXO3 is a downstream target of PI3K/AKT3 signaling (Manning and Toker, 2017), we next examined whether miR-181a-5p affects the AKT3/FOXO3 signaling. Overexpression of miR-181a-5p in Th17 cells substantially inhibited AKT3/FOXO3 signaling as indicated by significantly decreased phosphorylation of AKT3 and FOXO3 (Figure 5A). Similar to the in vitro results, the phosphorylation levels of AKT3 and FOXO3 in CD4+ T cells from LV-181a-infected EAU mice were also dramatically decreased as compared with control mice (Figure 5B). Given that the phosphorylation of FOXO proteins by AKT could trigger their relocation from the nucleus to the cytosol and therefore inactivate their transcription factor activity (Manning and Toker, 2017), we investigated the effect of miR-181a-5p on the nuclear localization of FOXO3 using an immunofluorescence assay. We found that FOXO3 protein primarily localized to the cytoplasm of EL4 T cells and miR-181a-5p overexpression induced FOXO3 nuclear translocation (Figure 5C), suggesting that miR-181a-5p may suppress pathogenic Th17 cell function by activating FOXO3 nuclear translocation. IL-23R is closely involved in the pathogenicity of Th17 cells (Wu et al., 2013), and RORγt is necessary for IL-23R expression in Th17 cells. We previously reported that FOXO3 suppressed Il23r expression, and there was a potential FOXO3 binding site close to the RORγt binding region on the Il23r promoter locus (Wei et al., 2019). This led us to hypothesize that FOXO3 might regulate IL-23R expression via affecting RORγt function. To confirm this, we constructed a luciferase reporter containing Il23r promoter region to analyze the transcriptional activity of IL-23R. As shown in Figure 5D, FOXO3 efficiently inhibited RORγt induced Il23r luciferase activity in HEK293 T cells in a dose-dependent manner, whereas FOXO3 alone did not significantly affect Il23r luciferase activity. These data suggest that FOXO3 might negatively regulate IL-23R expression via interference with RORγt activity in Th17 cells. Ccl5, one of the key pathogenic Th17 cell signature genes (Hu et al., 2017; Lee et al., 2012), plays an important role in the pathogenesis of uveitis (Niu et al., 2019). Here, we observed that FOXO3 significantly suppressed the expression of Ccl5 in Th17 cells (Figure 5E), and bioinformatic analysis with JASPER (http://jaspar.genereg.net/) revealed the presence of putative FOXO3 binding sites in Ccl5 promoter region. These suggest that FOXO3 might negatively regulate Ccl5 transcription via binding its promoter region. To test this, a luciferase reporter containing Ccl5 promoter region was constructed to analyze the direct role of FOXO3 on Ccl5 promoter activity. As shown in Figure 5F, FOXO3 dramatically reduced the levels of Ccl5 promoter activity in a dose-dependent manner, as measured by luciferase activity, suggesting that binding of FOXO3 to the promoter region of Ccl5 is critical for its transcriptional repression. Together, these data strongly indicate that dramatic Th17 cell defects associated with miR-181a-5p overexpression are at least in part caused by faulty AKT3-FOXO3 signaling.
Epigenetic modifications, such as trimethylation of histone 3 lysine 27 (H3K27me3), are key mediators of miRNAs dysregulation (Baer et al., 2013). Recent studies revealed that MYC recruited EZH2, the histone methyltransferase of the polycomb repressive complex 2 catalyzing H3K27me3, to epigenetically silence tumor suppressor genes (Wang et al., 2014; Zhang et al., 2018). We wondered whether miR-181a-5p downregulation in pathogenic Th17 cells has a similar mechanism. We first examined the expression of Myc and Ezh2 in EAU, and observed that both Myc and Ezh2 were significantly increased in IRBP-specific Th17 cells (Figures 6A and 6B). Using siRNA-mediated knockdown of Myc or Ezh2 in Th17 cells (Figure 6C), we further found that either silencing Myc or Ezh2 robustly increased miR-181a-5p and pri-miR-181a expression (Figures 6D and 6E), suggesting the involvement of both MYC and EZH2 in regulation of miR-181a-5p expression. Moreover, we found a broad overlap of MYC and EZH2 occupancy on the miR-181a promoter (Valencia et al., 2020) in T cell (Figure 6F) by analyzing the ChIP-seq datasets of Cistrome Project (http://cistrome.org/). To explore how MYC and EZH2 repress miR-181a transcription, we constructed a luciferase reporter containing miR-181a promoter region. As presented in Figure 6G, co-transfection of siMyc and siEzh2 induced remarkably increased luciferase activity of miR-181a promoter, as compared with transfection with siMyc and siEzh2 alone. However, overexpression of MYC greatly suppressed the luciferase activity of miR-181a promoter and the addition of siEzh2 abolished that (Figure 6H), indicating that MYC might decrease miR-181a-5p expression by recruiting EZH2 to miR-181a promoter. To confirm MYC and EZH2 mediated methyltransferase activity, we sought to identify H3K27me3 marks on the promoter of miR-181a. As shown in Figure 6I, the enrichment of H3K27me3 marks was noted on the miR-181a promoter region in Th17 cells relative to naive CD4+ T cells by analyzing ChIP-seq dataset (GSE14254). Moreover, treatment of Th17 cells with H3K27me3 inhibitor deazaneplanocin A (DZNep) led to robust re-expression of pri-miR-181a and miR-181a-5p (Figure 6J). Collectively, these results indicate that MYC and EZH2 coordinately suppress miR-181-5p expression through H3K27me3 in pathogenic Th17 cells (Figure 6K).
To explore the translational implications of our findings, we examined the therapeutic effect of local miR-181a-5p administration on established EAU. To this, liposomes containing miR-181a-5p mimics or Ctrl mimics were intravitreally injected into EAU mice (Sun et al., 2015) at the early phase of disease (day 11 after EAU induction) (Figure 7A). As shown in Figure 7B, treatment with miR-181a-5p-mimics significantly reduced EAU clinical scores compared to control mice. Consistently, slight inflammatory infiltrates in the retina/vitreous cavity and reduced retinal damage were detected by histopathological analysis in miR-181a-5p mimics treated mice (Figure 7C). These results suggest that miR-181a-5p may be a promising therapeutic target for uveitis treatment.
To evaluate the potential clinical relevance of this regulatory pathway in human, we analyzed the publicly available datasets of uveitis patients. miR-181a-5p was down-regulated in the peripheral blood mononuclear cells (PBMCs) of Behçet’s disease (BD) patients (Puccetti et al., 2018) and enucleated globes of sympathetic ophthalmia (Kaneko et al., 2012) (Figure 8A). Also, upregulated expression of AKT3 was observed in PBMCs of patients with BD (Figure 8B), and a positive correlation between the expression of AKT3 and pathogenic Th17 signature genes (including IL-17, RORC, IL-23R, GM-CSF and CCL5) was shown in CD4+ T cells from BD patients (Figure 8C). Moreover, MYC was up-regulated in the CD4+ T cells of BD patients (Figure 8D). These findings suggest that similar to mouse the potential regulatory pathway of MYC/miR-181a-5p/AKT3 appears to operate in human uveitis.
miRs are important for Th17 cell function in autoimmunity. However, limited information is available on the roles of miRs in pathogenic Th17 cell responses. In this study, we revealed a previously unrecognized role of miR-181a-5p in controlling pathogenic Th17 cells. miR-181a-5p was significantly decreased in pathogenic Th17 cells, and it inhibited pathogenic Th17 cell responses in vivo and in vitro. At the molecular level, miR-181a-5p directly targeted AKT3 to reduce the phosphorylation levels of AKT/FOXO3, leading to decreased IL-23R and CCL5 expression. Accordingly, both global and Th17 cell-specific overexpression of miR-181a-5p effectively protects mice against the development of EAU. miR-181a-5p has been linked to the Th17 cell biology. It inhibited Th17 cell differentiation by targeting IFN-γ (Sang et al., 2015) in human CD4+ T cells on anti-CD3/CD28 stimulation, decreased the frequency of Th17 cells by inhibiting HMGB1 or IL-2 expression in murine CD4+ T cells (He et al., 2022; Liu et al., 2019), and affected cell survival by modulating BCL-2 expression in Th17 cells (Song et al., 2018). Nonetheless, little is known with regard to the role of miR-181a-5p in pathogenic Th17 cells. Here, using combination of loss- and gain-of-function experiments, IRBP-induced or T cell transfer model of EAU, we demonstrated that miR-181a-5p suppressed pathogenic Th17 cell responses as well as the ability of Th17 cells to provoke EAU in vivo and in vitro. These data highlighted the importance of T cell-intrinsic miR-181a-5p in controlling pathogenic Th17 cell function and EAU. Enhanced miR-181a-5p expression may cause the decreased survival and proliferation of autoreactive Th17 cells, leading to alleviated EAU in miR-181a overexpressing mice. In addition, we observed a significant decrease in the expression of Il23, Il6, and Il1b in the spleens of LV-181a-infected EAU mice and miR-181a-5p-overexpressing dendritic cells (DCs) (Figures 2I and S3A). IL-23, IL-6, and IL-1β produced mainly by DCs are pathogenic Th17 cell instructive cytokines (Ghoreschi et al., 2010). IL-6 is essential for priming pathogenic Th17 cell responses (Heink et al., 2017), and IL-23 and IL-1β signaling can promote stabilization and expansion of pathogenic Th17 cells (Lee et al., 2012; Mufazalov et al., 2017). By reducing these cytokines, miR-181a-5p modulated DCs may create a cytokine milieu that indirectly suppresses the generation of pathogenic Th17 cells in EAU. Indeed, we found that miR-181a-5p-overexpressing DCs significantly decreased the expression of pathogenic Th17 signature genes and the percentages of Th17 cells in vitro (Figures S3B and S3C). Via inhibiting Th1-associated transcription factor Tbx21 and cytokine IFN-γ, miR-181a-5p also dramatically repressed pathogenic Th1 responses, in line with previous studies showing that miR-181a-5p inhibited Th1 responses via targeting of IFN-γ in vitro (Sang et al., 2015). Given that both Th17 and Th1 cells are important mediators of uveitis (Luger et al., 2008), manipulation of miR-181a-5p expression may be a potential therapeutic strategy for uveitis treatment. Indeed, we observed that local administration of miR-181a-5p mimics effectively ameliorated the severity of established EAU. Our further mechanism study showed that AKT3 is a functional target of miR-181a-5p in EAU, which is consistent with a recent study revealing that miR-181a-5p negatively regulated the expression of AKT3 in gastric adenocarcinoma (Lu et al., 2019). AKT3 deficient naive T cells exhibited a significantly increased efficiency of differentiation toward Th17 cells (DuBois et al., 2019). Nonetheless, AKT3 in control of antigen-specific Th17 cell responses has not been investigated. Here, we found that AKT3 silencing resulted in significantly decreased IL-17 production and reduced expression of pathogenic Th17 signature genes, suggesting that AKT3 functions as a T cell-intrinsic positive regulator of pathogenic Th17 cells. Compatible with our observation is the data that AKT3 expression correlated positively with the expression of pathogenic Th17 signature genes in uveitis patients, implicating the importance of AKT3 in human Th17-driven autoimmunity. Importantly, we also found that AKT3 silencing partially reversed increased pathogenic Th17-related gene expression induced by miR-181a-5p inhibitor in Th17 cells, indicating the involvement of AKT3 signaling in miR-181a-5p-mediated defective pathogenic Th17 responses. However, we cannot exclude the involvement of other mechanisms. For instance, miR-181a-5p can modulate ERK signaling to favor human memory Th17 cell activation (Mele et al., 2015). Whether miR-181a-5p could regulate pathogenic Th17 responses via ERK signaling in EAU remained to be determined. FOXO3, one main member of the FOXO transcription factor family, is a key downstream target of AKT signaling. It has been shown to promote Treg generation by facilitating TGF-β-induced Foxp3 expression via binding to its locus (Ouyang et al., 2010), and drive pathogenic Th1 cell differentiation by inducing Eomes expression (Stienne et al., 2016). However, the role played by FOXO3 in Th17 responses is less well defined. IL-23/IL-23R signaling was important for the stability and function of pathogenic Th17 cells (Wu et al., 2013). Here, using luciferase reporters containing Il23r promoter region, we demonstrated that FOXO3 inhibited the transcription of Il23r via interference of RORγt activity. CCL5, a key chemokine that can expand Th17 cell-mediated autoimmune pathogenesis via recruiting inflammatory cells into intraocular inflammatory sites (Niu et al., 2019), is among the genes that highly expressed in human and murine pathogenic Th17 cells (Hu et al., 2017). Moreover, CCL5 has been reported to be elevated in the aqueous humor and vitreous of patients with autoimmune uveitis and correlated with the clinical severity of the disease (Adamus et al., 2001; Fukunaga et al., 2020), further supporting the role of this chemokine in human ocular inflammation. In vascular smooth muscle cells, NF-κB and STAT3 interacted to modulate CCL5 transcription (Kovacic et al., 2010). Moreover, ASIC1a enhanced CCL5 expression by inducing nuclear translocation of NFATc3 in rheumatoid arthritis synovial fibroblasts (Zhang et al., 2020). Our findings that FOXO3 repressed CCL5 expression by directly binding to its promoter region add another layer of complexity to the CCL5 regulatory network. In addition, the promoter region of Il17a gene has several putative FOXO3-binding sites (FBS) (Figure S4A), meaning that it can be modulated directly by FOXO3. Collectively, FOXO3 might control the pathogenicity of Th17 cells to act on not only IL-23R but also CCL5 or others. FOXP3+ Treg cells suppress inflammation and control the development of various autoimmune diseases including uveitis. IL-10 and TGF-β released by Tregs directly mediate their inhibitory function. Recently, AHR has been demonstrated to inhibit the enrichment of histone H3K9me3 at Foxp3 promoter region and promote the expression of FOXP3 and IL-10 (Lv et al., 2018). Here, we observed a significant increase not only in the percentage of Treg cells but also in the expression of Treg-related genes in the T cells from miR-181a-overexpressing mice, suggesting that miR-181a-5p may augment Treg cell differentiation and function. Our results are supported by previous studies showing that miR-181a promoted Treg differentiation through targeting SMAD7 in vitro (Ghorbani et al., 2017), and miR-181a deficiency impaired the generation of Tregs via elevating the expression of CTLA4 in thymus (Lyszkiewicz et al., 2019). In contrast, Serr et al. (2018) reported that miR-181a mimics impeded human and murine Treg induction by enhancing NFAT5 expression. Further studies are needed to define the molecular mechanisms underlying modulation of Tregs by miR-181a -5p in EAU. Aberrant miRs expression has been reported in uveitis (Kaneko et al., 2012; Muhammad et al., 2019; Puccetti et al., 2018; Wei et al., 2019). However, the molecular basis for miR dysregulation remains unclear. EZH2 is the histone methyltransferase that catalyzes H3K27me3, thereby mediating epigenetic gene silencing (Baer et al., 2013). Recent studies have shown that MYC is essential for recruiting EZH2 to the regulatory regions of miRs, which further mediate H3K27me3 and induce silencing of tumor suppressive miRs (Wang et al., 2014; Zhang et al., 2018). In this study, we revealed that MYC was highly expressed in IRBP-specific Th17 cells and positively regulated Th17 responses (Figures 6A and S5A–S5D), in line with a previous study in EAE showing that the pharmacological inhibition of MYC resulted in significantly decreased IL-17 production (Bandukwala et al., 2012). Furthermore, we found that MYC and EZH2 might act in concert to epigenetically silence miR-181a-5p expression in IRBP-specific Th17 cells, implying the important role of MYC in EAU progression that warrants further study. In the endometrial cancer cell, lncRNA DLEU2 interacted with EZH2 to inhibit hsa-miR-181a expression (Dong et al., 2021), suggesting the complexity of the molecular regulatory networks underlying miR-181a dysregulation. Of note, a study from Shi et al. (2018) reported that miR-181a was silenced in human colorectal cancer because of DNA hypermethylation. In contrast, we did not observe statistical difference in levels of miR-181a-5p between DNA methyltransferases inhibitor treated and untreated Th17 cells (Figure S6A). Differences in species and cell types may account for the discrepancy in these studies. Future studies should define how MYC and EZH2 cooperatively control miR-181a-5p expression in the progression of EAU. In summary, our findings elucidated a critical function for miR-181a-5p in attenuating Th17 cell-mediated autoimmunity. miR-181a-5p directly targets AKT3, which activates AKT3-regulated transcription factor activity of FOXO3, leading to decreased pathogenic Th17 cell responses. These findings shed new light on uveitis mechanisms and might guide the development of effective therapeutics for uveitis and other Th17-mediated autoimmune diseases.
In this study, we perform extensive in vitro and in vivo experiments to prove that miR-181a-5p negatively regulates pathogenic Th17 cell functions via modulating AKT3/FOXO3 signaling. However, we cannot rule out the involvement of other signaling pathways. Also, detailed study is necessary to define how MYC and EZH2 cooperatively control miR-181a-5p expression in pathogenic Th17 cells in EAU. In addition, miR-181a-5p shows promising therapeutic effects in EAU, whereas the comparable effects remain to be assessed in human studies.
Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Hong Nian ([email protected]).
This study did not generate new unique reagents.
Pathogen-free female C57BL/6 mice (10 weeks old) were obtained from Vital River Laboratory Animal Technology (Beijing, China). Mice were housed in a temperature-controlled (22 ± 2°C), specific pathogen-free barrier facility under a 12-hour light/dark cycle with a standard laboratory diet and water ad libitum. All animal experiments were approved by the Institutional Animal Care and Use Committee of Tianjin Medical University (ethics approval number: TJYY2019110117), in line with the requirements of the Association for Research in Vision and Ophthalmology (ARVO) Statement for the Use of Animals in Ophthalmic and Vision Research.
For induction of EAU by active immunization, female C57BL/6 mice (female mice were chosen as there is a higher incidence of autoimmune uveitis in women than in men (Agarwal et al., 2012; Bowers et al., 2022)) were injected intraperitoneally (i.p.) with 800 ng of pertussis toxin and immunized subcutaneously (s.c.) at over six spots on the tail base and flank with uveitogenic peptide IRBP1–20 (200 μg per mouse) emulsified in an equal volume of complete Freund’s adjuvant (CFA) containing Mycobacterium tuberculosis strain H37RA (0.8 mg per mouse). Interphotoreceptor retinoid-binding protein (IRBP) peptide 1–20 (aa 1–20 of human IRBP) was synthesized and purified by Sangon Biotech (Shanghai, China). Mycobacterium tuberculosis strain H37RA and pertussis toxin were purchased from BD Biosciences (San Jose, CA, USA) and Sigma-Aldrich, Merck (Darmstadt, Germany), respectively. For induction of EAU by adoptive transfer, CD4+ T cells from IRBP1-20-immunized mice were transfected with Ctrl or miR-181a-5p mimics, and then transfected T cells (1 × 107 cells/well) were restimulated in vitro with IRBP1-20 (10 μg/ml) in the presence of 1 × 107 irradiated (30 Gy) syngeneic splenocytes as antigen-presenting cells (APCs) under Th17 cell polarizing conditions. After 2 days, the activated T cell blasts were isolated by density gradient centrifugation (Ficoll; GE Health Care, Little Chalfont, UK) and injected i.p. into naive C57BL/6 mice (5 × 106 cells per mouse) as described previously (Nian et al., 2012; Shao et al., 2006).
Clinical signs of EAU were assessed by indirect fundoscopy three times a week. The pupils were dilated using 0.5% tropicamide and 1.25% phenylephrine hydrochloride ophthalmic solutions, and fundoscopic grading of the disease was performed in a blinded manner on a scale from 0 to 4 according to published scoring criteria that are based on the severity and extent of the inflammatory lesion (Agarwal et al., 2012). In brief, the clinical scoring scale is as follows: 0 = no inflammatory lesion; 0.5 = trace disease with minimal vasculitis; 1 = mildly active disease with mild vasculitis and a few small focal chorioretinal lesions; 2 = moderately active disease with severe vasculitis, multifocal chorioretinal lesions; 3 = active disease with large, confluent chorioretinal lesions, linear chorioretinal lesions, and/or hemorrhage; 4 = severely active disease with retinal detachment, hemorrhage, and/or atrophy. For histopathological analysis, whole eyes were fixed and embedded in paraffin and sectioned in 5-μm thickness along the papillary-optic nerve axis. The sections were stained with hematoxylin and eosin (H&E). The severity of EAU was scored on a scale of 0–4, based on the cellular infiltration and structural changes, using previously reported criteria (Agarwal et al., 2012): 0 = no inflammation; 0.5 = mild cellular infiltration; 1 = moderate cellular infiltration and a few retinal folds; 2 = medium cellular infiltration, multifocal retinal folds and focal photoreceptor cell damage; 3 = heavy cellular infiltration, extensive retinal folds with detachment, serous exudates, and moderate photoreceptor cell damage; 4 = very heavy cellular infiltration, extensive photoreceptor cell damage, and retinal layer atrophy.
CD4+ T cells were isolated and purified from the spleen and draining lymph nodes of EAU mice by positive selection using PE-conjugated anti-mouse CD4 antibody (BioLegend, San Diego, CA, USA), anti-PE microbeads, and auto-MACS separator (Miltenyi Biotec, Bergisch Gladbach, Germany) according to the manufacturer’s protocol. CD4+ T cells were maintained in RPMI 1640 medium (Gibco, CA, USA) with 10% heat-inactivated fetal bovine serum (HyClone, Logan, UT, USA), 50 μM β-mercaptoethanol (Gibco), 2mM L-Glutamine (Gibco), and 100 U/mL Penicillin-Streptomycin (Gibco), referred to as complete RPMI 1640 medium. Then, CD4+ T cells (1 × 106 cells/well) were co-cultured with 1 × 106 irradiated (30 Gy) syngeneic splenocytes as APCs, which were pre-incubated with 10 μg/ml IRBP1-20 for 20 min in a 24-well plate, under Th17 cell polarization (culture medium supplemented with 10 ng/ml IL-23) or Th1 cell polarization (culture medium supplemented with 10 ng/ml IL-12).
siRNAs, miR-181a-5p mimics, inhibitors, and corresponding controls were synthesized by GenePharma (Shanghai, China). All sequences used are presented in Key Resources Table. miR-181a-5p mimics, inhibitors (300 nM), or siRNAs (200 nM) were transfected into CD4+ T cells with Lipofectamine 2000 (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s instructions. Twenty-four hours after transfection, the transfected CD4+ T cells were co-cultured with IRBP1-20 (10 μg/ml) and irradiated APCs (at a ratio of 1:1) under Th17 cell polarization for additional 2 days or 8 days. Cells and supernatant were then collected for further analysis.
Total RNA was extracted from the cells and tissues (including spleen, lymph nodes, thymus, and eye) with TRIzol reagent (Thermo Fisher Scientific). RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific) was utilized to synthesize cDNA according to the manufacturer’s protocol. Real-time quantitative RT-PCR (real-time qRT-PCR) was performed with SYBR Green Master Mix (Roche, Basel, Switzerland) on LightCycler 480 Instrument (Roche). For mRNA analysis, the gene-specific primers were used (Table S1) and values were calculated using the 2-△△Ct method with glyceraldehyde-3-phosphate dehydrogenase (Gapdh) as an endogenous control. For miRNA analysis, the stem-loop primer method was used for the quantification of miR-181a-5p and its relative expression levels were normalized to U6 snRNA levels within each sample. The primer sequences were as follows: miR-181a-5p RT primer: 5′-CGAACATTCAACGCTGTCG-3′; miR-181a-5p Forward primer: 5′-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACACTCAC-3′; miR-181a-5p Reverse primer: 5′-AGTGCAGGGTCCGAGGTATT-3′.
The genomic sequence spanning the mouse miR-181a-5p precursor sequence was amplified and cloned into lentiviral vector pLL3.7 (Addgene) between the Hpa I and the Xho I site. The PLL3.7 plasmid was a gift from Prof. Chunsheng Han and Dr. Jian Chen (Institute of Zoology, Chinese Academy of Science). Rorc coding sequence or Myc coding sequence was PCR amplified from mouse spleen cDNA and inserted into the Not I and EcoR I sites of pCDH-CMV-MCS-EF1-copGFP (System Biosciences), respectively. All primers used are listed in Table S2. The PCR amplification was carried out for 30 cycles using the following parameters: predenaturation at 94°C for 3 min; denaturation at 94°C for 30 sec, annealing at 67°C (Rorc coding sequence) or 65.5°C (Myc coding sequence) for 45 sec, extension at 72°C for 2 min; and a final extension step of 5 min at 72°C.
The recombinant lentiviral plasmid was transfected into human embryonic kidney 293T cells (HEK293T) with psPAX2 (Addgene) and pMD2.G (Addgene) using Lipofectamine 2000 (Thermo Fisher Scientific). After 48 h and 72 h, the culture medium was collected and centrifuged at 2000 × g for 15 min to remove the cell debris, and then PEG8000 (Solarbio, Beijing, China) was added to concentrate the lentivirus. The titer of the lentivirus used for in vitro infection and in vivo injection was concentrated to at least 5 × 108 transducing units (TU) per milliliter. CD4+ T cells were infected with lentivirus (MOI 50) by spinning at 1000 × g for 90 min in the presence of 6 μg/ml polybrene (Solarbio). Mice were given approximately 5 × 107 TU of lentivirus by tail vein injection at a volume of 200 μl/mouse. On day 7 after the systemic administration injection, mice were actively immunized with IRBP1-20 to induce EAU. Then, the clinal and histological assessment was performed as described previously.
EAU mice were intravitreally injected with liposomes containing miR-181a-5p or Ctrl mimics (6 mice per group) at the onset of disease symptoms (about 11 days post-immunization). The Ctrl or miR-181a-5p mimics were complexed with liposomes to form nanoparticles for in vivo applications (Xiang et al., 2015). The miRNA mimics (1 mg/ml in water, 0.5 μl) were mixed with 0.5 μl lipofectamine 2000 (Thermo Fisher Scientific) for 20 min before intravitreal injection. Thereafter, 1 μl miRNA-liposome complexes were delivered into the vitreous cavity using 34-gauge Hamilton microsyringe, and the needle was kept still for 30 sec after injection to prevent leakage and reflux from the injection site.
Bone marrow-derived dendritic cells (DCs) were generated by in vitro differentiation of bone marrow cells as previously described (Lutz et al., 1999). Briefly, bone marrow cells were flushed from femurs and tibias of mice and cultured in 12-well plate (2 × 106 cells per well) with complete RPMI 1640 medium supplemented with 10 ng/ml granulocyte-macrophage colony-stimulating factor (GM-CSF; R&D system, Minneapolis, MN, USA) and 10 ng/ml interleukin-4 (IL-4; R&D system). On day 6, non-adherent cells were harvested for phenotyping and further experiments. For DCs transfection, DCs were transfected with miR-181a-5p or Ctrl mimics in 24-well plate (2.5 × 105 cells per well) using Lipofectamine 2000 (Thermo Fisher Scientific). At 24 h after transfection, DCs were treated with 100 ng/mL of lipopolysaccharide (LPS) and subjected to real-time qRT-PCR analysis. For co-cultured study, the transfected DCs were pre-incubated with IRBP1-20 (10 μg/ml) for 20 min, and then co-cultured with CD4+ T cells at a ratio of 1:10 under Th17 cell polarization for 2 days or 8 days. Then the cells were collected for real-time qRT-PCR or flow cytometry analysis.
For surface staining, cells were incubated with Fc-block (BioLegend) and stained with the following antibodies from BioLegend: PE-conjugated anti-mouse CD4 antibody (clone GK1.5), or FITC-conjugated anti-mouse CD4 antibody (clone H129.19). For intracellular staining, cells were stimulated for 4-6 h at 37°C in complete RPMI 1640 medium with phorbol myristate acetate (50 ng/ml), ionomycin (1 μg/ml), and brefeldin A (1 μg/ml) (Sigma-Aldrich, Merck), followed by fixation and permeabilization using Fixation and Permeabilization kit (eBioscience, SanDiego, CA, USA). FITC-conjugated anti-mouse IL-17 antibody (clone TC11-18H10.1) and PE-conjugated anti-mouse Foxp3 antibody (clone FJK-16s) were used for intracellular staining. Stained cells were analyzed with a FACSCalibur flow cytometer (BD Biosciences). FlowJo software (Tree star, Ashland, OR, USA) was used to analyze the acquired data.
The cytokines in the culture supernatants were detected with Mouse IL-17 DuoSet ELISA Kit (R&D Systems, Minneapolis, MN, USA) and Mouse IFN-gamma DuoSet ELISA Kit (R&D Systems) according to the manufacturer’s instructions. Briefly, 96-well plates were coated with the capture antibodies overnight at room temperature. After washing and blocking, the diluted supernatants and recombinant cytokine standards were added to the plates and incubated for 2 h at room temperature. Then, the plates were incubated sequentially with the detection antibodies and streptavidin-HRP, as well as Substrate Reagent (R&D Systems) and Stop Solution. The absorbance was measured at 450 nm with wavelength correction set to 540 nm.
RNA samples were extracted from CD4+ T cells of naïve or EAU mice using TRIzol reagent (Thermo Fisher Scientific) and subjected to miRNA array analysis by 8 × 60 K miR Microarray (Agilent Technologies, Santa Clara, CA, USA). The microarray was performed by CapitalBio Corporation (Beijing, China), and microarray data were analyzed using the GeneSpring GX software (Agilent Technologies).
Firstly, the wild-type (WT) Akt3 3′ UTR fragment containing the putative miR-181a-5p binding site or mutant (mut) Akt3 3′ UTR fragment was amplified and cloned into pMIR-REPORT Vector (Promega, Madison, WI, USA) between the Hind Ⅲ and Spe Ⅰ site as we described previously (Wei et al., 2019). For PGL3 plasmids harboring Il23r promoter, Ccl5 promoter, or miR-181a promoter, the promoter regions were amplified and cloned into pGL3-basic (Promega) between the Kpn I and Xho I site. All primers used are listed in Table S2. HEK293T cells (2.5 × 104 cells/well) or EL4 T cells (3 × 104 cells/well) were seeded in 96-well plates, and co-transfected with indicated oligonucleotides and plasmids using Lipofectamine 2000 (Thermo Fisher Scientific), and PRL-TK vector (Promega, Madison, WI, USA) was used as the internal control. Forty-eight hours after transfection, cell extracts were prepared using passive lysis buffer (Promega), and luciferase activity was detected by the Dual-Luciferase Assay System (Promega) following the manufacturer’s instructions. Firefly luciferase activity was normalized with Renilla luciferase activity.
Proteins were extracted from CD4+ T cells using RIPA lysis buffer (Solarbio, Beijing, China) accompanied by protease inhibitor PMSF (Solarbio) and phosphatase inhibitor cocktail (Cell Signaling Technology), and concentrations were determined with a BCA protein assay kit (Solarbio). 30 μg of protein were electrophoresed by SDS-PAGE and transferred onto PVDF membranes. The membranes were blocked with 5% non-fat milk for 2 h and incubated with the antibodies specific for AKT3, Phospho-AKT (Ser473), Phospho-FOXO3 (Thr32) (Cell Signaling Technology, Danvers, MA, USA) or β-actin (Santa Cruz Biotechnology, Dallas, TX, USA) at 4°C overnight. HRP-conjugated secondary antibody (ZSGB-BIO, Beijing, China) was applied at room temperature for 2 h. Signals were visualized using ECL reagent, and the optical density of the protein bands was quantified by Quantity One software (Bio-Rad, Hercules, CA, USA).
LV-181a- or LV-Ctrl-infected EL4 T cells were fixed with 4% paraformaldehyde (Solarbio) at room temperature for 15 min and then permeabilized with 0.3% TritonX-100 (Solarbio) for 10 min. After blocking with 5% goat serum (Solarbio) for 1 h, EL4 T cells were incubated with rabbit anti-FOXO3 (Cell Signaling Technology) primary antibody overnight at 4°C. The following day, the cells were incubated with the goat anti-rabbit Alexa Fluor® 594 (IgG H&L) (Abcam, Cambridge, MA, USA) at room temperature for 1 h and subsequently the nuclei were counterstained with DAPI (Sigma-Aldrich, Merck). Fluorescence images were obtained using a confocal fluorescence microscope (LSM800, Zeiss, Oberkochen, Germany) with a ×63 oil immersion objective.
Potential target genes of miR-181a-5p were predicted by TarBase (www.microrna.gr/tarbase), Pictar (https://pictar.mdc-berlin.de/), StarBase (http://starbase.sysu.edu.cn) and Targetscan (www.targetscan.org) databases. The predicted target genes are listed in Table S3. The microarray profiles (GSE70403, GSE61399, and GSE145191) were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). Heatmaps were generated with Cluster 3.0 software (Stanford University). ChIP-seq datasets were obtained from the Cistrome Project (http://www.cistrome.org/). ChIP-seq genomic tracks were visualized using Integrative Genomics Viewer (IGV) tool.
SPSS 26.0 software (IBM Corporation, Somers, NY, USA) was used for statistical analysis. All experiments were repeated 3 times or more, and the data were presented as mean ± SEM. The normal distribution of the data was evaluated by Shapiro-Wilk test. According to the normality of data and the number of groups, Student’s t-test, Mann-Whitney U test, the Kruskal-Wallis test, One-way ANOVA or two-way ANOVA were then selected respectively. Correlation analysis was evaluated by the Pearson correlation test. P values of less than 0.05 were considered statistically significant. | true | true | true |
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PMC9558137 | Yuhan Zhang,Chaoming Gao,Yahong Zhang,Hang Huang,Yameng Du,Lan Wu,Liping Wu | FTX271: A potential gene resource for plant antiviral transgenic breeding | 29-09-2022 | tobacco mosaic virus,transgenic tobacco,disease resistance mechanism,omics,resistance gene | Flammutoxin (FTX), as well as its precursor TDP, is a protein from Flammulina velutipes with antiviral activity. Transgenic tobacco with the FTX271 (gene of FTX or TDP) can not only delay the onset time of symptoms but also alleviate the symptoms caused by tobacco mosaic virus (TMV), but the mechanism is still unclear. In this study, FTX271 was introduced into Nicotiana benthamiana, and the disease resistance mechanism activated by FTX271 was speculated by transcriptomic and proteomic techniques. The results showed that TDP was detected, and some genes, proteins and pathways were significant upregulated or enriched in transgenic tobacco, including the mitogen-activated protein kinase (MAPK) cascade signal transduction pathway, the expression of hypersensitive response (HR) marker genes H1N1 and HSR203J, pathogenesis-related (PR) genes, and the key genes COI1 and lipoxygenase gene LOX2 of the jasmonic acid (JA) signaling pathway, indicating FTX271 may activate the MAPK pathway and increase the content of reactive oxygen species (ROS) and JA, which promoted the HR and inducible systemic resistance (ISR). ISR caused increased expression of peroxidase (POD) and other proteins involved in pathogen defense. In addition, transgenic tobacco may use sHSP-assisted photoreparation to alleviate the symptoms of TMV. In conclusion, JA-mediated ISR and sHSP-assisted photoreparation are activated by FTX271 to protect tobacco from TMV infection and alleviate the symptoms caused by the virus. The study provided a theoretical basis for the TMV resistance mechanism of FTX271, which may represent a potential gene resource for plant antiviral transgenic breeding. | FTX271: A potential gene resource for plant antiviral transgenic breeding
Flammutoxin (FTX), as well as its precursor TDP, is a protein from Flammulina velutipes with antiviral activity. Transgenic tobacco with the FTX271 (gene of FTX or TDP) can not only delay the onset time of symptoms but also alleviate the symptoms caused by tobacco mosaic virus (TMV), but the mechanism is still unclear. In this study, FTX271 was introduced into Nicotiana benthamiana, and the disease resistance mechanism activated by FTX271 was speculated by transcriptomic and proteomic techniques. The results showed that TDP was detected, and some genes, proteins and pathways were significant upregulated or enriched in transgenic tobacco, including the mitogen-activated protein kinase (MAPK) cascade signal transduction pathway, the expression of hypersensitive response (HR) marker genes H1N1 and HSR203J, pathogenesis-related (PR) genes, and the key genes COI1 and lipoxygenase gene LOX2 of the jasmonic acid (JA) signaling pathway, indicating FTX271 may activate the MAPK pathway and increase the content of reactive oxygen species (ROS) and JA, which promoted the HR and inducible systemic resistance (ISR). ISR caused increased expression of peroxidase (POD) and other proteins involved in pathogen defense. In addition, transgenic tobacco may use sHSP-assisted photoreparation to alleviate the symptoms of TMV. In conclusion, JA-mediated ISR and sHSP-assisted photoreparation are activated by FTX271 to protect tobacco from TMV infection and alleviate the symptoms caused by the virus. The study provided a theoretical basis for the TMV resistance mechanism of FTX271, which may represent a potential gene resource for plant antiviral transgenic breeding.
Tobacco (Nicotiana tabacum L.) is one of the most widely cultivated cash crops in China as well as worldwide (Zou et al., 2021). Many products, such as nicotine, solanesol, fiberboard, pulp, and organic fertilizers, can be generated from tobacco plants or their byproducts produced after processing (Hu et al., 2015; Banožić et al., 2020). Tobacco mosaic virus (TMV) is a positive-sense single-stranded RNA (ssRNA) virus of the genus Tobamovirus (Kobayashi et al., 2010). TMV-infected plants will exhibit various symptoms, ranging from shrunken, deformed and twisted leaves in mild cases to dwarfed plants in severe cases and abnormal flowering and fruiting, which seriously endangers the yield and quality of crops (Scholthof, 2004; Scholthof et al., 2011). Tobacco disease caused by TMV has brought much more losses to the tobacco economy than fungal and bacterial diseases, and it has become the biggest disaster that threatens tobacco production (Yuan et al., 2022). Several strategies have been developed to control viral diseases, including transgenic technology. The gene transferred into plants can give the plants good antiviral properties, and the gene source can be the virus itself or the exogenous antiviral active protein (Suzuki et al., 1996; Baranwal and Verma, 1997). In 1986, Beachy introduced the coat protein (CP) gene of TMV into tobacco and obtained the first transgenic plant resistant to TMV infection (Reinero and Beachy, 1986). After that, other component genes of different viruses, such as replicase, protease, and mobile proteins, were also used as antiviral gene resources to control viruses. Nonviral-derived gene-mediated resistance has no risk of recombination and has higher safety. Therefore, nonviral transgenic technology is one of the research hotspots at this stage. At present, the main sources of nonviral genes are plant disease resistance-related genes, potential suicide genes, ribosomal inactivation protein genes, and other genes that can induce plant resistance (Lodge et al., 1993; Zheng et al., 2011). Flammutoxin (FTX), a protein with a 251 amino acid (aa) sequence, is specifically expressed during the formation and growth of Flammulina velutipes fruiting bodies and has cardiotoxicity and cytolytic properties (Tadjibaeva et al., 2000; Jin et al., 2007). Transepithelial electrical resistance-decreasing protein (TDP) is the precursor of FTX, containing 271 aa, without cytotoxicity, but can promote paracellular permeability (Tomita et al., 2004). After analyzing the protein and nucleic acid sequences of TDP and FTX, Watanabe and Narai suggested that FTX is produced by cleaving the 20aa at the C-terminus of TDP during protein processing (Watanabe et al., 1999). Protein Zb extracted from F. velutipes can reduce the number of dead spots formed by TMV on Nicotiana glutinosa leaves (Fu et al., 2003). The aa sequence showed that the anti-TMV protein Zb may be FTX or TDP because its N-end is completely consistent with that of FTX and TDP. However, the function of FTX or TDP was only found when it acted on the cell membrane of animal cells or tobacco. To date, their real function during the formation of F. velutipes is still unclear. Our previous study found that the onset time of symptoms caused by TMV was delayed and that mosaic symptoms were significantly reduced in FTX271 transgenic tobacco (N. tabacum cv. K326), as well as in tobacco sprayed with the recombinant protein TDP (Wu et al., 2017; Han et al., 2022). Salicylic acid (SA)-mediated systemic acquired resistance (SAR) was induced by TDP to protect tobacco from TMV infection, but what causes mosaic symptoms to delay and lessen in FTX271 transgenic tobacco? Is the transgene expression product TDP or FTX? JA and SA, triggered by the interaction of elicitor and plant receptor, are widely studied in plants, and both play an important role in plant defense signal transduction (Peng et al., 2005). The Nep1-like (NLPS) toxin family is a protein elicitor and generally induces immune responses and cell death in dicotyledonous plants. It is believed that NLPS can act as a cytolytic toxin to induce leakage of the cytoplasmic membrane, thus causing cytotoxicity (Santhanam et al., 2013). Is it possible that FTX also exploits its cytolytic toxin properties to induce plant immune defenses? FTX can promote the growth of fruiting bodies, does it have a plant growth-promoting effect? To functionally characterize the FTX271 gene during the transgenic tobacco response to TMV infection, transcriptomic and proteomic techniques were used to explore the effect on the expression of endogenous proteins in transgenic tobacco before and after infection with TMV. Additionally, p35s-30B-GFP was utilized to establish the transient expression system of TMV, and GFP was used as a reporter gene to indicate the expression of the virus in plants. The disease resistance of transgenic tobacco was further explored by determining the changes in the activity of defense enzymes. Based on the results of the joint action of multiple defense-related enzymes and metabolic pathways, we suggest that FTX271 promotes the immunity of transgenic tobacco.
The seeds of N. benthamiana were preserved by our laboratory. Escherichia coli DH5α and Agrobacterium GV3101 were provided by our laboratory. The plant expression vector pROK II was purchased from Wuhan Miaoling Biological Company (Wuhan, China). The transient expression vector TMV-based p35s-30B-GFP was donated by Fujian Agriculture and Forestry University. Fresh fruiting bodies of F. velutipes were purchased from Nanchang, Jiangxi Province, China. Tobacco was planted in a greenhouse at 25°C, 16 h of light and 8 h of darkness, seeds were sown, and germinated, and when the tobacco grew to the 2-leaf stage, single tobacco was transplanted into a separate flowerpot and was watered every other day to continue cultivation. The experiment can be carried out when the tobacco grows to the 5–6 leaf stage.
The extraction of total RNA from F. velutipes was completed with reference to the instructions of the plant RNA extraction kit (CW Biotech, Nanjing, China). After the concentration of RNA was determined, it was used as a template in the reverse transcription reaction with the HiFiScript cDNA Synthesis Kit (Kangwei Century, Nanjing, Jiangsu, China). The cDNA was then subjected to PCR amplification. The primers for the cDNA sequence of FTX271 were FTX271-F 5’-GCGGATCCACATGCCTCAAGTCAAGACAAG-3′ and FTX271-R 5’-GCGGTACCTCACTCAGGACCAGGAACCA-3′, which were designed according to the sequences of TDP (GenBank accession no. AB015948; shown in Supplementary material Table S1). The sequences of GGATCC and GGTACC are the restriction sites of Kpn I and BamH I. The purified PCR amplification product was ligated with pUC19-T vector and transformed into DH5α competent cells with reference to the rapid ligation vector kit to construct a cloning vector (Takara, Japan). Single clones were picked and cultured for colony PCR identification. The identified FTX271 gene was double-digested with Kpn I and BamH I and inserted into the pROK II plasmid (Miaoling Biotechnology, Wuhan, China) that had been digested with the same restriction enzymes, thus yielding the pROK II-FTX271 vector. Using the Agrobacterium-mediated transformation method, the pROK II-FTX271 vector with correct sequencing was introduced into Agrobacterium GV3101, and the bacterial liquid was identified by PCR and sequencing (Tsingke Biotechnology Co., Ltd., Beijing, China). Tissue culture was carried out by the tobacco leaf disc method (Pathi et al., 2013), and the operations were performed in order of predifferentiation, coculture, selective culture, rooting culture, seedling cultivation, transplanting and positive strain detection. The seeds of transgenic positive plants (T0 generation) were harvested and continued to be sown, then the target gene of FTX271 was tested on the T1 and T2 generation plants.
When the T1 and T2 generation plants grew to the 5–6 leaf stage, total RNA of transgenic tobacco was extracted and subjected to RT–PCR amplification by primers FTX271-F and FTX271-R. Approximately 50 plants of the T1 and T2 generation were tested. Total protein of 3 T2 generation tobacco plants that confirmed by RT-PCR were extracted according to the kit instructions (CW Biotech, Nanjing, China). Five milliliters of protein extract (10% protein inhibitor, 90% protein extraction) was added to 1 g of leaves, ground into a homogenate, incubated on ice for 25 min, and then centrifuged at 12000 rpm (4°C, 20 min). The supernatant was concentrated by centrifugation in an ultrafiltration centrifuge tube at 4°C and 12,000 rpm for 20 min. The protein was detected by SDS–PAGE and Western blotting. A polyclonal antibody specific for the C-terminal 20 aa of TDP prepared by GL Biochem (Shanghai, China) and anti-rabbit IgG (HRP conjugated) were used as primary and secondary antibodies, respectively.
Leaves of T2 generation tobacco plants (n = 4) at the 5–6 leaf stage were infected with Agrobacterium suspension containing the TMV-based p35S-30B-GFP vector by a needle-free injector, followed by incubation in the dark for 24 h and then cultured in a greenhouse. To detect TMV multiplication, the expression of GFP was observed and photographed under a 100 W longwave ultraviolet lamp (BlackRaymodel B100ATP, UVP, Upland, CA, USA) on the 1st, 3rd, 5th, 7th, 9th, and 11th days. Wild-type tobacco was treated as a control. The concentration of TMV CP in each treatment was measured by qRT–PCR, which was performed on the Bio-Rad CFX Manager 3.1 platform, with β-actin of tobacco as an internal reference. Primers were designed according to the sequences of the housekeeping genes β-actin (GenBank: AB158612.1) and TMV CP (GenBank: AY029262.1; Supplementary material Table S1). TMV expression was assessed by evaluating the threshold cycle (CT) values. The relative expression level was calculated using the 2–ΔΔCT method (Li et al., 2019).
The experiment was divided into four groups (for three independent biological replicates from different sets of plants; transgenic plant is the T2 generation tobacco): wild-type tobacco (WT), transgenic tobacco (N), wild-type tobacco infected with Agrobacterium suspension containing TMV-based p35S-30B-GFP vector (WT-TMV), and transgenic tobacco infected with Agrobacterium suspension containing TMV-based p35S-30B-GFP vector (N-TMV). After inoculation with TMV, tobacco leaves were collected on the 1st, 3rd, 5th, 7th, and 9th days, and the total protein was extracted according to the above method. Then, the enzyme activity was detected. Enzyme activity detection was performed according to the kit instructions (Nanjing Jiancheng, Nanjing, China), and phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), POD and chitinase (Chitinase) enzyme activities were determined. The OD420 of each sample was measured. Data are expressed as the means ± SDs, n = 4 for all groups. To compare differences in means, SPSS statistics 20 was used for analysis of variance (ANOVA). The significance levels for tests were p < 0.05.
Samples were treated as above, and the upper leaves were collected on the 7th day (four leaves from four different plants per replicate; for three independent biological replicates from different sets of treatments). After treatment with liquid nitrogen, leaves were sent to BGI Tech (Shenzhen, Guangzhou, China) for transcriptome sequencing. The raw data obtained by sequencing contained reads with low quality (more than 20% of the base qualities were lower than 10), adapter contamination, and a high N content of unknown bases (high N base content more than 5%). Clean reads were obtained by filtering out these reads with Trimmomatic v0.36 software. The filtered data were then mapped to the reference genome of Nicotiana benthamiana by HISAT v2.1.0 (Hierarchical Indexing for Spliced Alignment of Transcripts), followed by new transcript prediction, SNP and InDel and differentially spliced gene detection. New transcripts with protein-coding potential that predicted using CPC v0.9-r2 were added to the reference gene sequence. The gene expression level and transcripts were quantified by RSEM v1.2.8 (Langmead and Salzberg, 2012). The Pearson correlation coefficient between each pair of samples was calculated using the cor function in R software (Supplementary material Figure S1). Read counts obtained from samples were FPKM (fragments per kilobase of exon per million fragments mapped) normalized prior to differentially expressed genes (DEGs) analysis. Based on the gene expression level, differential expression analysis was performed using DEGseq algorithms (parameters: Fold Change ≥1 and Adjusted p value ≤0.01), which provided statistical routines for determining digital gene expression data using a model based on the negative binomial distribution. Finally, the phyper function in R software was used to perform in-depth Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses on the differentially expressed genes, and FDR correction was carried out for the p value, with a Q-value ≤0.05 as the enrichment standard. Fisher’s exact test was used to screen differentially expressed proteins, and the enrichment criterion was a value of p < 0.05. WOLFPSORT was used for the subcellular localization analysis. The GO classification is divided into three functional categories: biological process, cellular component and molecular function.
Samples were treated as described above, and the upper leaves were pooled together on the 7th day. Protein extraction and digestion were performed according to Wang et al. (2003), and the peptide was dried under vacuum and stored at −80°C. Mass spectrometry analysis was performed by Hangzhou Jingjie Biological Co., Ltd. (Hangzhou, Zhejiang, China). Secondary mass spectral data were retrieved using MaxQuant (v1.6.6.0). Search parameter settings: the database is Nicotianna_benthamiana_4100_TX_20190718 (76,475 proteins; Edwards et al., 2017). The reverse library and common contamination library were added to avoid FDR. The peptide digestion method was set to Trypsin/P, and the number of missed cleavage sites was set to 2. The primary precursor ion mass error tolerance of the first search is set to 70 ppm, and the tolerance for the main search is 70 ppm; the mass error tolerance for secondary fragment ions is set to 0.04 Da. Cysteine alkylation was set as a fixed modification, and variable modifications were oxidation of methionine and acetylation and deamidation of the protein N-terminus. To accurately identify the functions of the differentially expressed proteins, GSEA (Gene Set Enrichment Analysis) was used (Lu et al., 2022). GSEA (4.0.3) is a software developed by the Broad Institute for analyzing pathways enriched by differentially expressed proteins that can scan all pathways, intuitively understanding the difference of all proteins in each pathway, while it does not depend on the p value cutoff of differential expression. To determine the consistency of biological replicates, principal component analysis (PCA) and relative standard deviation (RSD) were used for evaluation, and the results showed that the reproducibility of the samples in this experiment was good (Supplementary material Figure S2). Due to the limited measurement range during protein mass spectrometry analysis, we analyzed the results of peptide lengths in this experiment. The results show that most of the identified peptide lengths are 7–20 amino acids, which conforms to the general rule of trypsin enzymatic hydrolysis and HCD fragmentation (Supplementary material Figure S2). To better explain the function of differentially expressed proteins (DEPs) in transgenic tobacco and wild-type tobacco, we used InterProScan v.5.14–53.0 software to annotate the screened differential proteins by GO function and used Wolfpsort v.0.2 and CELLO v.2.5 for subcellular localization. To understand the biological functions of differentially expressed proteins, the annotated differential proteins were analyzed by KEGG pathway using KAAS v.2.0 and KEGG v.2.5.
To verify the reliability of the sequencing results, more than 10 pairs of plant resistance-related genes were selected, primers were designed using OLIGO 7.0, and β-actin was used as an internal reference for qRT–PCR validation (Supplementary material Table S1). The detailed process is described above. 2–ΔΔCT was used to calculate the relative expression of the samples during data processing.
The total RNA extracted from F. velutipes was subjected to reverse transcription PCR to obtain a cDNA fragment of approximately 800 bp with the specific primers FTX271-F/FTX271-R (Figure 1A). Restriction cleavage sites of BamH I and Kpn I were added to the two terminals of cDNA. After purification, the PCR product was ligated with the pUC19-T vector and transformed into E. coli DH5a competent cells. Positive clones were identified by electrophoresis and sequencing (Figure 1B). The results showed that cDNA encodes a protein sequence of 271 aa, which is consistent with the amino acid sequence of Zb (amino acid number AAP38176.1). The aa sequence showed that the anti-TMV protein Zb may be FTX or TDP because its N-end is completely consistent with that of FTX and TDP (Fu et al., 2003). The sequenced pUC19-T-FTX271 vector was digested with enzymes of BamH I and Kpn I, ligated into the plant expression vector pROK II plasmid and transformed into Agrobacterium GV3101 to construct the pROK II-FTX271 vector. The PCR identification results of the bacterial liquid showed that the vector was successfully transferred into Agrobacterium GV3101 (Figure 1C). When N. benthamiana grows to the 5–6 leaf stage, intact and undamaged young leaves were selected, and the leaf disc method was used for transgenic operations, followed by the steps of predifferentiation, coculture, selective culture, rooting culture, seedling hardening, transplanting, etc. Finally, the transgenic FTX271 gene in tobacco was successfully constructed (Figure 1D).
The T0 generation seeds of three transgenic tobacco plants were collected and sown. When the T1- and T2-generation plants grew to the 5-6-leaf stage, total RNA of transgenic tobacco was extracted and subjected to RT–PCR amplification by the primers FTX271-F and FTX271-R (Figure 1E). After sequencing, the aa sequence of the 819 bp PCR product was deduced and was completely consistent with that of TDP. Approximately 50 plants of the T1 and T2 generation were detected, and positive results were obtained in 19. The total protein extraction of T2 tobacco was completed according to the reagent instructions. A polyclonal antibody specific for the C-terminal 20 aa of TDP and goat anti-rabbit IgG (HRP conjugated) were used as primary and secondary antibodies. Wild-type was used as a negative control, purified FTX and TDP were used as positive controls, and transgenic tobacco protein was analyzed by Western blotting (Figure 1F). Total protein extracted from wild-type tobacco and purified FTX had no bands, while the total protein extracted from transgenic tobacco and purified TDP had, indicating that the FTX271 gene was exactly transformed and could stably express TDP in N. benthamiana, but FTX was not sure.
The transient expression vector p35S-30B-GFP contains the full-length cDNA sequences of TMV and GFP, which can be expressed soon after transformation into plants. Plasmids of p35S-30B-GFP were transformed into tobacco of wild type (WT) and transgenic lines (N) and then observed under a 100 W longwave ultraviolet lamp. Obvious fluorescence was detected on the 3rd day after leaves of WT were inoculated with p35S-30B-GFP, and it became increasingly stronger over time. At Day 8 after infection, stems also appeared fluorescent, and the fluorescence spread to the whole tobacco plant. The plant exhibited severe shrinkage on the 12th day. However, compared with WT, the fluorescence of transgenic tobacco was much weaker on each day; it was detected on the 5th day, and on the 12th day, fluorescence only appeared on the top leaves and the stem, indicating that the reproduction and transmission of TMV in transgenic tobacco was obviously delayed and suppressed (Figure 2A). The amount of TMV-CP was further analyzed to investigate the replication status of the virus by qRT–PCR. The results showed that the concentration of TMV-CP in the WT and N groups could be detected on the 3rd and 5th days, respectively, and consistent with the fluorescence strength, the expression level of TMV-CP in the N group was considerably lower than that in the WT at a significance level of 0.01, indicating that FTX271 could indeed protect tobacco and inhibit the reproduction of TMV (Figure 2B).
To investigate whether defense enzymes are involved in the disease resistance of transgenic tobacco, the activities of four defense-related enzymes, POD, PAL, PPO and chitinase, were detected at different times after p35S-30B-GFP was transformed into tobacco. Although the changing trends were distinguished from each other, some enzyme activities of N-TMV and WT-TMV were always higher than those of the control (WT; Figures 2C–F), indicating that the defense reaction was induced by TMV infection in both transgenic lines and wild type. Although the changing trends of PAL activity, as well as PPO and chitinase, were relatively weak (Figures 2C,D,F), the activity of POD in Groups N-TMV was significantly higher than that in WT-TMV on all days, quickly reached the maximal potency after the 7th day and was nearly 4-fold more potent than the control (Figure 2E). PAL and POD are involved in reactive oxygen species (ROS) catabolism, and they use ROS, including H2O2 and ‧OH, as substrates in redox reactions and preventing oxidative bursts. The POD activity of transgenic tobacco was greatly increased, which may be due to the increase in ROS content in the body, indicating that this time was in the early stage of the defense response (Yu et al., 2004).
Symptoms of mosaic appeared in the WT on the 3rd day after inoculation with p35S-30B-GFP, while the symptoms were still not clear in the N lines on the 5th day. Considering the increase in defense-related enzyme activities starting on the 5th day, leaves of the healthy WT, N and TMV treatment samples on the 7th day were selected for transcriptome sequencing and proteomics analysis. Three tobacco plants in each treatment were used as biological repeats. A total of 567.96 M raw reads were obtained by DNBSeq platform sequencing. After quality control, the clean bases produced an average of 6.39 GB of data, with a Q30 value of more than 92% and a clean read ratio of approximately 90% (Supplementary material Table S2). When the clean reads were compared with the tobacco genome (N. benthamiana) using HISAT, the total mapping ratio was 82.33–85.65% (Supplementary material Table S3). A total of 276,490.0 and 1,256,723.0 secondary spectrograms and 195,372 and 149,357 distinct spectra were obtained by MS in the N, WT, WT-TMV and N-TMV groups. A total of 6750.0 and 6450.0 proteins were identified in this experiment, among which 4752.0 and 4508.0 had quantitative information (Supplementary material Table S4). DEPs were selected with significant changes (p value <0.05), and the cutoff point was fixed at >1.5-fold change (p value <0.05) for increased abundance proteins and < 0.67-fold change (p value <0.05) for reduced abundance proteins. A total of 166 and 26 DEPs were identified, among which 87 and 14 proteins had increased abundance and 79 and 12 proteins had reduced abundance in the N vs. WT and N-TMV vs. WT-TMV, respectively. The target protein FTX271 could be quantified in the transgenic experimental group but not in the WT group.
Values of log2 FC ≥ 1 and Q-value ≤0.01 were used to screen genes with significant differences based on DESEQ2 software. Compared with the healthy WT samples, a total of 953 DEGs were detected in transgenic samples (N), of which 580 were upregulated and 373 were downregulated. The DEGs in the N vs. WT lines were classified by GO and enriched at different GO functional annotation levels, and the top 20 GO terms are shown in Figure 3A. The results indicated that the DEGs mainly affected metabolism and responses, including glucan endo-1,3-β-D-glucosidase activity, β-glucosidase activity, glucosidase activity, response to stimulus, response to stress, defense response, carbohydrate metabolic process, polysaccharide metabolic process, cellular carbohydrate metabolic process, glucan metabolic process, extracellular region, apoplast, etc. To further clarify the molecular and biological functions of these DEGs in the N vs. WT lines, they were mapped to the KEGG database (Q-value ≤0.05; Figure 3B). The results showed that the FTX271 gene significantly affected pathways related to plant immune function, such as plant pathogen interactions, terpenoid biosynthesis and the MAPK signaling pathway. And the important differentially expressed genes in plant disease resistance-related pathways were analyzed. The expression of genes related to plant disease resistance and involved in plant growth was upregulated, indicating that transfection of the FTX271 gene can improve the defense response of tobacco and may have an impact on tobacco growth (Supplementary material Table S5). To further clarify the biological functions of 166 DEPs in the N vs. WT groups. GO annotation results indicated that the differential protein expression caused by transfection of FTX271 is mainly involved in important biological processes, such as plant metabolism and biosynthesis, and has catalytic activity, binding, antioxidant activity and other molecular functions (Figure 4A). The subcellular localization of the differentially expressed proteins was annotated, and the results showed that the differentially expressed proteins were mainly concentrated in the chloroplast, cytoplasm and nucleus, and the upregulated DEPs accounted for a higher proportion in the chloroplast and cytoplasm (Figure 4B). To further understand the biological functions of the DEPs, the annotated differential proteins were subjected to KEGG pathway analysis (Figure 4C), and it was found that the differential proteins were mainly located in the linolenic acid metabolism pathway, isoquinoline alkaloid synthesis, protein export, and tyrosine pathway and in the six signaling pathways of unsaturated fatty acid metabolism and endoplasmic reticulum protein processing. The differential proteins in each signaling pathway were analyzed, and the expression of lipoxygenase (LOX) in the metabolic pathway was upregulated, indicating that FTX271 can promote the expression of LOX (Supplementary material Table S6). When analyzing the significantly upregulated differential proteins, some proteins related to plant immunity, such as enzymes involved in disease resistance, MAPK proteins involved in autoimmunity, PRs that play an important role in the SAR response, and LOX during JA synthesis, were identified (Supplementary material Table S7).
To explore how FTX271 transgenic tobacco resist virus invasion, the N vs. N-TMV and WT-TMV vs. N-TMV groups were analyzed by omics. A total of 5,394 differentially expressed genes were screened in the N vs. N-TMV transcriptome, of which 2,997 were upregulated and 2,397 were downregulated. GO classification and enrichment analyses were performed on the DEGs (Figures 5A,B), and it was found that the DEGs were mainly concentrated in the biological pathways of starch and sucrose metabolism and plant hormone signal transduction. The KEGG pathway enrichment results indicated that the transgenic tobacco infected with TMV mainly affected starch and sugar metabolism and phytohormone and glycolipid biosynthesis (Figure 5C). KEGG pathway enrichment analysis was performed on the upregulated and downregulated genes (Figures 6A,B), and five biological pathways with high enrichment ratios related to plant disease resistance and JA synthesis were found. The related alpha-linolenic acid metabolism and the anabolism of some amino acids were all upregulated, indicating that the upregulated genes mainly affected the defense response of tobacco. A total of 1,441 DEGs were screened in the transcriptomes of the WT-TMV and N-TMV groups, of which 725 genes were upregulated and 716 were downregulated. GO analysis was performed on the DEGs (Figures 5D,E), and the they were mainly concentrated in the biological pathways of starch and sucrose metabolism and plant hormone signal transduction. The KEGG pathway enrichment results of the DEGs indicated that they mainly affected plant pathogen interactions and glucose metabolism (Figure 5F). The enrichment analysis of the upregulated gene KEGG pathway showed that the photosynthesis-related pathways of transgenic tobacco were upregulated (Figure 6C), suggesting that transfection of FTX271 may reduce the damage of TMV to chloroplasts by regulating plant hormones to promote photosynthesis or inhibit the accumulation of TMV. The downregulated gene KEGG pathways were enriched in the downregulated plant–pathogen interaction pathway (Figure 6D), indicating that the defense response of transgenic tobacco infected with TMV was milder. To further clarify the data distribution of the WT-TMV and N-TMV groups, DEPs quantification was represented by a volcano plot (Supplementary material Figure S3A). There were 26 proteins that were significantly differentially expressed, 14 upregulated and 12 downregulated, respectively. Since there were fewer differential proteins quantified by standardized analysis, fewer pathways could be enriched, and the functions of differential proteins could not be accurately identified. Therefore, the GSEA method was used to analyze the differentially expressed proteins. After GSEA, the protein processing pathway in the endoplasmic reticulum (Supplementary material Figure S3B), the upregulated differential proteins were mainly small heat shock proteins (sHSP; Table 1). While sHSP is a defense protein produced by plants under stress, it is speculated that FTX271 can improve the antiviral ability of transgenic tobacco.
To verify the results of up- and downregulation of important DEGs and DEPs in plant disease resistance-related pathways, 10 differentially expressed genes or proteins were selected from the transcriptome or proteome for qRT–PCR analysis to verify the omics results (Supplementary material Figures S4, S5). For genes with obvious differences or related to disease resistance, some specific gene information is shown in Supplementary material Tables S8, S9, and primers are shown in Supplementary material Table S1. The results showed that the upregulation and downregulation were consistent with the sequencing results. To deeply explore the host defense response of FTX271 transgenic tobacco to TMV, qRT–PCR was used to detect the expression of a series of defense genes in N, WT, and N-WT (5 dpi). The expression of defense genes showed that the expression levels of Rar1, PR1, PR2, and PR5 were upregulated in healthy transgenic tobacco compared with wild-type tobacco, indicating that the transfer of FTX271 promoted the expression of defense genes in N. benthamiana and that the expression of defense genes in N. benthamiana was increased during infection (Figure 7). The expression levels of COI1 and LOX2 in healthy transgenics were higher than those in wild-type tobacco (Figures 7H,I), indicating that FTX271 activates systemic resistance through the JA pathway. However, the expression levels of the programmed cell death marker genes H1N1 and HSR203J in the two groups of tobacco infected with TMV increased, indicating that TMV infection induced the HR of plants, causing programmed cell death in local areas, and the virus particles were confined to the infection site and activated system resistance.
The systemic immunity of plants, also known as induced resistance, is divided into SAR and ISR (Vlot et al., 2021). Some exogenous substances can stimulate the induced resistance of plants to protect susceptible plants and reduce the damage caused by susceptible factors. For example, both reticine A and PEVD1 can produce induced resistance in tobacco (Wang et al., 2012, 2021). Our laboratory’s previous in vitro experiments have shown that TDP protein from F. velutipes can inhibit TMV replication and proliferation and induce SAR by the SA-mediated pathway in common tobacco (Han et al., 2022). In addition, compared with wild-type tobacco, FTX271 transgenic tobacco not only relieved mosaic symptoms caused by TMV, but also delayed the time of systemic infection (Wu et al., 2017). Here, we would like to explore whether the antiviral mechanism of FTX271 in transgenic plants is the same as that of TDP in vitro. To explore the effect of the FTX271 gene on tobacco, we obtained transgenic tobacco (N. benthamiana) that can stably express FTX271 through tobacco leaf disc transformation. TDP is the expression product of the FTX271 gene in transgenic tobacco. Proteomic differences between transgenic tobacco and wild-type tobacco were analyzed by KEGG annotation analysis. Differential proteins were enriched in metabolic pathways such as linolenic acid metabolism, unsaturated fatty acid metabolism and endoplasmic reticulum protein processing (Figure 4). Differences in each signaling pathway protein analysis showed that the expression of LOX in the metabolic pathway was upregulated, suggesting that FTX271 could promote the expression of LOX. α-Linolenic acid (α-Lea) is the synthetic precursor of JA, and α-Lea is oxidized by LOX. Upregulation of the linolenic acid metabolism pathway and LOX may lead to an increase in JA content in transgenic tobacco (Ruan et al., 2019). JA, a class of oxygenated lipid derivatives, is a phytohormone necessary for the regulation of plant defense responses (Wasternack and Song, 2017; Ruan et al., 2019). Furthermore, the expression of defense genes measured by qRT–PCR showed that the resistance signal transduction gene Rar1, the key gene COI1 of the JA signaling pathway, and the lipoxygenase gene LOX2 were upregulated, while the key gene NPR1 of the salicylic acid-mediated systemic resistance pathway was downregulated. We infer that the transgenic FTX271 gene induces disease resistance in N. benthamiana through the JA pathway to activate ISR in tobacco; thus, the JA signaling pathway plays a major regulatory role in the transgenic tobacco. Transcriptomic analysis showed that plant hormone signal transduction, the plant Mitogen-activated protein kinase (MAPK) signaling pathway, α-Lea and other metabolic pathways were upregulated after infection with TMV. MAPK cascades play a crucial role in signal transduction in the plant stress response (Lin et al., 2021). Activation of MAPKs also results in multiple defense responses, including defense gene expression and ROS generation (Kroj et al., 2003). The accumulation of ROS acts as a signal to trigger preemptive defense responses, including HR, activating related defense signaling pathways, which can also induce resistance or lead to cell death, depending on the degree of oxidative stress in plants (Apel and Hirt, 2004). HR is a plant defense response triggered by the activation of immune receptors following pathogen recognition (Salguero-Linares and Coll, 2019). Tornero et al. (2002) observed that barley RAR1 is required for full HR and contributes significantly to HR. HIN1, upregulated both during the HR generated by an incompatible plant–pathogen interaction and during senescence, is a marker gene for HR cell death, as well as HSR203J (Pontier et al., 1999; Takahashi et al., 2004). The results of qRT–PCR showed that the expression of these genes was upregulated in transgenic tobacco infected with TMV compared with healthy transgenic tobacco (Figure 7), indicating that HR in transgenic tobacco was activated at this time, causing local resistance (Suleman et al., 2021). A gradual increase in the ROS content would induce an oxidative burst, which may activate the process of senescence. POD is an important oxidoreductase that slows the damage caused by ROS generated during plant HR. The enzymatic activities of the defense enzymes PAL, PPO, POD and chitinase were measured. The results showed that after TMV infection, the POD activity of transgenic tobacco was significantly higher than that of wild-type tobacco, indicating that the plants produced ROS after TMV infection. Studies have shown that after plants are infected with TMV, the formation of disease is related to the destruction of photosynthesis-related proteins by the virus (Hodgson et al., 1989). In transgenic tobacco, KEGG annotation analysis showed that biological pathways such as photosynthetic antenna proteins, steroid biosynthesis, and terpenoid backbone biosynthesis were upregulated, and photosynthesis-related pathways were also upregulated (Figure 6), which are related to photoprotection (Liu et al., 2020), suggesting that transgenic FTX271 may promote photosynthesis by regulating plant hormones, thereby delaying and relieving the symptoms of TMV infection of N. benthamiana. GSEA of TMV-infected transgenic tobacco and wild-type tobacco and protein processing metabolic pathway analysis in the endoplasmic reticulum found that the upregulated differentially expressed proteins were mainly sHSP. Heat shock proteins act as molecular chaperones that promote the natural folding of proteins and prevent irreversible aggregation of denatured proteins during stress (Li et al., 2015). Meanwhile, in TMV-infected transgenic tobacco, proteomics quantified the upregulated expression of class I sHSP and class II sHSP. Overexpression of CP sHSPs in tobacco can enhance the stability of photosystem II under high-temperature stress (Heckathorn et al., 1998). It is speculated that FTX271 can induce the expression of sHSP, and transgenic tobacco infected with TMV may enhance the ability of plants to resist TMV by activating the sHSP pathway to compensate for the damage to photosynthesis caused by TMV. Collectively, TDP expressed in transgenic tobacco acts as an elicitor, activates JA pathway-mediated resistance, enhances the activity of defense enzymes through a signaling cascade, promotes the expression of disease-related proteins, and activates the biosynthesis of hemiterpenoids and triterpenoids so that FTX271 transgenic tobacco acquires resistance before virus infection. After TMV infects plants, it elicits basic immune responses in transgenic tobacco and activates ROS and HR in tobacco. HR and ROS in transgenic tobacco may cause subsequent systemic resistance responses, and the expression of a series of downstream resistance genes is mediated by JA, thereby inhibiting virus replication and transmission in tobacco. In addition, transgenic tobacco may use sHSP-assisted photoreparation to alleviate the symptoms of TMV (Figure 8). Interestingly, in our previous study, we found that spray TDP on leaves could induced SAR to protect tobacco from TMV infection and alleviate the symptoms caused by TMV. The reasons for the different disease resistance pathways caused by transgenic and spraying need further research and analysis. In conclusion, JA-mediated ISR and sHSP-assisted photoreparation are activated by FTX271 to protect tobacco from TMV infection and alleviate the symptoms caused by the virus. The study provided a theoretical basis for the TMV resistance mechanism of FTX271, which may represent a potential gene resource for plant antiviral transgenic breeding.
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: The accession number of the transcriptomic data is SUB11888272 (BioProject database), and the accession number of the proteomics is 1-20220803-135351 (PRIDE database).
YZ conceptualization, methodology, and writing—original draft. CG data curation and software. YZ visualization and formal analysis. YD and HH investigation and data curation. LaW resources, LiW supervision, resources, writing—review and editing. All authors contributed to the manuscript and approved the submitted version.
This study was supported by the National Natural Science Foundation of China (31860525) and Natural Science Foundation of Jiangxi Province (20212BAB205028).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2022.1003478/full#supplementary-material Click here for additional data file. | true | true | true |
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PMC9558407 | Yanyan Wang,Yun-Ling Tai,Grayson Way,Jing Zeng,Derrick Zhao,Lianyong Su,Xixian Jiang,Kaitlyn G. Jackson,Xuan Wang,Emily C. Gurley,Jinze Liu,Jinpeng Liu,Weidong Chen,Xiang-Yang Wang,Arun J. Sanyal,Phillip B. Hylemon,Huiping Zhou | RNA binding protein HuR protects against NAFLD by suppressing long noncoding RNA H19 expression | 12-10-2022 | Bile acids,NASH,Inflammation,Sphingosine kinase,Sphingosine-1 phosphate receptor 2 | Background NAFLD has become the most common chronic liver disease worldwide. Human antigen R (HuR), an RNA-binding protein, is an important post-transcriptional regulator. HuR has been reported as a key player in regulating lipid homeostasis in the liver and adipose tissues by using tissue-specific HuR knockout mice. However, the underlying mechanism by which hepatocyte-specific HuR regulates hepatic lipid metabolism under metabolic stress remains unclear and is the focus of this study. Methods Hepatocyte-specific HuR deficient mice (HuRhKO) and age-/gender-matched control mice, as well as long-noncoding RNA H19 knockout mice (H19−/−), were fed a Western Diet plus sugar water (WDSW). Hepatic lipid accumulation, inflammation and fibrosis were examined by histology, RNA transcriptome analysis, qRT–PCR, and Western blot analysis. Bile acid composition was measured using LC–MS/MS. Results Hepatocyte-specific deletion of HuR not only significantly increased hepatic lipid accumulation by modulating fatty acid synthesis and metabolism but also markedly induced inflammation by increasing immune cell infiltration and neutrophil activation under metabolic stress. In addition, hepatic deficiency of HuR disrupted bile acid homeostasis and enhanced liver fibrosis. Mechanistically, HuR is a repressor of H19 expression. Analysis of a recently published dataset (GSE143358) identified H19 as the top-upregulated gene in liver-specific HuR knockout mice. Similarly, hepatocyte-specific deficiency of HuR dramatically induced the expression of H19 and sphingosine-1 phosphate receptor 2 (S1PR2), but reduced the expression of sphingosine kinase 2 (SphK2). WDSW-induced hepatic lipid accumulation was alleviated in H19−/− mice. Furthermore, the downregulation of H19 alleviated WDSW-induced NAFLD in HuRhKO mice. Conclusions HuR not only functions as an RNA binding protein to modulate post-transcriptional gene expression but also regulates H19 promoter activity. Hepatic HuR is an important regulator of hepatic lipid metabolism via modulating H19 expression. Supplementary Information The online version contains supplementary material available at 10.1186/s13578-022-00910-7. | RNA binding protein HuR protects against NAFLD by suppressing long noncoding RNA H19 expression
NAFLD has become the most common chronic liver disease worldwide. Human antigen R (HuR), an RNA-binding protein, is an important post-transcriptional regulator. HuR has been reported as a key player in regulating lipid homeostasis in the liver and adipose tissues by using tissue-specific HuR knockout mice. However, the underlying mechanism by which hepatocyte-specific HuR regulates hepatic lipid metabolism under metabolic stress remains unclear and is the focus of this study.
Hepatocyte-specific HuR deficient mice (HuRhKO) and age-/gender-matched control mice, as well as long-noncoding RNA H19 knockout mice (H19−/−), were fed a Western Diet plus sugar water (WDSW). Hepatic lipid accumulation, inflammation and fibrosis were examined by histology, RNA transcriptome analysis, qRT–PCR, and Western blot analysis. Bile acid composition was measured using LC–MS/MS.
Hepatocyte-specific deletion of HuR not only significantly increased hepatic lipid accumulation by modulating fatty acid synthesis and metabolism but also markedly induced inflammation by increasing immune cell infiltration and neutrophil activation under metabolic stress. In addition, hepatic deficiency of HuR disrupted bile acid homeostasis and enhanced liver fibrosis. Mechanistically, HuR is a repressor of H19 expression. Analysis of a recently published dataset (GSE143358) identified H19 as the top-upregulated gene in liver-specific HuR knockout mice. Similarly, hepatocyte-specific deficiency of HuR dramatically induced the expression of H19 and sphingosine-1 phosphate receptor 2 (S1PR2), but reduced the expression of sphingosine kinase 2 (SphK2). WDSW-induced hepatic lipid accumulation was alleviated in H19−/− mice. Furthermore, the downregulation of H19 alleviated WDSW-induced NAFLD in HuRhKO mice.
HuR not only functions as an RNA binding protein to modulate post-transcriptional gene expression but also regulates H19 promoter activity. Hepatic HuR is an important regulator of hepatic lipid metabolism via modulating H19 expression.
The online version contains supplementary material available at 10.1186/s13578-022-00910-7.
Nonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases that affect more than 25% of the adult population globally, imposing a substantial social and economic burden [1]. NAFLD refers to a broad spectrum of histological conditions, from simple hepatic steatosis (NAFL) to nonalcoholic steatohepatitis (NASH). Moreover, about 10–25% of NAFLD patients will develop NASH, which is now a leading cause of progression to advanced fibrosis, cirrhosis, and hepatocellular carcinoma (HCC) [2]. Furthermore, NASH–HCC is the second leading cause of liver transplantation related to HCC in the United States [3, 4]. Over the last several decades, considerable efforts have been made to identify the potential molecular mechanisms underlying NAFLD progression. In addition to demographic and genetic factors, obesity, diabetes, and cardiovascular diseases are also closely associated with NASH–HCC [5, 6]. However, the pathogenesis of NAFLD remains incompletely understood, and no effective treatment is available. It has been well accepted that the progression of NAFLD is driven by multiple factors, such as dysregulation of hepatic lipid and bile acid metabolism, activation of inflammatory pathways and endoplasmic reticulum (ER) stress response, as well as dysbiosis of the gut microbiome [2, 7]. We and others have previously reported that sphingosine-1 phosphate receptor 2 (S1PR2) and sphingosine kinase 2 (SphK2) are important regulators of hepatic lipid metabolism [8–10]. It also has been reported that long noncoding RNA (lncRNA) H19, an imprinted and maternally expressed gene, is an important regulator in cholestatic liver fibrosis, inflammation, and hepatic lipid metabolism [11–14]. The aberrant expression of H19 is associated with liver fibrosis in HCC patients [15]. Human antigen R (HuR), also known as HuA and embryonic lethal abnormal vision-like 1 (ELAVL1), functions to regulate the expression of coding and noncoding RNAs by post-transcriptional mechanisms [16, 17]. Global HuR-knockout mice exhibited embryonic lethality due to extra-embryonic placental defects [18]. Recently, the importance of HuR-mediated roles in cell signaling, inflammation, fibrogenesis, and cancer development in the liver has attracted a great deal of attention [19]. Several studies have reported that hepatic HuR protects against NAFLD by targeting lipid and glucose metabolism, regulating lipid transport, and inhibiting adipogenesis [20–22]. A recent study reported that HuR is a gatekeeper of liver homeostasis and liver-specific deletion of HuR accelerated NASH fibrosis and HCC [20]. However, the hepatocyte-specific roles of HuR in NAFLD pathogenesis have not been fully explored, and the underlying mechanisms remain largely unclear. In the present study, hepatocyte-specific HuR knockout (HuRhKO) mice were generated to evaluate the role of HuR in regulating hepatic lipid metabolism using a Western diet plus sugar water (WDSW)-induced NAFLD mouse model. The current study shows that HuRhKO mice exacerbate the progression of WDSW-induced NAFLD as indicated by enhanced liver steatosis, inflammation, and fibrosis. Mechanistically, hepatocyte-specific HuR deficiency upregulated the expression of H19, which promoted inflammation and hepatic lipid accumulation. In addition, hepatocyte-specific HuR deficiency disrupted bile acids homeostasis. These results suggested that hepatocyte HuR may be a potential therapeutic target for NAFLD.
Although two recent studies have reported the hepatic-specific role of HuR modulating lipid metabolism in mouse NAFLD models, both studies used liver-specific HuR knockout mice by cross-breeding a HuRflox/flox mouse with albumin-Cre mice, not hepatocyte-specific knockout mice [20, 22]. To delineate the hepatocyte-specific role of HuR in the NAFLD disease progression, HuRhKO mice were generated by tail-vein injection of HuRflox/flox mice with AAV8-TBGP-Cre recombinase and AAV8-TBGP-GFP was used as a control. HuRhKO and control mice were fed ad libitum a WDSW for 4 weeks. As shown in Additional file 1: Fig.S1a–c, the HuR mRNA and protein levels were significantly reduced in the liver of HuRhKO mice. Immunofluorescence staining further confirmed the deletion of HuR in hepatocytes (Additional file 1: Fig. S1d). As shown in Fig. 1a, b, hepatocyte-specific deletion of HuR exacerbated WDSW-induced hepatic lipid accumulation and liver injury following 4-week feeding as indicated by increased lipid accumulation (H&E and Oil Red O staining), and increased serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels. Although the liver index (ratio of liver/body weight), serum cholesterol, triglycerides, glucose, and alkaline phosphatase (ALP) levels were not significantly altered (Additional file 1: Fig. S1e–g), hepatic levels of triglycerides and cholesterol in HuRhKO mice were much higher than those in control mice (Fig. 1c). However, no significant change was noticed in the serum ALT and AST in HuRhKO and control mice under a normal diet (Additional file 1: Fig. S1h, i), which was consistent with the H&E staining (Additional file 1: Fig. S1j). Previous studies have reported that NALFD disease severity is associated with specific changes in circulating bile acids in human NASH patients and mouse NASH models. Serum taurocholic acid (TCA) level is significantly increased in NASH patients [23, 24]. To examine whether the serum bile acid profile was changed in HuRhKO mice after 4-week WDSW feeding, serum bile acid composition and levels were measured using LC–MS/MS [24]. As shown in Fig. 1d, the percentage of TCA in total bile acids was significantly increased from 10% (Control) to 23% (HuRhKO), while βMCA was significantly decreased from 26% (Control) to 15% (HuRhKO) after 4-week WDSW feeding. Total serum bile acid levels were significantly increased in HuRhKO mice; including, total primary, secondary, and conjugated bile acids (Fig. 1e and Additional file 1: Table S2). In addition, serum levels of TCA, TβMCA, TCDCA, TωMCA, and THDCA in HuRhKO mice were much higher than those in control mice (Additional file 1: Table S3).
To illustrate the underlying mechanisms by which hepatic HuR deficiency-induced NAFLD disease progression, we performed RNA-seq transcriptome analysis. As shown in Fig. 2a, b, WDSW-feeding induced the upregulation of 192 genes and down-regulation of 160 genes in HuRhKO mice compared to the control mice. Gene Ontology analysis showed that WDSW-feeding significantly impacted the major pathways in biological process (BP), cellular component (CC), and molecular function (MF) related to metabolic processes and immunological responses (Additional file 1: Fig. S2a–c) in HuRhKO mice compared to the control mice, including cholesterol metabolic process, biosynthetic process, inflammatory response, extracellular exosome, lipoprotein, extracellular matrix, oxidoreductase activity, fatty acid-binding, etc. Furthermore, KEGG pathways analysis showed that metabolic pathways, including steroid hormone biosynthesis and inflammatory response, were dysregulated in HuRhKO mice (Additional file 1: Fig. S2d).
Dysregulation of lipid metabolism contributes to the development of NAFLD [25]. As shown in Fig. 2c, most of the genes involved in the fatty acid biosynthesis pathway were increased in HuRhKO mice compared to the control mice after 4 weeks of WDSW feeding; including acetyl CoA carboxylase (Acc1), fatty acid synthase (Fasn), elongation of very-long-chain fatty acids member 6 (Elovl6), fatty acid desaturases (Fads1&2), liver X receptor (Lxrα&β), peroxisome proliferator-activated receptor (Pparα&β), carnitine palmitoyltransferase 1 (Cpt1α), patatin-like phospholipase domain containing (Pnpla3), and adipose triglyceride lipase (Atgl, also known as Pnpla2), etc. The mRNA expression levels of key genes involved in hepatic lipid metabolism were further confirmed by real-time RT–PCR. As shown in Fig. 2d, the mRNA levels of Acc1, Fasn, Elovl6, Fads1, Fads2, Lxrα, Lxrβ, Pparα, Pparβ, Cpt1α, Pnpla3, and Atgl were significantly increased in HuRhKO mice compared to the control mice after 4-weeks of WDSW feeding.
Inflammation and stress response are important driving forces in promoting NAFL to NASH progression [26–28]. RNA-seq analysis showed that the key genes involved in inflammatory and stress responses, such as F4/80, Cd68, Cd63, C-X-C Motif Chemokine Ligand 1 (Cxcl1), Cxcl10, chemokine ligand 2 (Ccl2), C–C chemokine receptor type 2 (Ccr2), Caspase 3, Activating transcription factor 4 (Atf4), interleukin 1α (IL-1α), were significantly increased in HuRhKO mice fed with a WDSW for 4 weeks (Additional file 1: Fig. S3a). Hepatocyte-specific deletion of HuR promoted WDSW-induced macrophage infiltration to the liver as indicated by the IHC staining of F4/80 antigen; a mature cell surface glycoprotein expressed at high levels on various macrophages (Fig. 3a). Real-time PCR results further showed that the mRNA expression levels of major marker genes of macrophages, inflammatory cytokines and chemokines, such as F4/80, Cd68, Cd63, Integrin alpha M (also known as Cd11b) (Fig. 3b), Cxcl1, Cxcl10, Ccl2, Ccr2, IL-1α, IL-1β, tumor necrosis factor α (Tnfα), and IL-6, were significantly increased (Fig. 3c). Neutrophils, the most abundant leukocytes in circulation, play a vital role in innate immunity [29]. However, inappropriate activation of neutrophils can cause tissue damage, which has been involved in different diseases, including various liver diseases [30, 31]. Our recent study reported that in the WDSW-induced NASH mouse model, the expression levels of major genes involved in neutrophil activation were significantly upregulated in the liver [24]. As shown in Additional file 1: Fig. S3b, the key genes involved in neutrophil activation, such as NADPH oxidase 2 [Nox2, also known as neutrophil cytochrome b heavy chain (Cybβ), or p91phox], neutrophil cytosolic factor 2 (Ncf2, also known as p67phox), Ncf4 (also known as p40phox), Cybα (also known as p22phox), IL-2 receptor gamma unit (IL2rg), intercellular adhesion molecule 1 (ICAM1) and vascular cell adhesion molecule 1 (vcam1), were significantly upregulated in the liver of WDSW-fed HuRhKO mice. The upregulation of mRNA levels was further confirmed by real-time RT–PCR (Fig. 3d). Pathway analysis further showed that oxidative phosphorylation in mitochondria and MAPK signaling pathways were significantly dysregulated in WDSW-fed HuRhKO mice compared to control mice (Additional file 1: Fig.S4 and S5).
We and others have previously reported that aberrant expression of lncRNA H19 is closely associated with hepatic inflammation and liver fibrosis in various liver diseases, including NASH [12–14]. To further identify the potential underlying mechanisms by which hepatic deletion of HuR promotes NAFLD progression, we examined H19 expression in the livers of human NASH patients and WDSW-induced NASH mouse models. As shown in Fig. 4a, hepatic H19 mRNA levels were increased more than tenfold in human NASH patients compared to healthy controls. Similarly, in NASH mice fed WDSW for 21 weeks, hepatic H19 mRNA levels were increased more than 30-fold compared to control mice (Fig. 4b). Analysis of the publically available RNAseq data set from a most recent study (GSE143358) showed that H19 is the most significantly upregulated gene in liver-specific HuR knockout mice (Fig. 4c) [20]. In a newly developed preclinical NASH–HCC model with C57/BL6NJ mice, H19 is in the top ten upregulated genes (GSE197884) (Fig. 4c) [32]. We also found that H19 was significantly upregulated in the liver of HuRhKO mice fed with WDSW for 4 weeks (Fig. 4d). To identify the mechanism underlying HuR deficiency-induced H19 expression, a luciferase reporter assay with a human H19 promoter was performed to examine the impact of HuR on H19 transcriptional activity. As shown in Fig. 4e, overexpression of HuR significantly inhibited H19 promoter activity. To further determine the role of H19 in hepatic steatosis and inflammation in vivo, H19−/− mice and gender and age-matched WT mice were fed a WDSW for 4 weeks. As shown in Fig. 4f, H&E and Oil red O staining indicated that H19−/− mice were protected from WDSW-induced hepatic lipid accumulation.
Previous studies have reported that SphK2, a key enzyme in sphingolipid catabolism, plays a critical role in regulating hepatic lipid metabolism [8–10]. Global SphK2 deficient (SphK2−/−) mice developed overt fatty liver compared to the control mice on a two-week high-fat diet [10]. SphK2 is primarily located in the cell nucleus. As shown in Fig. 5a, the nuclear protein levels of SphK2 were significantly decreased in the livers of WDSW-fed HuRhKO mice compared to control mice. Deletion of H19 increased SphK2 nuclear protein level (Fig. 5b). However, neither hepatocyte HuR deficiency nor deletion of H19 significantly altered the total protein levels of SphK2 in the livers (Additional file 1: Fig. S6a, b). Our previous studies also reported that S1PR2 deficiency significantly reduced cholestasis-induced cholangiocyte proliferation and liver injury [33]. As shown in Fig. 5c, d, S1PR2 mRNA levels were significantly upregulated in the livers of human NASH patients and the WDSW-induced NASH mouse model. Similarly, both mRNA and protein levels of S1PR2 were significantly increased in WDSW-fed HuRhKO mice. To further elucidate the potential role of S1PR2 in HuR deficiency-induced metabolic liver injury, we examined the effect of overexpression of S1PR2 on H19 promoter activity using the luciferase report assay. As shown in Fig. 5e, S1PR2 significantly enhanced H19 promoter activity.
Bile acids are critical in regulating hepatic lipid, glucose, and energy metabolism as they are important signaling molecules [24, 34, 35]. LC–MS/MS analysis of serum bile acid levels indicated that hepatocyte-specific HuR deficiency aggravated WDSW-induced disruption of bile acid homeostasis (Fig. 1d, e, Additional file 1: Table S2 and S3). Real-time PCR analysis showed that the expression levels of two rate-limiting enzymes in the bile acid synthesis pathway, cholesterol 7 alpha-hydroxylase (Cyp7α1) and cholesterol 27 alpha-hydroxylase (Cyp27α1), were significantly decreased. In contrast, the expression levels of small heterodimer partner (Shp) and Na + -taurocholate cotransporting polypeptide (Ntcp) were significantly upregulated in the livers of WDSW-fed HuRhKO (Fig. 6a). To further determine the impact of hepatocyte-specific deletion of HuR on enterohepatic circulation, the bile acid composition and levels in the liver, intestinal ileum, and cecal contents were measured using LC–MS/MS. As shown in Fig. 6b, the percentage of TCA in total hepatic bile acids was increased from 27% (Control) to 40% (HuRhKO), while βMCA was decreased from 39% (Control) to 24% (HuRhKO). Although the total liver bile acids showed no significant changes between the WDSW-fed HuRhKO mice and control mice, the TCA level, the ratio of total primary conjugated bile acids to total primary unconjugated bile acids, the ratio of total conjugated bile acids to total unconjugated bile acids, and the ratio of total secondary conjugated bile acids to total secondary unconjugated bile acids were increased in HuRhKO mice (Fig. 6c, Additional file 1: Table S4 and S5). Moreover, it should be noted that TCA has been shown to be a potent activator of S1PR2 [36]. In the intestinal ileum, as shown in Additional file 1: Fig. S7a, the percentage of TCA in total bile acids was increased from 27% (Control) to 35% (HuRhKO). Hepatocyte HuR deficiency had no significant effect on intestinal total bile acids, the ratio of total primary conjugated bile acids to total primary unconjugated bile acids, and the ratio of total conjugated bile acids to total unconjugated bile acids in the intestine (Additional file 1: Fig. S7b and Additional file 1: Table S6, S7). However, hepatocyte HuR deficiency significantly reduced bile acid levels, including total bile acids, total unconjugated bile acids, total primary bile acids, and total secondary bile acids in the cecal contents (Fig. 6d, Additional file 1: Fig. S7c, d, and Additional file 1: Tables S8, S9). Under normal diet feeding conditions, the deletion of HuR in hepatocytes significantly changed bile acid levels and composition in the serum. As shown in Additional file 1: Fig. S8a, the percentages of TCA and TβMCA in total bile acids increased from 14 to 63% and 3% to 20%, respectively, in normal diet fed HuRhko mice. While the percentage of βMCA decreased from 25 to 1%. The total bile acid level and ratios of total primary bile acid to total bile acid and total primary bile acid to total secondary bile acids were also increased in the serum of normal diet-fed HuRhko mice (Additional file 1: Tables S10, S11). There were no significant changes in hepatic bile acid level and composition in normal diet-fed HuRhko mice (Additional file 1: Fig. S8b, Tables S12, S13). However, the total bile acid levels in the intestine and cecal contents were reduced, although the bile acid composition was not significantly changed in normal diet-fed HuRhko mice (Additional file 1: Tables S14–17; Fig. S9).
To further examine the impact of hepatic HuR in WDSW-induced NAFLD disease progression, both control and HuRhKO mice were fed ad libitum a WDSW for 12 weeks to induce NASH and early fibrosis. As shown in Additional file 1: Fig. S10a, HuR protein levels were significantly downregulated in the livers of HuRhKO mice. As expected, H&E staining showed that HuRhKO mice fed WDSW for 12 weeks exacerbated intra-acinar (lobular) inflammation, hepatocellular ballooning, and macrovesicular steatosis (Fig. 7a). Similar to the 4-week WDSW feeding study in HuRhKO mice (Fig. 4d), the hepatic H19 expression level was significantly upregulated in 12-week WDSW-feeding HuRhKO mice (Fig. 7b). The key genes involved in the fatty acid synthesis and lipid metabolism were also increased in HuRhKO mice compared to the control mice, including sterol regulatory element-binding protein 2 (Srebp2), Pparα, elovl fatty acid elongase 7 (Elovl7), 3-hydroxy-3-methylglutaryl coenzyme-A (HMG-CoA) reductase (HMG-CoAR), PPARG Coactivator 1 Alpha (Pgc1α), lipoprotein lipase (Lpl), fibroblast growth factor 21 (Fgf21), fatty acid desaturase (Fads2), and Cyclin D1 (Additional file 1: Fig. S10b). As shown in Fig. 7c, HuRhKO mice fed WDSW for 12 weeks resulted in enhanced macrophage infiltration to the liver, as indicated by IHC staining of F4/80. In addition, the mRNA levels of F4/80, Cd11b, Cd63, Cd68, Ccl2, Ccr2, Tnfα, Cd14, Tlr4, ceramide kinase (Cerk), Caspase 1, and cyclooxygenase 2 (Cox-2) were significantly increased in the liver of HuRhKO mice (Additional file 1: Fig. S11a). Furthermore, as shown in Additional file 1: Fig. S11b, the expression levels of key genes involved in neutrophil activation were also significantly upregulated in the liver of HuRhKO mice fed WDSW for 12 weeks, including Nox2, neutrophil cytosolic factor 1 (Ncf1), Ncf2, Ncf4, Cybα, Il2rg, Elastin, and Selectin. These findings were consistent with the results in HuRhKO mice fed WDSW for 4 weeks, indicating hepatocyte-specific HuR deficiency enhances WDSW-induced dysregulation of hepatic lipid metabolism and activation of inflammatory response. Hepatic cell injury and inflammation are the major driving forces of hepatic fibrosis, which is closely associated with mortality in NASH patients [37]. To determine the impact of hepatic HuR on the progression of NASH fibrosis, we performed Picro Sirus Red staining, IHC staining of CK-19 and real-time PCR analysis. As shown in Fig. 7c, 12-week WDSW-feeding induced early fibrosis in HuRhKO mice but much less in control mice. CK-19 staining indicated that hepatocyte-specific HuR deficiency significantly exacerbated WDSW-induced cholangiocyte proliferation. The mRNA expression levels of fibrotic genes were significantly upregulated in 12-week WDSW-feeding HuRhKO mice, including Ck19, smooth muscle actin (α-Sma), transforming growth factor-beta 1 (Tgfβ1), lysyl oxidase-like 2 (Loxl2), SRY (sex-determining region Y)-box 4&9 (Sox4&9), connective tissue growth factor (Ctgf), matrix metallopeptidase 2 and 7 (Mmp2&7), secretin receptor (Sctr), periostin (Postn), and S1pr2, indicating hepatocyte-specific HuR deficiency aggravates WDSW-induced hepatic fibrosis (Fig. 7d).
Based on our results and published RNAseq data, H19 upregulation may represent a major cellular mechanism underlying WDSW-induced NAFLD in HuRhKO mice. To verify the role of H19 in WDSW-induced NAFLD in HuRhKO mice, HuRhKO mice were injected with a recombinant adenovirus encoding an H19 shRNA or control adenovirus (GFP) while being fed ad libitum a WDSW for 4 weeks. As shown in Fig. 8a, the H19 levels in the liver were significantly decreased after injection of adenovirus of H19 shRNA compared to injection of control adenovirus. Down-regulation of H19 reversed the WDSW-induced decrease of nuclear SphK2 protein (Fig. 8b). H&E staining showed that downregulation of H19 in HuRhKO mice reduced WDSW-induced intra-acinar (lobular) inflammation, hepatocellular ballooning, and macrovesicular steatosis (Fig. 8c). The Picro-Sirius Red staining also showed that downregulation of H19 in HuRhKO mice reduced WDSW-induced early fibrosis (Fig. 8d). Together, these results suggest that the upregulation of H19, at least partially, contributes to WDSW-induced NAFLD development in HuRhKO mice.
The prevalence of NAFLD has been continuously increasing during the last decade globally due to obesity. Recently, there has been compelling evidence supporting the “Multi-hit” over the “Two-hit” hypothesis of NAFLD pathogenesis [2, 38–40]. In addition to the dysregulation of hepatic lipid metabolism, the progression from NAFL to NASH is correlated with systemic and adipose tissue inflammation, individual genetic and epigenetic factors, complex environmental factors, dysbiosis and disruption of bile acids homeostasis [2, 40]. Histologically, NASH is characterized by steatosis, inflammation, hepatocyte injury (ballooning), and/or fibrosis [40]. Emerging evidence has demonstrated the involvement of HuR in the pathogenesis of various liver diseases, including fatty liver diseases, hepatic inflammation, viral hepatitis, liver fibrosis, and liver cancers [20–22, 41]. In the present study, we demonstrated that in HuRhKO mice, lack of HuR in hepatocytes exacerbated the progression of WDSW-induced NAFLD as indicated by enhanced liver steatosis, inflammation, and fibrosis, consistent with the findings in the recent studies [20]. Using RNA transcriptome analysis combined with histological examination, we found that hepatocyte-specific HuR deficiency upregulated the expression of H19 and S1PR2 (Figs. 4, 5). Our current study also discovered that hepatocyte-specific HuR deficiency significantly disrupted bile acid homeostasis. Two studies reported that HuR played a critical role in modulating lipid homeostasis in response to metabolic stress using liver-specific HuR knockout mice [20, 41]. In the study by Zhang et al. no significant change was noticed in hepatic lipid accumulation and liver function under a chow diet [41]. However, the recent study by Subramanian, P. et al. showed significant hepatic lipid accumulation in liver-specific HuR knockout mice under normal diet feeding [20]. Since studies did not specify the gender and age of the mice, the discrepancy could be due to the gender and age difference or other environmental factors. In our HuRhKO mice, we did not observe a significant change in hepatic lipid accumulation under a normal diet condition (Additional file 1: Fig.S1j). Hepatic lipid accumulation is associated with dysregulated fatty acid biosynthesis and lipid metabolism [42]. The results of the current study showed that the essential genes involved in fatty acid biosynthesis were significantly increased in the liver of HuRhKO mice fed WDSW for 4 or 12 weeks (Fig. 2 and Additional file 1: Fig. S10). Inflammation and oxidative stress are important drivers for NAFLD disease progression [27, 43, 44]. Our data showed that hepatocyte-specific deficiency of HuR significantly increased the expression of macrophage markers, various chemokines, innate immune responses markers, and chemokines in the livers of HuRhKO mice (Fig. 3 and Additional file 1: Fig. S11a). The activation of neutrophils contributes to NAFLD/NASH progression [45, 46]. We have previously reported that neutrophils were activated in a WDSW-induced NASH mouse model [24]. Consistently, RNA-seq data and real-time RT–PCR results indicated that hepatocyte-specific deficiency of HuR was able to exacerbate WDSW-induced activation of neutrophils (Fig. 3d and Additional file 1: Fig. S3b and S11b). Hepatic fibrosis is a vital marker during the progression from NAFL to NASH. The results of our current study demonstrated that hepatic deficiency of HuR also induced early hepatic fibrosis by modulating key genes involved in hepatic stellate cell activation and cholangiocyte proliferation after a WDSW feeding for 12 weeks (Fig. 7c, d). In contrast, a previous study reported that HuR is upregulated in the liver of human cirrhotic patients and BDL mouse models. HuR silencing using siRNA had beneficial functions during BDL-induced cholestatic liver injury and HSC activation [47]. However, the cell-type-specific role of HuR in this study remains unclear. Based on our current data, it is clear that HuR may play a protective role in hepatocytes in the progression of NAFL to NASH. Consistent with this hypothesis, we found that HuR protein level was significantly reduced in NASH–HCC patients (Additional file 1: Fig. S12a, b). H19 is the first lncRNA identified and characterized as the first imprinted gene in eukaryotes as a hepatic fetal-specific non-translatable mRNA in the late 1980s and has been implicated in various liver diseases [12]. We have previously reported that H19 promoted hepatic stellate cell activation and cholestatic liver fibrosis [13, 14]. The current studies showed that H19 was highly expressed in human NASH patients and NASH mouse models (Figs. 4a, b). We also found that hepatic H19 level was significantly upregulated in HuRhKO mice fed-WDSW for 4 or 12 weeks (Figs. 4d and 7b). Interestingly, in a recent study with liver specific HuR knockout mice, H19 is the most significantly upregulated gene (Fig. 4c, GSE143358). Similarly, in a new NASH–HCC mouse model, H19 ranked the top ninth among significantly upregulated genes (Fig. 4c, GSE197884). We further showed that HuR inhibited H19 transcription by suppressing the H19 promoter activity (Fig. 4e). Although HuR has been extensively studied as an RNA-binding protein, it has been reported that many RNA-binding proteins, including HuR, can function as transcription factors [48]. Furthermore, H19 deficiency protected mice from WDSW-induced NAFLD (Fig. 4f); and downregulation of H19 in HuRhKO mice significantly reduced WDSW-induced hepatic lipid accumulation, inflammation and liver fibrosis (Fig. 8c, d). We and others have previously reported that SphK2 is an important regulator of hepatic lipid metabolism and ER stress [9, 10]. Consistently, in the current study, we also found that the nuclear SphK2 levels were dramatically decreased in the liver of WDSW-induced HuRhKO mice but increased in WDSW-induced H19−/− mice (Fig. 5a, b). However, neither HuR nor H19 had significant effects on the total protein level of SphK2 (Additional file 1, Fig.S6). The results indicated that HuR or H19 might regulate the translocation of SphK2 from the cytosol into the nucleus. Consistently, downregulation of H19 using an H19 shRNA in HuRhKO mice increased the nuclear protein level of SphK2 in the liver (Fig. 8b). Bile acids are important signaling molecules in regulating hepatic lipid metabolism, inflammation, and fibrotic response. Altered circulating bile acid composition is associated with the severity of NASH [23]. Increased hepatic/serum conjugated primary bile acids may be an important factor in cholestatic liver injury and liver fibrosis by activating S1PR2 and H19 [13, 33]. Consistent with the previous studies, total conjugated primary bile acids were significantly increased in the serum of WDSW-fed HuRhKO mice, together with the increased total bile acids and TCA (Fig. 1d, e, Additional file 1: Table S2-3). In addition, the current study showed that hepatic deficiency of HuR disrupted bile acid homeostasis by modulating key enzymes of bile acid synthesis, nuclear receptors, and hepatic bile acid transporters (Fig. 6a). Interestingly, the β-MCA level was significantly decreased in the serum and liver of WDSW-fed HuRhKO mice (Fig. 1d and 6b). This may be caused by the down-regulation of Cyp2c70 (Additional file 1: Fig. S12c), which catalyzes the conversion of CDCA into αMCA and possible reduction of gut microbiome-mediated epimerization of 7α-MCA into 7β-MCA [49]. In addition, hepatocyte-specific deficiency of HuR induced dysregulation of intrahepatic bile acid homeostasis under both normal diet and WDSW feeding conditions (Fig. 6b–d and Additional file 1: Figs.S7–S9, and Additional file 1: Tables S4–S17). These findings provided strong evidence for a protective role of hepatocyte-specific HuR in NAFLD progression by modulating enterohepatic bile acid circulation. We have previously reported that TCA-induced activation of S1PR2 promotes cholestatic liver injury [33]. In the current study, we also found that S1PR2 expression was upregulated in the livers of human NASH patients and NASH mice (Fig. 5c). Importantly, we found both mRNA and protein levels of S1PR2 were upregulated in HuRhKO mice (Fig. 5c, d). Moreover, S1PR2 overexpression enhanced H19 transcription by increasing the H19 promoter activity (Fig. 5e). Since S1PR2 is a cell membrane GPCR, its effect on the H19 promoter is likely mediated by its downstream signaling molecules via activation of ERK1/2. Although the current study showed that S1PR2 expression was increased in HuRhKO mice fed with WDSW, the luciferase reporter assay indicated that HuR had no direct effect on S1PR2 expression (Data not shown). Our previous studies showed that conjugated bile acids activate ERK via the S1PR2, resulting in the activation of nuclear SphK2 [10, 36]. Activation of SphK2 ameliorates metabolic stress-induced hepatic lipid accumulation [9]. In HuRhKO mice, upregulation of H19 reduced SphK2 nuclear translocation under WDSW feeding condition.
In summary, as illustrated in Fig. 8e, the current study has demonstrated that HuR functions as an important regulator of hepatic lipid metabolism, enterohepatic bile acid homeostasis, inflammation, and fibrosis by suppressing H19 expression and modulating SphK2 nuclear protein level. Bile acid-induced activation of S1PR2 may also contribute to NASH fibrosis via upregulating H19. In addition, the phosphorylation status of HuR impacts its intracellular localization. It has been reported that ERK-mediated phosphorylation of HuR increases cytosolic HuR levels and reduces nuclear HuR [50, 51]. Hepatocyte-specific modulation of HuR expression and its downstream target, H19, may be used to develop potential therapeutic targets for NAFLD.
Both male and female mice were used for all in vivo studies. HuRflox/flox mice (C57BL/6 J) were from the Jackson Laboratory (Bar Harbor, ME). Hepatocyte-specific HuR knockout (HuRhKO) mice were generated by tail-vein injection of HuRflox/flox mice with AAV8-thyroxine-binding globulin promoter (TBGP)-Cre recombinase from Addgene (Watertown, MA). Control mice were injected with the same amount of AAV8-TBGP-GFP from Vector Biolabs (Malvern, PA). Age and gender-matched HuRhKO and control mice were fed ad libitum a Western diet, with 42% kcal from fat and containing 0.1% cholesterol from Envigo (Cat#: TD.88137, Indianapolis, IN) with a high fructose-glucose solution (23.1 g/L d-fructose + 18.9 g/L d-glucose) (Western diet plus sugar water, WDSW) for 4 weeks or 12 weeks. Age and gender-matched H19 knockout (H19−/−) (the maternal H19ΔExon1/ + mice with C57BL/6 J background generated by Dr. Karl Pfeifer at NIH and provided by Dr. Jian-Ying Wang at the University of Maryland (Baltimore, MD, USA) and WT mice were fed ad libitum a WDSW for 4 weeks. An adenovirus expressing H19 shRNA (A gift from Dr. Li Wang, The Institute for Systems Genomics at the University of Connecticut) was used to knock down H19 expression in HuRhKO mice via tail-vein injection and adenovirus of GFP was used as a control. All mice were housed in a 12 h light/12 h dark cycle with a controlled room temperature between 21 and 23 °C and free access to water. All animal experiments were performed following institutional guidelines for ethical animal studies and approved by the VCU Institutional Animal Care and Use Committee. At the end of the experiment, mice were weighed and anesthetized by exposure to inhaled isoflurane. Blood was collected by cardiac puncture. The serum was collected and stored at − 80 °C for later analysis. After euthanasia, the liver was collected for histological analysis, RNA profiling, and Western blot analysis.
HEK-293 cells with a density of 75% were inoculated into 24-well plates at a density of 2 × 105 cells per well and cultured for 24 h. The cells were transfected with pGL3-human H19-promoter (a gift from Dr. Xiaodi Tan at Northwestern University (Chicago, IL) or pGL3-control vector together with pcDNA3-TAP-human HuR or pcDNA3-TAP vector (gifts from Dr. Jian-Ying Wang at University of Maryland) along with Renilla control vector, pGL4.76-hRluc/Hygro from Promega (Madison, WI) using PolyJet from SignaGen Laboratories (Frederick MD) according to the manufacturer's instructions (n = 6). After 48 h, the cells were washed with PBS, and the cell lysates were collected for firefly and Renilla luciferase activity assays using a dual-luciferase reporter assay kit (E1910) from Promega (Madison, WI). The promoter activity was expressed using the ratio of firefly luciferase activity to Renilla luciferase activity.
Frozen human liver tissues (Healthy and NASH patients, both male and female) were obtained through the Liver Tissue Cell Distribution System (Minneapolis, MN), funded by the National Institutes of Health (Contract# HSN276201200017C).
Data are expressed as the mean ± SEM from at least three independent experiments. The student's t-test was used to analyze the difference between the two groups by GraphPad Prism (version 8; GraphPad Software Inc., San Diego, CA). p ≤ 0.05 was considered statistically significant.
Additional file 1: Additional methods, Supplementary figures, Supplementary tables, and raw image files. The accession number for the raw data FASTQ and processed data file deposit in NCBI is GEO: GSE231215. | true | true | true |
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PMC9558416 | Yufei Long,Tuotuo Chong,Xiaoming Lyu,Lujia Chen,Xiaomin Luo,Oluwasijibomi Damola Faleti,Simin Deng,Fei Wang,Mingliang He,Zhipeng Qian,Hongli Zhao,Wenyan Zhou,Xia Guo,Ceshi Chen,Xin Li | FOXD1-dependent RalA-ANXA2-Src complex promotes CTC formation in breast cancer | 13-10-2022 | Breast cancer,Circulating tumor cells,FOXD1,RalA-ANXA2-Src complex,ERK1/2 inhibitor | Background Early metastasis is a key factor contributing to poor breast cancer (BC) prognosis. Circulating tumor cells (CTCs) are regarded as the precursor cells of metastasis, which are ultimately responsible for the main cause of death in BC. However, to date molecular mechanisms underlying CTC formation in BC have been insufficiently defined. Methods RNA-seq was carried out in primary tissues from early-stage BC patients (with CTCs≥5 and CTCs = 0, respectively) and the validation study was conducted in untreated 80 BC patients. Multiple in vitro and in vivo models were used in functional studies. Luciferase reporter, ChIP-seq, CUT&Tag-seq, and GST-pulldown, etc. were utilized in mechanistic studies. CTCs were counted by the CanPatrol™ CTC classification system or LiquidBiospy™ microfluidic chips. ERK1/2 inhibitor SCH772984 was applied to in vivo treatment. Results Highly expressed FOXD1 of primary BC tissues was observed to be significantly associated with increased CTCs in BC patients, particularly in early BC patients. Overexpressing FOXD1 enhanced the migration capability of BC cells, CTC formation and BC metastasis, via facilitating epithelial-mesenchymal transition of tumor cells. Mechanistically, FOXD1 was discovered to induce RalA expression by directly bound to RalA promotor. Then, RalA formed a complex with ANXA2 and Src, promoting the interaction between ANXA2 and Src, thus increasing the phosphorylation (Tyr23) of ANXA2. Inhibiting RalA-GTP form attenuated the interaction between ANXA2 and Src. This cascade culminated in the activation of ERK1/2 signal that enhanced metastatic ability of BC cells. In addition, in vivo treatment with SCH772984, a specific inhibitor of ERK1/2, was used to dramatically inhibit the CTC formation and BC metastasis. Conclusion Here, we report a FOXD1-dependent RalA-ANXA2-Src complex that promotes CTC formation via activating ERK1/2 signal in BC. FOXD1 may serve as a prognostic factor in evaluation of BC metastasis risks. This signaling cascade is druggable and effective for overcoming CTC formation from the early stages of BC. Supplementary Information The online version contains supplementary material available at 10.1186/s13046-022-02504-0. | FOXD1-dependent RalA-ANXA2-Src complex promotes CTC formation in breast cancer
Early metastasis is a key factor contributing to poor breast cancer (BC) prognosis. Circulating tumor cells (CTCs) are regarded as the precursor cells of metastasis, which are ultimately responsible for the main cause of death in BC. However, to date molecular mechanisms underlying CTC formation in BC have been insufficiently defined.
RNA-seq was carried out in primary tissues from early-stage BC patients (with CTCs≥5 and CTCs = 0, respectively) and the validation study was conducted in untreated 80 BC patients. Multiple in vitro and in vivo models were used in functional studies. Luciferase reporter, ChIP-seq, CUT&Tag-seq, and GST-pulldown, etc. were utilized in mechanistic studies. CTCs were counted by the CanPatrol™ CTC classification system or LiquidBiospy™ microfluidic chips. ERK1/2 inhibitor SCH772984 was applied to in vivo treatment.
Highly expressed FOXD1 of primary BC tissues was observed to be significantly associated with increased CTCs in BC patients, particularly in early BC patients. Overexpressing FOXD1 enhanced the migration capability of BC cells, CTC formation and BC metastasis, via facilitating epithelial-mesenchymal transition of tumor cells. Mechanistically, FOXD1 was discovered to induce RalA expression by directly bound to RalA promotor. Then, RalA formed a complex with ANXA2 and Src, promoting the interaction between ANXA2 and Src, thus increasing the phosphorylation (Tyr23) of ANXA2. Inhibiting RalA-GTP form attenuated the interaction between ANXA2 and Src. This cascade culminated in the activation of ERK1/2 signal that enhanced metastatic ability of BC cells. In addition, in vivo treatment with SCH772984, a specific inhibitor of ERK1/2, was used to dramatically inhibit the CTC formation and BC metastasis.
Here, we report a FOXD1-dependent RalA-ANXA2-Src complex that promotes CTC formation via activating ERK1/2 signal in BC. FOXD1 may serve as a prognostic factor in evaluation of BC metastasis risks. This signaling cascade is druggable and effective for overcoming CTC formation from the early stages of BC.
The online version contains supplementary material available at 10.1186/s13046-022-02504-0.
Breast cancer (BC) is the leading cause of cancer-associated death in women worldwide [1]. Despite numerous efforts to improve the survival rate of BC in the past decades, about 25–50% of BC patients develop distant metastases after diagnosis [2]. Metastatic breast tumor cells spread to almost all parts of the human body, among which lung, bone, liver, and brain rank as the most frequent metastatic sites [3]. Presently, the five-year survival rate is about 27% in BC patients with recurrence and has not been effectively improved [3–6]. As such, identifying of novel druggable targets for the treatment of BC is crucial. Circulating tumor cells (CTCs) refer to cancer cells detached from the primary or metastatic tumors and released into blood circulation. They are considered as the ‘precursor event’ of BC metastasis and an important prognostic factor [7, 8]. The American Joint Committee on Cancer (AJCC) TNM staging system incorporated CTC enumeration into a new classification of metastatic staging of BC, and confirmed a significant prognostic effect of CTC count. Several factors, including reactive oxygen species (ROS), tumor cell intravasation, platelets adhesion and epithelial-mesenchymal transition (EMT), etc., have been investigated [9–12], but the molecular mechanisms underlying the regulation of CTC formation in primary BC tissue, particularly in early BC, are scant. FOXD1 (Forkhead Box D1) is a member of the forkhead gene family of transcription factors and has been implicated in tumorigenesis [13–17]. By activating ALDH1A3 transcription, FOXD1 enhances the oncogenic potential of mesenchymal glioma stem cell-like cells [18]. By regulating MMP9 and RAC1B, FOXD1 promotes invasion in melanoma [19]. By activating the ERK1/2 signal, FOXD1 induces the invasion and metastasis of colorectal cancer [20, 21]. FOXD1 also enhances BC proliferation and chemoresistance [22]. However, to date there has been no evidence linking FOXD1 to CTC formation and metastasis in BC. Ral (Ras Like) protein is a member of the Ras small G protein family [23]. Activated RalA (GTP-bound RalA) can interact directly with downstream effectors. Oncogenic Ral is often upregulated in various human tumors and plays a key role in oncogenesis and metastasis [24]. ANXA2, an accessory protein that belongs to the calcium-conducting annexin family [25], is highly expressed in breast tumor tissues [26]. Tyr23 Phosphorylation of ANXA2 by Src tyrosine kinase is an important post-translational modification of ANXA2, and p-ANXA2 has significant effects on ERK signal activation, EMT, and metastasis in tumor cells [27–30]. However, little is known regarding the interaction between RalA, ANXA2 and Src in BC. Here, we carried out a comprehensive study on CTC formation in BC. Clinical sample analyses firstly showed a positive correlation between CTCs in blood samples and FOXD1 expression in primary BC tissue samples, particularly in early BC. High FOXD1 expression was closely associated with increased metastasis and poor outcomes in BC patients. Secondly, comprehensive functional and mechanistic studies provided the first evidence that FOXD1 promoted CTC formation and metastasis in BC by regulating the RalA-ANXA2-Src complex activating ERK1/2 signaling. Further, we conducted an in vivo therapy with ERK inhibitor to evaluate the clinical benefit of FOXD1-dependent cascade on CTC formation and metastasis in BC, providing a potential approach for preventing BC metastasis. Our goal for this study is to give a new perspective on CTC formation and identify novel targets for predicting metastasis risk and preventing metastasis in BC, particularly in early BC.
Tissue specimens from 80 patients were provided by the department of breast surgery of Nanfang hospital. All BC patients were newly diagnosed and without distant metastasis or clinical treatments. The samples were immediately frozen in liquid nitrogen for RNA extraction and qRT-PCR. The clinical staging of all patients was based on the eighth edition of the AJCC guidelines. 7.5 ml peripheral blood was collected from each patient before treatments, and the circulating tumor cells (CTCs) were counted by the CanPatrol™ CTC classification system (Guangzhou, China). 14 early BC patients were selected for RNA-seq (Novogne, China); among them, 7 patients with CTC ≥ 5 and 7 patients with CTC = 0 (early stage breast cancer was defined as stages I–II [31, 32]). This study was approved by the Ethics Committee of Southern Medical University, and all patients signed informed consent.
Breast tumor cell lines were obtained from the cell bank of the Chinese Academy of Sciences. MDA-MB-231, MDA-MB-468, T-47D, HS 578 T, and SK-BR-3 were cultured in DMEM containing 10%FBS. MCF-7 cells were cultured in MEM containing 10%FBS and non-essential amino. BT-549 was cultured in 1640 containing 10%FBS. MCF-10A was cultured in MEGM kit (Lonza). 20 mM HEPES, penicillin, and streptomycin were included in all medium formulations. All cells are cultured at 37 °C in a humidified incubator with 5% CO2.
For tissue samples, the tissues were ground with mortar and pestle. After adding TRIzol lysate, the suspension was then homogenized on ice. For the cell samples, TRIzol lysate was added after the adherent cells were washed twice with PBS buffer. After chloroform (200 μl/1 ml TRIzol lysate) was added and mixed, the suspension was placed at room temperature for 5 minutes and centrifuged at 12000 g at 4 °C for 15 minutes. 100-400 μl liquid was pipetted out from the upper layer. Gently mixed it well after adding isopropanol, then centrifuged the suspension at 12000 g at 4 °C for 10 minutes. 75% ethanol (configured with DEPC water and anhydrous ethanol) was added to remove the excess isopropanol reagent. An appropriate amount of DEPC water was added to dissolve the RNA precipitation. Finally, RNA concentration was determined using Nanodrop.
Total RNA was reverse transcribed into cDNA using the RT reagent kit (Takara, RR047A). cDNA was used for subsequent qRT-PCR using the PerfectStart™ Green qPCR SuperMix (Tansgen, AQ602). Briefly, the reagents for gDNA removal were added proportionally, and the mixed liquid was reacted at 42 °C for 2 minutes on a standard PCR instrument. Reverse transcription reaction reagents were proportionally added to the products. The cDNA products were diluted and added to qPCR reaction reagents, including 2X qPCR Supermix, forward and reverse primers (10 μM), nuclease-free water. After lightly blending, a two-step reaction was conducted. According to the results of dissolution and amplification curve analysis, the relative expression of genes was calculated by 2-△△Ct. See Supplementary Table 3 for primer information.
After assessing RNA integrity using RNA Nano 6000 (Agilent Technologies, CA, USA). RNA samples of clinical BC tissues or FOXD1 knockdown and control cell lines were subjected to library construction and then sequenced on Illumina Novaseq 6000. FeatureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene. RNA sequencing technology was provided by Novogene (Beijing, China).
Two hundred mCherry-labeled cells were suspended in 5 nL DMEM medium for the vitellicle injection of each FLK-EGFP transgenic zebrafish embryo after 48 h fertilization. The numbers of mCherry-labeled cells that intravasated into circulation were observed under CQ1 confocal imaging system (Yokogawa, Japan) and was quantified via ImageJ software.
A total of 1500–2000 cells per well were seeded into 96-well plates. 10 μL of CCK-8 (APExBIO, USA) solution and 100 μL of fresh medium were loaded to each well for incubation at 37 °C for 2 h. The optical density (OD) value was measured at 450 nm using a microplate reader.
Cells were grown on glass-bottom 24-well culture plates. After treated with 4% paraformaldehyde, the adherent cells were permeabilized with 0.2% Triton X-100. Blocking solution (5% goat serum) was applied for 60 minutes at room temperature. Detailed antibodies information sees Supplementary Table 4. Nuclear staining was performed with DAPI. The images were collected after samples treated with a mounting medium.
5 × 105 cells/well were added to the six-well plate to ensure that the cells were confluent the next day. The next day, a wound was made by dragging a plastic pipette tip across the cell surface. The medium was aspirated, and the floating cells were washed with PBS buffer solution, and the serum-free medium was added to each well. The double turntable high intension confocal was used to record the same position in each well every hour for continuous observation.
Firstly, tissues were fixed in 10% buffered formaldehyde, and then, 3-4 μm paraffin-embedded slides were prepared. After antigen retrieval, the slides were stained with specific primary antibodies and the corresponding species-specific HRP-conjugated secondary antibodies. A Freshly-prepared DAB solution was used for chromogenic reaction, and the nucleus was stained with hematoxylin. Antibodies information see Supplementary Table 4.
The cells were resuspended in a serum-free medium, and the cell concentration was adjusted to 10^6 cells/ml. 100 μl/well cell suspension was added in the upper compartment, and 600 μl 10%FBS medium was added in each 24plate well. The residual cells in the upper compartment were cleaned up by swabs after 12-24 h. The cells were fixed with methanol and stained with crystal violet solution.
The total cell protein was extracted by RIPA lysate containing protease/phosphatase inhibitor and denatured. After that, denatured proteins were separated using SDS-PAGE gel, and transferred to the PVDF membrane. The PVDF membrane was incubated with primary antibodies (see Supplementary Table 4) corresponding to the specific protein and species-specific HRP-conjugated secondary antibodies. Blots were visualized by ECL chemiluminescence.
Disruption of RalA gene in BC cell line MDA231 were adopted from the protocol of our previous work [33]. Two guide RNAs (gRNA1 at 39,686,777) and gRNA2 at 39,687,757) targeting to the genomic locus of RALA NC_000007.14 (39,622,955...39708124, GRCh38.p13) were selected by DNA2.0 /CRISPR online tools. Those guide RNAs combination were introduced to cells to create a big fragment (about 980 bp) deletion around the second exon region of RALA. The transfection was carried out with equimolar mixture of pX459v2-HF-1-RALA_gRNA1/2. 24 hours after post-transfection, the cells were selected with 2 μg/ml puromycin for 3–7 days. At the end of the selection, the puromycin-resistant cells were trypsinized and replated in 96-well at density suitable for single colony isolation of the knockout cell clones. These clonal cell lines were picked from plates and were split into two new replica plates, with one plate for genomic DNA isolation and genotyping PCR, the others for cell expansion till to preservation after validation again by western-blot.
RalA promoter (Chr7:39,662,789-39,663,177, hg19) and serial truncations were cloned into pGL4.10[luc2] vector. The indicated reporter vectors were transfected into BC cells together with ectopic expression vector and pGL4.74[hRluc/TK]. Plasmids were transfected with ViaFect™ Transfection Reagent (Promega). After 48 hours cells were harvested. Then, luciferase and Renilla activity were detected according to the manufacture of the Promega dual-luciferase reporter assay kit.
For RalA GTPase pulldowns, RalA activity was measured using RalA Activation Assay Kit (Cat. #BK040, Cytoskeleton, USA). Briefly cell lysates were incubated with RalBP1-RBD beads for 1 hour at 4 °C. After this the beads are washed and boiled in Laemmli Sample Buffer. The boiled samples are run on SDS-PAGE followed by Western Blotting. HRP labeled mouse or rabbit secondary antibodies were used to develop the blots by chemiluminescence using ECL.
The GST fusion ANXA2 protein (Cat. Ag1777) and 6*His fusion RalA protein (Cat. Ag5329) were purchased from Proteintech™. Briefly, GST or GST-ANXA2 recombinant protein was conjugated to pre-washed anti-GST Tag magnetic beads (Sino Biological, China), followed by the incubation with protein lysates of His-RalA recombinant protein. The immobilized proteins were then eluted and subjected to western blot analysis.
Co-IP was performed using Pierce Classic Magnetic IP/Co-IP Kit (No.88804, Thermofisher, USA) according to the manufacture’s protocols. Briefly, the total protein of the cells was harvested and incubated with the antibody for FLAG for 12 hours at 4 °C on a rotating wheel. Then, the mixes were incubated together with the protein A/G magnetic beads for 1 hour at room temperature. After extensive washing, the immunocomplexes were eluted and subjected to LC-MS/MS analysis or western blot analysis. For LC-MS/MS analysis, MaxQuant software (version 1.5.6) was applied for protein identification and quantification. According to the LFQ intensity, a protein only identified in FLAG-RalA group with> 2 unique peptides was considered significant. Thus, the top 5 candidates of RalA-interacting proteins were further identified from LC-MS/MS analysis and listed in Supplementary Table 1.
MDA231 cell lines were cross-linked with 1% formaldehyde for 10 min and quenched in 125 mM glycine at RT for 5 min. The formed chromatin was sonicated to generate DNA fragments using Bioruptor plus. Chromatin fragments were immunoprecipitated with antibodies against normal mouse IgG (Invitrogen, USA), FOXD1 (Santa Cruz, USA). Purified DNA was analyzed by qRT-PCR with SYBR Green Master Mix (Transgen, Beijing, China). The primers used are listed in the Supplementary Table 3. ChIP libraries were prepared using ChIP DNA according to the KAPA Hyper Prep Kit library preparation protocol. Libraries were sequenced on Illumina Novaseq 6000.
This assay was processed using the NovoNGS CUT&Tag High-Sensitivity Kit V2.0 (Novoprotein, Shanghai) according to the manufacturer’s instruction. 106 cells/sample were harvested and washed in Wash Buffer. ConA magnetic bead-bound cells were resuspended in 50 μL precooled Primary Antibody Buffer containing the appropriate primary antibody (FOXD1, Santa Cruz). Mouse IgG (Invitrogen) was used as the control antibody. After removing the primary antibody, the diluted secondary antibody in 100 μl Secondary Antibody Buffer and cells were incubated at RT for 1 h. ChiTag™ 2.0 Transposome was used to resuspend the cells and the incubation was performed at RT for 1 h. After cells were incubated in Tagmentation Buffer on a rotating platform at 37 °C for 1 h, the DNA were extracted. For libraries amplification, DNA was mixed with i5 Primer, i7 Primer, and 5XAmpliMix were added and mixed, following cycling conditions: 72 °C for 3 min; 98 °C for 30 s; 22 cycles of 98 °C for 15 s, 60 °C for 20 s and 72 °C for 15 sec; final extension at 72 °C for 2 min and hold at 10 °C. Post-PCR clean-up was performed by adding NovoNGS® DNA Clean Beads, and libraries were incubated with beads for 5 min at RT, washed twice gently in 80% ethanol, and eluted in TE-Buffer. Libraries were sequenced by Genefund (Shanghai, China).
Female-specific pathogen-free (SPF) NSG mice were purchased from Shanghai Model organisms Co.,Ltd. Control or FOXD1-shRNA MDA231 cell was transfected to express luciferase and tdTomato tags. 2 × 106 FOXD1-shRNA (shFOXD1) or control (shCtrl) cells were mixed with 50% Basement Membrane Matrix Phenol Red free (Corning) in PBS and injected orthotopically in mammary fat pad of NSG mice. Primary tumor assessment, CTC enumeration, and lung metastasis analysis were performed 9 weeks after tumor onset. For ERK inhibitor treatment assessment, mice were randomly divided into 5 batches, recorded as batch 1, batch 2, batch 3, batch 4, batch 5. Each batch divided again into 3 experimental groups, CtrL-vehicle, FOXD1-vehicle and FOXD1-SCH (detailed information see Fig. 6 legend). At each observation time point, the CTC number of 3 mice in each group (CtrL-vehicle, FOXD1- vehicle, FOXD1-SCH) were respectively detected. The mice of batch 5 were continuously imaged by BLI (Fig. 6D). In detail, 2 × 106 MDA231-FOXD1-Luc-tdTomato or MDA231-FOXD1-CtrL-Luc-tdTomato cells were mixed with 50% Basement Membrane Matrix Phenol Red free (Corning) in PBS and injected orthotopically in NSG mice. When tumor volumes reached ≈50mm3, SCH772984 (25 mg/kg, formulated in DMSO) or vehicle (DMSO) was intraperitoneally injected twice per day for 2 weeks. All animal experiments were performed according to the university animal guidelines, and with prior approval from the Animal Experimentations Ethics Committee, Southern Medical University.
Peripheral blood specimens for CTC analysis were obtained after informed patient consent at Nanfang Hospital. 7.5 ml of peripheral blood was drawn in EDTA vacutainers. The first 2 ml were discard to avoid potential skin cell contamination from the venipuncture. The CanPatrol™ system (Guangzhou, China) was used to isolate CTCs as previously described [34]. Briefly, the prepared blood samples were filtrated through a membrane with 8-μm diameter pores. The CTCs were retained on the filter, and the leukocytes went through the pores because CTCs were larger than leukocytes. Then, the CTCs were identified by RNA-ISH. Briefly, the cells retained on the filter were fixed, permeabilized and digested. Next, the cells were subjected to a serial of hybridization reactions with probes specific to the EpCAM, CK8/18/19, Vimentin, Twist, and CD45 transcripts. DAPI was used to stain the nucleuses. The cells were analyzed with a fluorescent microscope. The CTCs were identified by probes specific for the genes mentioned above (EpCAM, CK8/18/19, Vimentin and Twist), and CD45 was used to discriminate leukocytes and CTCs. For mouse studies, the CTCs were captured by microfluidic immunomagnetic bead screening provided by LiquidBiospy™ CTCs enrichment and detection platform (Livzon Cynvenio) [35], according to the manufacturer’s instructions. Briefly, the blood samples were retrieved via cardiac puncture. The prepared blood samples were added with biotin-labeled capture antibodies (including EpCAM, and EMT relative antibodies), streptavidin-labeled magnetic beads. In addition, fluorescence-labeled CD45 antibody was added to detect and eliminated leukocytes. Nucleuses were stained by DAPI. The enriched CTCs on microfluidic chips were identified and counted by Ariol DM6000B system (Leica Microsystems). The CTCs were defined as nucleated cells lacking CD45 and expressing eGFP.
All data were extracted from not less than three independent experiments. To ascertain statistical differences between two groups or multiple testing, Student’s t-test or One-way ANOVA was used ascertain posttest combined with Tukey test used to compare all pairs of groups. The χ2 or Fisher exact tests were used for categorical variables. Correlation analysis was performed using Pearson’s correlation. P < 0.05 was considered significant.
A total of 80 patients who had been clinically diagnosed with BC at Nanfang hospital, Southern Medical University, China, were enrolled in this study. Using the CanPatrol™ CTC classification system (Guangzhou, China) [34], CTCs were isolated from peripheral blood samples (7.5 ml) collected prior to the commencement of treatment. According to the 8th edition of the American Joint Committee on Cancer (AJCC) TNM staging system, CTC ≥ 5 /7.5 mL in peripheral blood of BC patients indicates poor prognosis. We randomly selected 7 patients with CTCs≥5 and 7 patients with CTCs = 0 (Fig. 1A). All patients had early-stage BC with similar primary foci size. Comparing the gene expression profiles of primary BC tissues derived from these two groups, we obtained a list of 103 differentially expressed genes (37 were upregulated and 66 were down-regulated) (Fig. 1B). According to the p-value and foldchange (Fig. 1B), we paid attention to FOXD1, which was previously implicated in cell proliferation and chemoresistance in BC [22] and its exact role in CTC formation has not been reported in BC so far. Notably, the verification of FOXD1 differential expression in a second cohort (CTCs≥5, n = 40 and CTCs<5, n = 40) showed a similar expression trend of FOXD1 to sequencing data (Fig. 1C). FOXD1 mRNA expression in primary foci positively correlated with CTCs in peripheral blood (R = 0.3033, P = 0.0062) (Fig. 1D). FOXD1 protein expression level in the CTCs≥5 group was significantly higher than the CTCs<5 group (Fig. 1F-G). Moreover, it was particularly noteworthy that, in the early BC patients, FOXD1 mRNA expression still remained higher in CTCs≥5 group than in CTCs<5 group (Fig. 1E), suggesting that FOXD1 was implicated in CTC formation in BC, particularly in early BC. The Cancer Genome Atlas (TCGA) database revealed that FOXD1 was highly expressed in a variety of other tumors (Supplementary Fig. 2E). The TCGA database also supported that the disease-free survival was significantly low in the BC patients with high FOXD1 expression relative to the BC patients with low FOXD1 expression (Fig. 1H). Together, these results indicate that FOXD1 is clinically correlated with CTC formation in BC, particularly in early BC.
We initially investigated six BC cell lines and normal breast epithelial cell line MCF-10A. Compared with MCF-10A, six BC cells showed higher expression levels of FOXD1 (Supplementary Fig. 1A-B). We designed lentivirus vectors carrying FOXD1 short hairpin RNA (shRNA) sequences (sh1, sh2, sh3) and infected two of six cell lines, MDA-MB-231 (MDA231) and MDA-MB-468 (MDA468), with relatively high endogenous FOXD1 expression. shRNA effectively knocked down the FOXD1 expression in both cells at the mRNA level and protein level (Supplementary Fig. 1C-D). We also established FOXD1-overexpressing MCF-7 cells, which originally had a relatively low FOXD1 expression (Supplementary Fig. 1C-D). To elucidate the function of FOXD1 in regulating CTC formation, we established immunodeficient (NSG) mice bearing MDA231-shFOXD1-Luc and MDA231-shCtrL-Luc cells. Blood samples (about 0.8-1 ml) were collected from mice. CTCs were enriched by LiquidBiospy™ CTCs enrichment and detection platform (Livzon Cynvenio) [35]. We noticed that the number of CTCs was significantly lower in FOXD1 knockdown group than in control group (Fig. 2A). Metastatic bioluminescence signals from lungs were significantly lower in the FOXD1 knockdown group than the control (Fig. 2B). Similarly, tumor growth rate (Fig. 2C) and tumor volume (Fig. 2D) were reduced in mice bearing FOXD1-knockdown cells. Moreover, Zebrafish metastatic xenograft model revealed that the metastatic cells (marked by white arrows) in the tail of zebrafish injected with FOXD1 knockdown MDA231 cells were fewer than that in the control group (Fig. 2E). In consistence with in vivo results, knockdown of FOXD1 decreased the migration potential of BC cells, as shown by transwell and wound healing experiments, while overexpression of FOXD1 showed opposite effects (Fig. 2F and Supplementary Fig. 2A). EMT plays an essential role in BC metastasis and CTC formation [36–38]. Immunoblot analyses showed that, in the FOXD1 knockdown group, the expression of E-cadherin was increased while the expression of N-cadherin, Vimentin, Snail and β-catenin was decreased. Inversely, stable overexpression of FOXD1 decreased E-cadherin expression and increased the expression of N-cadherin, Vimentin, Snail and β-catenin (Fig. 2G and Supplementary Fig. 2B). We also observed morphologic changes in MCF-7-FOXD1 cells from circular or polygonal to long spindle shape, suggesting the existence of EMT-associated phenotypic features (Supplementary Fig. 2C). We further detected the expression of EMT genes in primary tissues of clinical BC patients. Consistently, BC patients with CTCs≥5 had higher Vimentin expression and lower E-cadherin expression than the CTCs<5 group (Fig. 2H). The expression trend of Vimentin protein was consistent with that of FOXD1 (Fig. 2H and Fig. 1G). We also investigated the effects of FOXD1 on cell proliferation. CCK-8 assays showed that FOXD1 increased BC cell growth (Supplementary Fig. 2D). Collectively, these findings demonstrate that FOXD1 may promote the development of CTCs and metastasis in BC by inducing EMT.
To identify the molecules directly regulated by FOXD1 in CTC formation, we performed ChIP-sequencing and CUT&Tag-sequencing analyses. Gene enrichment pathway (KEGG) analyses revealed that FOXD1 downstream genes were preferentially enriched in the top-ranked MAPK signaling pathway (Fig. 3A). We also investigated the global transcriptional alteration (RNA-seq) caused by FOXD1 in two pairs of stable FOXD1 knockdown cells (MDA231-shFOXD1, MDA468-shFOXD1) and their corresponding control cells (Fig. 3B). Next, using Venn diagram analysis for three datasets from RNA-seq, ChIP-seq and CUT&tag-seq, we discovered 6 common genes, of which RalA (a Ras-like small GTPase) was identified as a FOXD1 downstream target gene uniquely associated with the MAPK pathway (Fig. 3C). Results from ChIP-seq and CUT&Tag-seq analyses showed that FOXD1 bound to the upstream (− 382 ~ + 6 bp, chr7:39,662,789 -39,663,177) of the transcription start site (TSS) of RalA (Fig. 3D). To confirm the ChIP-seq and CUT&Tag-seq results, luciferase reporters were constructed by fusing the enriched peak region of RalA promoter with the luciferase gene (Fig. 3E). We found that the ectopic expression of FOXD1 majorly increased the luciferase reporter activity of RalA-Fragment 3 (F3) compared to the controls (Fig. 3E-F and Supplementary Fig. 3A). To further confirm the FOXD1 binding site within the F3 of RalA promoter, mutant constructs for FOXD1 binding sites (− 83 ~ − 76 bp) were generated after using analysis of JASPAR database (Additional file 2). The enhanced luciferase activity was reversed by transfection with mutant promoter region (Fig. 3G). Moreover, the transcriptional regulation of RalA by FOXD1 was supported by ChIP-qPCR, which indicated that FOXD1 directly bound to the promoter region of RalA in BC cells (Fig. 3H). In the clinical primary BC tissues, RalA expression level was also positively correlated with FOXD1 (R = 0.4064, P = 0.0002) (Fig. 3I). Furthermore, western blot showed that knockdown of FOXD1 markedly reduced RalA and the phosphorylation of MEK1/2 and ERK1/2 (MAPK pathway proteins) while the expression of non-phosphorylated proteins remained unchanged. Overexpression of FOXD1 upregulated RalA and the phosphorylation of MEK1/2 and ERK1/2 (p-MEK1/2, p-ERK1/2) (Fig. 3J). Immunohistochemical staining of primary mouse tissues indicated that the expression of RalA, p-ERK1/2 and Vimentin in the FOXD1 knockdown group were lower than those in the control group (Fig. 3K). Together, these data indicated that FOXD1 majorly influenced the MAPK signaling pathway in BC cells. It is known that RalA is a small Ras-related protein that functions as a GTPase, so we further examined whether FOXD1 influenced RalA GTPase activity. Interestingly, we observed that RalA GTPase activity was significantly reduced upon the inhibition of FOXD1 expression. In contrast, GTPase activity was enhanced after FOXD1 was overexpressed (Fig. 3L). Taken together, these findings support that FOXD1 transcriptionally regulates RalA and enhances its GTPase activity in BC cells.
To determine whether the CTC formation and BC cell migration were regulated by FOXD1-RalA-ERK1/2 signaling cascade, we performed CRISPR/Cas9-mediated knockout of RalA in MDA231 cells. RalA knockout reduced the migration ability of BC cells (Supplementary Fig. 3E-G), down-regulated ERK1/2 signal, and impaired EMT process (Supplementary Fig. 3I). The cell growth ability of BC cells also reduced after RalA knockout (Supplementary Fig. 3H). Subsequently, RalA rescue experiments were performed. After overexpressing RalA, the reduction of cell migration ability caused by FOXD1 knockdown was observed to be largely restored (Fig. 4A), and the expression of E-cadherin was downregulated while the expression of p-MEK1/2, p-ERK1/2, N-cadherin, Vimentin, β-catenin and Snail was upregulated (Fig. 4B-C and Supplementary Fig. 3B). RalA also partially restored the reduced cell growth ability caused by FOXD1 knockdown (Supplementary Fig. 3 J). Moreover, we used siRNA to suppress RalA expression in MCF-7-FOXD1 cells. Knockdown of RalA significantly reduced the cell migration of MCF-7-FOXD1 cells (Fig. 4A), upregulated E-cadherin expression and down-regulated the expression of p-MEK1/2, p-ERK1/2, N-cadherin, Vimentin, β-catenin and Snail (Fig. 4B-C and Supplementary Fig. 3C). CCK-8 assay also showed that the proliferation of MCF-7-FOXD1 cells was significantly reduced upon RalA knockdown (Supplementary Fig. 3 J). SCH772984 is a preclinically promising, selective, ATP-competitive ERK1/2 inhibitor that inhibits the phosphorylation of the ERK self-activating ring [39, 40] (Supplementary Fig. 4A and Supplementary Fig. 3D). Using ERK inhibitor, we continued to testify the regulatory role of ERK1/2 signal in FOXD1’s promotion of BC cell migration. We found that SCH772984 attenuated the migration ability of MDA231-FOXD1 cells in a dose-dependent manner (Supplementary Fig. 4B). It also significantly impaired EMT process in MDA231-FOXD1 cells (Supplementary Fig. 4C). CCK-8 assays also showed that the SCH772984 reduced the proliferation of FOXD1-overexpressing tumor cells (Supplementary Fig. 4D). Furthermore, we clinically assessed the correlation between RalA and CTCs in BC patients. RT-qPCR showed that RalA expression level in primary BC tissues with CTCs≥5 (n = 40) was significantly higher than that in primary BC tissues with CTCs<5 (n = 40) (Fig. 4D). Notably, consistently with that of FOXD1 expression, it is in the early BC patients that RalA expression was still higher in the CTCs≥5 group (n = 27) than in the CTCs<5 group (n = 31), suggesting that RalA also played a role in CTC formation in the early BC patients (Fig. 4E). Moreover, Western blot and IHC results showed that the expression level of RalA in the group with CTCs≥5 was higher than that in the group with CTCs<5 (Fig. 4F-G). The TCGA database indicated that the overall survival of BC patients with high RalA expression was significantly shorter than that of patients with low RalA expression (Fig. 4H). Finally, IHC analysis showed that the expression levels of p-ERK1/2 and p-MEK1/2 were higher in primary tissues with high CTCs than those of BC patients with low CTCs (Fig. 4G). Collectively, the above results demonstrate that the FOXD1-dependent RalA-ERK1/2 signaling cascade mediates CTC formation and BC cell migration.
To gain further insight into the mechanisms underlying the activation of ERK1/2 signal by RalA, we applied immunoprecipitation-LC-MS to identify the potential binding partners of RalA (Additional file 3). Interestingly, Annexin A2 (ANXA2) was identified as a major protein partner of RalA (Supplementary Table 1). Thus, we focused our subsequent studies on the role of ANXA2 in RalA-dependent activation of ERK1/2 signal. The interaction between RalA and ANXA2 was confirmed by co-immunoprecipitation (co-IP) in MDA231 cells and GST-pulldown (Fig. 5A-B). The co-localization of RalA and ANXA2 was observed in the cytoplasm using immunofluorescent staining (Fig. 5C). To further ascertain the crucial binding site of RalA, ZDOCK was used to build an interaction model of these two proteins (Supplementary Table 2). Co-IP assay confirmed that aa80–120 of RalA was necessary for the direct interaction between RalA and ANXA2 (Fig. 5D). Notably, CRISPR/Cas9-mediated knockout of RalA was found to reduce the phosphorylation of ANXA2 (p-ANXA2, Tyr23), but did not obviously alter total ANXA2 (Fig. 5E). These data suggested that RalA formed a complex with ANXA2, inducing the phosphorylation of ANXA2. ANXA2 belongs to the calcium-conducting annexin family, which has been reported to activate MAPK signaling and promote metastasis in tumor cells. Tyrosine phosphorylation (Tyr23) of ANXA2 was required for ERK1/2 activation [30, 41, 42]. In RalA-overexpressing MDA231 cells, we observed that ANXA2 knockdown indeed reduce p-ERK1/2 (Fig. 5F), confirming that ANXA2 was required for RalA-dependent activation of ERK1/2 signal. ANXA2 was first described as a substrate for the Src kinase and previously reported to bind to Src [43, 44]. To explore whether Src kinase is involved in the phosphorylation of ANXA2, we used si-Src in MDA231-RalA and MDA468-RalA cells and found that si-Src reduced the cell migration ability (Fig. 5G) and down-regulated the expression of p-ANXA2 (Fig. 5H). Given that RalA was interacted with ANXA2 and ANXA2 was reported to bind to Src [44], we proposed that RalA may form a complex with ANXA2 and Src in BC cells. Notably, co-IP assays showed that Src co-precipitated with RalA and ANXA2, while ANXA2 interacted with RalA and Src in an endogenous condition (Fig. 5I). Also, we predicted the model of RalA-ANXA2-Src ternary interaction (Supplementary Fig. 4E). RalA overexpression conferred no evident effect on the expression levels of Src or ANXA2, whereas the interaction between Src and ANXA2 was notably enhanced compared with control cells (Fig. 5J), suggesting that RalA was required for the binding of Src to ANXA2. In addition, Ral GTPase inhibitor RBC8 was used to test whether RalA-GTP activity was necessary for the interaction between ANXA2 and Src. Co-IP assay showed that the binding ability of ANXA2 to Src was decreased in RalA-GTP inhibited cells compared with control cells (Fig. 5K). Using RBC8 obviously reduced the expression of p-ANXA2, p-ERK1/2 and the EMT process in FOXD1 overexpression cells (Fig. 5L). Moreover, ectopic expression of constituently activated RalA mutant (G23V) induced p-ERK1/2, whereas constituently inactivated RalA mutant (G26A) decreased p-ERK1/2 level, indicating RalA-GTP indeed activated ERK1/2 signaling pathway (Supplementary Fig. 4F). These data collectively suggest that RalA forms a complex with ANXA2 and Src, mediates the interaction between Src and ANXA2, and thus promotes the phosphorylation of ANXA2. This RalA-ANXA2-Src complex is essential for activating ERK1/2 signaling cascade and promoting metastasis ability of BC cells.
We established orthotopic xenograft tumor models to evaluate the therapeutic efficacy of ERK inhibitor SCH772984 (SCH). FOXD1-overexpressing or FOXD1-ctrl MDA231 cells were inoculated into mammary fat pads of NOD/SCID mice (Fig. 6A). After 2 weeks, mice inoculated with FOXD1-overexpressing MDA231 cells were randomly assigned into two groups (FOXD1-SCH, FOXD1-vehicle) that were administered respectively with 25 mg/kg SCH772984 or control vehicle intraperitoneally twice a day (Fig. 6A). Interestingly, we found that CTCs were increased in the FOXD1-vehicle group compared to the control-vehicle group as early as 3 weeks after cell inoculation, indicating that FOXD1 promoted CTC formation from the early stages of BC (Fig. 6B). Notably, a significant reduction of CTC number became detectable in week 3 in the FOXD1-SCH group compared to FOXD1-vehicle (Fig. 6B). Lung metastasis were significantly decreased in the FOXD1-SCH group than FOXD1-vehicle (Fig. 6C). Following the commencement of SCH treatment, we observed an obvious reduction of tumor growth (Fig. 6D) and tumor volume (Fig. 6E) in the FOXD1-SCH group compared to FOXD1-vehicle. Furthermore, IHC confirmed that the expression levels of p-ERK1/2 and Vimentin were decreased in tumor tissues treated with SCH772984 (Fig. 6F). Collectively, these in vivo data confirm that FOXD1 plays a critical role in promoting CTC formation and metastasis in BC. Blocking FOXD1-dependent ERK1/2 signaling cascade with ERK1/2 inhibitor might serve as an effective therapeutic approach to reduce CTC formation and mitigate breast metastasis.
CTCs play an essential role in tumor metastasis and the underlying molecular mechanisms of CTC formation in BC, particularly in early BC, are unclear. In this study, we sought to identify the regulatory pathway modulating CTC formation in BC. We observed a consistent correlation between the abnormal changes of FOXD1-dependent RalA-ANXA2-Src-ERK1/2 signaling cascade and CTC formation in BC, particularly in early BC. Our data demonstrated that early CTC formation was not a random process; it was under the influence of FOXD1-dependent signaling cascade that BC cells acquired the potential for motility to detach and disseminate from primary tumor foci in BC. RalA, as the upstream activated protein, is required for the binding of Src to ANXA2; RalA forms a complex with ANXA2 and Src, mediates the interaction between Src and ANXA2, and thus promotes the phosphorylation of ANXA2, further inducing the activation of ERK1/2 signal. We also evaluated the clinical benefit of blocking FOXD1’s regulatory cascade in BC, and found that ERK1/2 inhibitor effectively reduced CTC formation and tumor metastasis in BC. This study has profound implications for understanding of CTC formation in early BC patients and provide a novel druggable and effective strategy to reduce early metastasis of BC. Our study for the first time demonstrated the important role of FOXD1 in promoting CTC formation in BC, particularly in early BC, and provided a new perspective on FOXD1-associated mechanism. Mechanistic studies showed that FOXD1 promoted CTC formation by activating ERK1/2 signaling cascade through RalA-ANXA2-Src complex. It is noteworthy that, besides regulating BC migration and CTC formation, FOXD1 promoted tumor growth as well. This is consistent with some of other previous studies [45, 46]. Our clinical, functional and mechanistic studies consistently supported that FOXD1 primarily modulated CTC formation at the early stage of BC. As tumor was progressing, the effect of FOXD1 on tumor growth became pronounced, which might further quicken the formation of CTCs. In this study, we first found that FOXD1 directly regulated RalA transcription in BC after using deep sequencing and luciferase assays. RalA expression was regulated by FOXD1 in primary tumors of BC patients, especially in early BC, and positively correlated with the number of CTCs. RalA enhanced CTC formation and metastasis ability of BC cells via the activation of ERK1/2 signal. Furthermore, we found that the activation of ERK1/2 signal by RalA-GTP was dependent on ANXA2 and Src. Src is a non-receptor protein tyrosine kinase. Src is highly overexpressed and activated in different epithelial cancers, especially breast cancer. It is well-documented to promote cancer cell plasticity, motility and invasion, and has been described as a key player in EMT [47, 48]. Tyr23 Phosphorylation of ANXA2 by Src tyrosine kinase promotes proliferation, migration, and invasion of tumor cells [27]. RalA is required for Src-induced phospholipase D (PLD) and MMPs (MMP-2 and 9) activations, thereby promoting tumor formation and cell invasion ability [49, 50]. We first provided strong genetic and biochemical data for RalA-ANXA2-Src interaction and demonstrated that RalA enhanced the interaction between ANXA2 and Src. RalA, ANXA2 and Src formed a complex that executed regulatory functions to increase p-ANXA2 (Tyr23), thereby activating ERK1/2 signaling in BC. Notably, we further observed that RalA-GTP played a critical role in the binding of ANXA2 to Src. Mitogen-activated protein kinase (MAPK) signaling pathway is involved in signal transduction between cell membrane receptor and nucleus [51]. It often plays an essential regulatory role in the proliferation, apoptosis, and metastasis of malignant tumor cells [52]. As important proteins of MAPK signaling pathway, ERK1/2 can modulate the migration and EMT of tumor cells through regulating ZEB1, SOX2, etc. [53–55]. Our study identified that ERK1/2 signal pathway was a critical downstream effector of RalA and participated in CTC formation and metastasis in BC. ERK1/2 inhibitor significantly reduced CTCs and metastasis from the early stages of BC progression. This confirms the significance of FOXD1-dependent RalA-ANXA2-Src-ERK1/2 signaling cascade in promoting CTC formation and highlights that ERK1/2 inhibitor SCH772984 can be a potential and effective strategy preventing CTC formation and metastasis in BC, particularly in early BC. Moreover, ERK1/2 inhibitor indeed affects some aspects of cellular functions, so clinically, it might be helpful to define optimal targeted delivery of this inhibitor to develop more effective therapeutics for ERK1/2 signal-activated BC patients. In conclusion, this study reports a FOXD1-dependent RalA-ANXA2-Src complex that promotes CTC formation via activating ERK1/2 signal in BC. The FOXD1 expression in primary BC tissues positively correlates with CTCs in BC patients, particularly in early BC patients. Functional and mechanistic studies provided the first evidence that FOXD1 promoted CTC formation and metastasis in BC by regulating the RalA-ANXA2-Src-ERK1/2 signaling cascade. In vivo experiment with ERK inhibitor validated the effect of FOXD1-dependent cascade on CTC formation and BC metastasis, providing a potential effective approach for preventing BC metastasis (Fig. 6G). Thus, this study not only improves our understanding of molecular mechanisms underlying CTC formation in early BC patients but also provides insight into the therapeutic potential of targeting the FOXD1-dependent ERK1/2 signaling cascade though further understanding this complexity will require a broader view of underlying signal transduction in the future. Tracking or modulating this signaling cascade could offer a viable approach for metastasis risk assessment, prognosis, and prevention of metastasis in early BC patients.
In summary, our study demonstrates that the FOXD1-dependent RalA-ANXA2-Src complex promotes CTC formation via activating ERK1/2 signal in BC. In vivo treatment with ERK1/2 inhibitor dramatically inhibits the CTC formation and BC metastasis. FOXD1 may serve as a prognostic factor in evaluation of BC metastasis risks, particularly in early-stage BC patients. This signaling cascade is druggable and effective for overcoming CTC formation from the early stages of BC.
Additional file 1: Supplementary Fig. 1. (A) RT-qPCR analyses of FOXD1 mRNA in the indicated breast tumor cell lines and MCF-10A. Error bars, SEM. n = 3. (B) Western blotting analyses of FOXD1 expression in the indicated breast tumor cell lines and MCF-10A. (C)RT-qPCR analysis of FOXD1 expression in control and sh-FOXD1 cells (MDA231 and MDA468), or control and FOXD1 overexpression cells (MCF-7). Error bars, SEM. n = 3. **p < 0.01, ***p<0.001 by Student’s t test. (D) FOXD1 protein expression level in control and FOXD1 knockdown cells (MDA231 and MDA468), or control and FOXD1 overexpression cells (MCF-7) by immunoblotting. Supplementary Fig. 2. (A) Cell migration capacity of FOXD1 knockdown BC cells (MDA231 and MDA468), FOXD1 overexpression BC cell (MCF7), and their control cells was determined by the wound healing assays. Scale bar, 1000 μm. Error bars, SD. n = 3. **p<0.01 by Student’s t-test. (B) Immunofluorescence images for E-cadherin and Vimentin expression in CtrL and FOXD1 knockdown BC cells (MDA231 and MDA468). Scale bar, 50 μm. (C) The morphology analysis of control and FOXD1 overexpression MCF-7 cells. Scale bar, 100 μm. (D) The cell proliferation in these transfected cells was determined using CCK-8 assays. Error bars, SD. n = 3. **p<0.01, ***p<0.001, ****p<0.0001 by Student’s t-test. (E) Expression of FOXD1 across TCGA cancers (with tumor and normal samples). Supplementary Fig. 3. (A) Immunoblotting of FOXD1 after MDA231 cells transfected with pEXP-FOXD1 or with control. (B) Immunoblotting of RalA after MDA231 cells transfected with pEXP-RalA or with control. (C) Western blotting assay was used to examine the protein levels of RalA in MCF-7 cell transfected with the control or RalA-siRNAs (si-1, si-2, and si-3). (D) Western blotting assay was used to examine protein levels of FOXD1 in MDA231 cell stably overexpressed the vector or FOXD1. (E) Visualization of genotyping PCR product for each MDA231 single clonal cell line with indicated genotype. (F) Immunoblotting of RalA in MDA231 single clonal cell lines with indicated genotype. (G) WT and RalA KO MDA-MB-231 cells were subjected to transwell migration assays. Scale bar, 250 μm. Error bars, SD. n = 3. ***p<0.001 by Student’s t-test. (H) The cell proliferation in MDA231 with WT, RalA-KO#6, or RalA-KO#26 was investigated using CCK-8 assays. Error bars, SD. n = 3. ****p<0.0001 by Student’s t-test. ns. = not significant. (I) WT and RalA KO MDA-MB-231 cells were subjected to immunoblotting assays. (J) The cell proliferation in these transfected cells was determined using CCK-8 assays. Error bars, SD. n = 3. *p<0.05, **p<0.01, ****p<0.0001 by Student’s t-test. Supplementary Fig. 4. (A) FOXD1 overexpression MDA231 in combination with SCH772984 (0, 1.25, 2.5 and 5 μM, 12 h) were subjected to western blotting assays. (B) FOXD1 overexpression MDA231 in combination with SCH772984 (0, 1.25, 2.5 and 5 μM, 12 h) were subjected to transwell migration assays. Scale bar, 250 μm. Error bars, SD. n = 3. ***p<0.001 by Student’s t test. (C) Western blotting analyses of E-cadherin, N-cadherin, Vimentin, and GAPDH expression in MDA231 with FOXD1 overexpression alone or in combination with SCH772984 (5 μM, 12 h). (D) MDA231 cells with FOXD1 overexpression were treated with SCH772984 (0, 0.3125, 0.625, 1.25, 2.5 and 5 μM) for 12 hours, and the OD450 was measured by CCK-8 assay. Error bars, SD. n = 3. ****p<0.0001 by one-way ANOVA. (E) The predicted model of the RalA-ANXA2-Src ternary interaction. (F) RalA-KO MDA231 cells transfected with constituently inactivated (G26A) or activated (G23V) RalA mutant respectively, were subjected to western blotting assays. For RalA-GTP assays, cells were harvested and subject to RalBP1-RBD pulldown assays to determine RalA-GTP level. Pulldowns were analyzed by immunoblotting with anti-RalA.Additional file 2. Predicted binding sites through JASPAR database, and the sequences of the constructed Luciferase activity reporter assays.Additional file 3. The potential binding partners of RalA identified by immunoprecipitation-LC-MS.Additional file 4: Supplementary Table 1. List of top 5 candidates of RalA-interacting proteins that were identified by co-immunoprecipitation and MS. Supplementary Table 2. ZDOCK used to predict the binding sites of RalA and ANXA2. Supplementary Table 3. The sequences of the primers. Supplementary Table 4. The antibodies applied in this study. | true | true | true |
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PMC9558422 | Yang Duan,Jianjun Li,Sujun Qiu,Songjia Ni,Yanlin Cao | TCF7/SNAI2/miR-4306 feedback loop promotes hypertrophy of ligamentum flavum | 12-10-2022 | Ligamentum flavum hypertrophy,TCF7,SNAI2,miR-4306 | Background Hypertrophy of ligamentum flavum (HLF) is the mainly cause of lumbar spinal stenosis (LSS), but the precise mechanism of HLF formation has not been fully elucidated. Emerging evidence indicates that transcription factor 7 (TCF7) is the key downstream functional molecule of Wnt/β-catenin signaling, which participated in regulating multiple biological processes. However, the role and underlying mechanism of TCF7 in HLF is still unclear. Methods We used mRNAs sequencing analysis of human LF and subsequent confirmation with RT-qPCR, western blot and immunohistochemistry to identified the TCF7 in HLF tissues and cells. Then effect of TCF7 on HLF progression was investigated both in vitro and in vivo. Mechanically, chromatin immunoprecipitation, dual-luciferase reporter assays, and rescue experiments were used to validate the regulation of TCF7/SNAI2/miR-4306 feedback loop. Results Our results identified for first time that the TCF7 expression was obviously elevated in HLF tissues and cells compared with control, and also found that TCF7 expression had significant positive correlation with LF thickness and fibrosis score. Notably, TCF7 inhibition suppressed the hyper-proliferation and fibrosis phenotype of HLF cells in vitro and ameliorated progression of HLF in mice in vivo, whereas TCF7 overexpression promoted hyper-proliferation and fibrosis phenotype of HLF cells in vitro. Our data further revealed that TCF7 interacted with SNAI2 promoter to transactivated the SNAI2 expression, thereby promoting hyper-proliferation and fibrosis phenotype of HLF cells in vitro. Furthermore, miR-4036 negatively regulated by SNAI2 could negatively feedback regulate TCF7 expression by directly binding to TCF7 mRNA 3’-UTR, thus inhibiting the hyper-proliferation and fibrosis phenotype of HLF cells in vitro. Conclusions Our study demonstrated that TCF7 inhibition could suppress HLF formation by modulating TCF7/SNAI2/miR-4306 feedback loop, which might be considered as a novel potential therapeutic target for HLF. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03677-0. | TCF7/SNAI2/miR-4306 feedback loop promotes hypertrophy of ligamentum flavum
Hypertrophy of ligamentum flavum (HLF) is the mainly cause of lumbar spinal stenosis (LSS), but the precise mechanism of HLF formation has not been fully elucidated. Emerging evidence indicates that transcription factor 7 (TCF7) is the key downstream functional molecule of Wnt/β-catenin signaling, which participated in regulating multiple biological processes. However, the role and underlying mechanism of TCF7 in HLF is still unclear.
We used mRNAs sequencing analysis of human LF and subsequent confirmation with RT-qPCR, western blot and immunohistochemistry to identified the TCF7 in HLF tissues and cells. Then effect of TCF7 on HLF progression was investigated both in vitro and in vivo. Mechanically, chromatin immunoprecipitation, dual-luciferase reporter assays, and rescue experiments were used to validate the regulation of TCF7/SNAI2/miR-4306 feedback loop.
Our results identified for first time that the TCF7 expression was obviously elevated in HLF tissues and cells compared with control, and also found that TCF7 expression had significant positive correlation with LF thickness and fibrosis score. Notably, TCF7 inhibition suppressed the hyper-proliferation and fibrosis phenotype of HLF cells in vitro and ameliorated progression of HLF in mice in vivo, whereas TCF7 overexpression promoted hyper-proliferation and fibrosis phenotype of HLF cells in vitro. Our data further revealed that TCF7 interacted with SNAI2 promoter to transactivated the SNAI2 expression, thereby promoting hyper-proliferation and fibrosis phenotype of HLF cells in vitro. Furthermore, miR-4036 negatively regulated by SNAI2 could negatively feedback regulate TCF7 expression by directly binding to TCF7 mRNA 3’-UTR, thus inhibiting the hyper-proliferation and fibrosis phenotype of HLF cells in vitro.
Our study demonstrated that TCF7 inhibition could suppress HLF formation by modulating TCF7/SNAI2/miR-4306 feedback loop, which might be considered as a novel potential therapeutic target for HLF.
The online version contains supplementary material available at 10.1186/s12967-022-03677-0.
Lumbar spinal canal stenosis (LSCS) is the most common spinal disease in elderly patients [41], and hypertrophy of ligamentum flavum (HLF) is considered to be a major cause of LSCS [27, 42]. There is currently no particularly effective conservative treatment to delay or reverse the HLF-induced LSCS except surgical decompression. Surgical removal of the hypertrophic ligamentum flavum can achieve spinal decompression, but not only the risks and postoperative complications of surgery are particularly prominent but also many patients with underlying diseases (such as diabetes, hypertension and hyperlipidemia) are intolerant to surgery [21, 37, 43]. Although fibrosis have been proved to be the key pathological feature of HLF, the precise mechanism of the pathology of LF fibrosis has not been fully elucidated [32]. Therefore, investigating molecular pathways associated with LF fibrosis will provide insight into HLF mechanisms and identify novel targets for prevention and treatment of HLF-induced LSCS. Transcription factor is a DNA binding proteins that can recognize specific DNA sequences to activate or inhibit gene transcription [15]. Studies have proved that abnormal expression of transcription factor is closely related to the occurrence and development of many human diseases [7, 29]. The TCF/LEF transcription factor family can bind to the WRE region within the promoter sequence or enhancer sequence of the target gene, thereby promoting or inhibiting transcription of the target gene [14]. Transcription factor 7 (TCF7, also known as TCF1) is one of the members of the TCF/LEF transcription factor family and participates in the transcriptional regulation of Wnt/β-catenin signal [1, 3]. Emerging evidence has shown that TCF7 is involved in tumorigenesis and development [2, 35, 44], sepsis-induced renal injury [39], heart development [40], and cardiac hypertrophy [26]. However, the roles and underlying mechanism of TCF7 in HLF have not been clarified. Extensive evidence has shown that TCF7 is negatively regulated by microRNAs (miRNAs) [12, 28]. MiRNAs is a class of non-coding single-stranded RNA molecules with a length of about 19–25 nucleotides encoded by endogenous genes, which participate in the regulation of post-transcriptional gene expression in plants and animals [19]. Current studies have been demonstrated that dysregulated miRNAs play an important role in the pathogenesis of HLF [43]. For example, Li P et al. have demonstrated that miR-10396-3p is significantly decreased in the mechanical stress (MS)-induced HLF and overexpressing miR-10396-3p inhibits MS-induced HLF by targeting the inhibition expression of IL-11 [17]. Ma et al. reported that delivering the two miRNAs (miR-146a-5p and miR-221-3p) to LF cells markedly suppressed fibrosis and hypertrophy of LF in vitro and vivo [20]. Our preliminary analysis found that miR-4306 has a potential binding site with TCF7 and negatively regulates TCF7 expression in HLF cells. Previous study have shown that miR-4306 is downregulated in HLF tissues, and miR-4306 expression in HLF tissues were markedly negatively associated with the ratio of LF/spinal canal area [22]. These studies showed that miR-4306 might be involved in the pathogenesis of HLF, but the specific biological function of miR-4306 in the pathogenesis and development of HLF still remains unclear. In the current study, we identified the TCF7 is significantly upregulated in HLF tissues and cells by integrating analysis of RNA-sequencing, bioinformatics analysis and validation experiments. Functional experiments demonstrated that TCF7 promoted hyperplasia and fibrosis of the HLF cells in vitro and in vivo. Moreover, our data demonstrated that TCF7 promoted SNAI2 expression by directly activating transcription SNAI2, and further SNAI2 inhibited miR-4306 expression by directly binding the promoter of miR-4306. Finally, our data revealed that miR-4036 negatively regulated by SNAI2 negative feedback regulated TCF7 expression by directly binding to TCF7 mRNA 3′-UTR, thus inhibiting the hyper-proliferation and fibrosis phenotype of HLF cells in vitro. Collectively, our results demonstrated not only an important role of TCF7/SNAI2/miR-4306 signaling in regulating HLF, but also provide a strong theoretical rational for developing new drugs to prevent and treat HLF.
This study was approved by the Institutional Research Ethics Committee of the Zhujiang Hospital of Southern Medical University. A total of 30 LF tissues samples, including hypertrophied and non-hypertrophied LF tissues, were collected from patient under-going lumbar spine surgery in Zhujiang Hospital of Southern Medical University. The hypertrophied LF tissues (> 4 mm thickness) were obtained from patient with LSCS due to LF hypertrophy, and non-hypertrophied LF tissues (≤ 4 mm thickness) were obtained from age- and gender-matched lumbar disc herniation (LDH) patient without LF hypertrophy as control. All enrolled patients were excluded from diseases such as cancer, heart disease, kidney disease, rheumatism and autoimmune diseases. All patients underwent magnetic resonance imaging scan to confirm the thickness of the LF before surgery, and all LF samples were obtained from the anatomical region (L4/5). Fibrosis score was assessed by Masson's trichrome staining according to previously report [38]. Informed consent was obtained from each patient prior to this study. Patient information in this study is summarized in Additional file 5: Table S1.
Total RNAs were extracted from three independent samples of hypertrophied or non- hypertrophied LF using TRIzol reagent (Invitrogen) according to the manufacturer’s recommended protocol, and the RNA quantity was assessed with a NanoDrop ND-2000 spectrophotometer (NanoDrop Technologies). After purifying the mRNA using RiboZero Magnetic Gold Kit, the cDNA libraries were constructed for the KAPA Stranded RNA-Seq Library Prep kit (Illumina, Inc.) according to the manufacturer’s instructions. Subsequently, we used Agilent 2100 and qPCR to assess the quality and quantification of the cDNA library. Finally, the RNA-sequencing was performed by Next-Generation Sequencing with an Illumina HiSeq Xten platform. Clean data were obtained from the raw data by removing reads containing adapters, reads containing over 10% poly N, and low-quality reads, which were aligned to the specified reference genome (Homo sapiens. GRCh38, NBCI) to obtain the mapped data. The differentially expressed mRNAs between hypertrophied LF tissues and non- hypertrophied LF tissues were performed using EBseq R package. The fold changes (FCs) ≥ 2 or − 2 and false discovery rates (FDRs) < 0.05 served as the screening criteria to get differentially expressed mRNA.
According to our previously described method [4], LF cells were isolated and cultured from the LF tissues of patients with LSCS or LDH. Briefly, the obtained LF samples were cut into small pieces and digested for 2 h at 37 °C using Dulbecco’s modified Eagle’s medium (DMEM, Gibco) with 0.2% type I collagenase (Gibco), then seeded on to cell culture dish and incubated with DMEM containing 10% fetal bovine serum (FBS, Gibco) and 1% penicillin/streptomycin (Invitrogen). The isolated cells were observed for fibroblast morphology and identified the expression of specific markers [collagen I (1:100, #72026, Cell Signaling Technology) and Vimentin (1:500, ab16700, Abcam)] by immunofluorescence staining. Subsequent experiments were conducted using cells from the third passage to forth passage of LF cells.
The adenovirus of TCF7 overexpression/knockdown or SNAI2 overexpression/knockdown were constructed by Genechem (Nanjing, China). The adenovirusl particles of miR-4306 mimic/inhibitor and negative control (NC) mimics/inhibitor were obtained from Ribobio Inc. (Guangzhou, Guangdong, China). All cells were infected with the adenovirus according the manufacturer’s instructions, and the infection efficiency was verified by real-time quantitative PCR (RT-qPCR) or Western blotting analyses. All shRNA and miR-4306 mimics/inhibitor sequences are listed in Additional file 6:Table S2.
Total RNA from the cells or tissues sample was extracted using Trizol (Invitrogen, Carlsbad, CA). Reverse transcription and RT-qPCR for miR-4306 were carried out using miRNA 1st Strand cDNA Synthesis Kit (MR101-01, Vazyme) and miRNA Universal SYBR qPCR Master Mix (MQ101-01, Vazyme) on a LightCycler®96 (Roche). Reverse transcription and RT-qPCR for the mRNAs were performed as described in our previous studies [4].U6 small nuclear RNA and GAPDH were used as an internal control for miR-4306 and mRNAs, respectively. The relative RNA expression of genes was calculated according to the Ct (2−ΔΔCt) method. All experiments were performed in triplicate. All specific primers sequence in study are listed in Additional file 7:Table S3.
The nuclear protein extraction was performed using the Nuclear and Cytoplasmic Protein Extraction Kit (Beyotime, Shanghai, China) according to the protocol of manufacturer, and then subjected to western blotting analysis. Western blotting was conducted as described in our previous studies [4]. Primary antibodies antibody information is as follows: cleaved Caspase-3 (1:500, ab32042, Abcam), Bax (1:1000, ab182733, Abcam), Bcl-2 (1:500, ab182858, Abcam), TCF7 (1:1000, #2203, Cell Signaling Technology), SNAI2 (1:1000, #9585, Cell Signaling Technology), collagen I (1:1000, ab260043, Abcam), collagen III (1:1000, ab7778, Abcam), MMP2 (1:500, ab181286, Abcam), MMP13 (1:1000, ab39012, Abcam), TGF-1β (1:1000, ab215715, Abcam), and GAPDH (1:1000, ab8245, Abcam).
Cell proliferation ability was detected using a Cell Proliferation Reagent Kit I (MTT, Sigma-Aldrich) according to the manufacturer’s recommended protocol. Absorbance values were measured at the wavelength of 490 nm. All experiments were performed in three to five biological duplicates.
Cells apoptosis was measured by flow cytometry using Annexin V-FITC/propidine iodide (PI) double-staining kit (Abcam) according to the manufacturer’s instructions. All experiments were performed in three biological duplicates.
A chromatin immunoprecipitation (ChIP) assay was carried out using the ChIP assay kit (ab500, Abcam) according to the manufacturer’s instructions. Briefly, the following antibodies were used to immunoprecipitate cross-linked protein-DNA complexes: rabbit anti-TCF7 (1:50, #2203, Cell Signaling Technology, USA), rabbit anti-SNAI2 (1:50, #9585, Cell Signaling Technology, USA), and normal rabbit IgG (1:50, #2729, Cell Signaling Technology, USA). After cross-linked protein-DNA complexes to free DNA, the immunoprecipitated DNA was purified for RT-qPCR analyses with specific primers.
For validation of transcription factor interactions with target genes, the TCF7-binding motif in the promoter region of SNAI2 and the SNAI2-binding motif in the promoter region of miR-4306 were predicted through JASPAR (http://jaspar.genereg.net/). According to the predicted results, different truncated plasmid of SNAI2 or miR-4306 promoter was co-transfected with corresponding transcription factors plasmid into 293 T cells. For the verification of interaction between miR-4306 and TCF7, the wild type or mutant type of TCF7 3′-UTR (containing the binding site of miR-4306) was cloned into the luciferase vector, and then transfected into 293 T cells together with miR-4306 mimics or the negative control (NC mimics), respectively. Transfer after 24 h, luciferase activities were assessed using a Dual Luciferase Assay Kit (Promega, Madison, WI, USA) in accordance with the manufacturer’s instructions. The relative luciferase activities were calculated by normalizing the signal value of Renilla luciferase to Firefly luciferase, and then compared with the negative control.
RNA immunoprecipitation (RIP) experiments were performed with a Magna RIP™ RNA-Binding Protein Immunoprecipitation Kit (Millipore, Billerica, MA) according to the manufacturer’s instructions. AGO2 antibody ((Millipore, Billerica, MA, USA)) or negative control IgG antibody (Millipore, Billerica, MA, USA) was used for RIP. Co-precipitated RNAs were finally extracted with RNeasy Mini Kit (QIAGEN, China) for RT-qPCR to demonstrate the presence of the binding targets.
All animal experimental protocols were approved by the Ethics Committee for Animal Research of the Zhujiang Hospital of Southern Medical University (Guangzhou, China). All mice purchased from the Experimental Animal Center of Southern Medical University were 8-week-old C57BL/6 male mice. The mice model with HLF was constructed by the hydrophobic characteristics of mice according to the previously described [45, 46]. In brief, the mice were placed in a beaker with 5 mm of animal water at the bottom to induce a bipedal standing posture. The mice were maintained in a bipedal standing posture for 6 h a day with an interval of 2 h of free activity, and the above operations were continued for 8 weeks to construct the HLF mice model. The control mice were placed in a same condition as the mice with HLF model except for the bottom without animal water. To verify the therapeutic effect of silencing TCF7 on the mouse HLF model, 20 mice were randomly assigned to the control group, HLF model group, HLF + AAV-shNC group, and HLF + AAV-shTCF7 group. After six weeks of bipedal induction, we made a longitudinal skin incision in the mouse lumbar spine, and removed the dorsal paravertebral muscle from the spinous processes and laminae to expose the L5/6 LF under a surgical microscope, thereby AAV-shNC or AAV-shTCF7 (1 × 1012 vg/ml, 3 µl) from Hanbio Biotechnology (Shanghai, China) was injected into L5/6 LF in anesthetized mice with a microinjector (NF36BV 36GA, NanoFil, United States). After 4 weeks of AVV injection, mice were euthanized and L5/6 vertebrae were collected to obtain LF tissue for later histological analyses and molecular biological analyses. Histological analyses were performed to measure the area of the LF.
hematoxylin and eosin (H&E) staining and Elastica van Gieson (EVG) staining were performed to measure the area of the LF and degree of LF fibrosis, respectively. The LF samples from mice or humans were fixed overnight with 4% paraformaldehyde (Beyotime, shanghai, China), paraffin-embedded, and cut into slices (4 μm). After dewaxing and dehydration, the slices were performed by H&E kit (Beyotime, shanghai, China) or EVG kit (JianChen, Nanjing, China) according to the manufacturer’s instructions. Quantitative analyses of the LF areas and degree of LF fibrosis (the ratio of elastic fibers to collagen fibers) were obtained using ImageJ software (NIH, United States). Each sample was detected three times, and the average value was taken.
Immunohistochemical staining was conducted using Histostain®-SP Kits according to the manufacturer’s instructions. In brief, the LF samples from humans were fixed overnight with 4% paraformaldehyde (Beyotime, shanghai, China), paraffin-embedded, and then cut into slices with 4 μm thickness. After dewaxing and antigen retrieval, the slices were organization background closed using serum blocking reagent. Then these slices were incubated with TCF7 primary antibodies (1:200, #2203, Cell Signaling Technology) and β-catenin (1:100, ab16051, Abcam) overnight at 4 °C. Subsequently, these sections were incubated with the respective secondary antibodies (Proteintech) at room temperature. Immunohistochemical results were visualized using a Zeiss microscope (Carl Zeiss Meditec AG, Jena, Germany) and then analyzed by ImageJ software (NIH, United States).
Results are presented as the means ± SD. All the statistical analyses were performed using the GraphPad Prism 6.0 (GraphPad Software, La Jolla, USA). Statistical significance for comparisons between two groups were analyzed using Student’s t-test, and statistical significance for comparisons among more than two group was analyzed using one-way ANOVA. The p < 0.05 was considered as significant difference.
To explore the underlying mechanism of HLF, the mRNA sequencing was performed by in the HLF tissues and non-HLF tissues. HLF tissue or non-HLF tissue has been identified by MRI and histopathology (Fig. 1A). The results of RNA sequencing analysis showed that a total of 848 mRNAs were differentially expressed between the HLF tissues and non-HLF tissues, of which 407 were up-regulated and 441 down-regulated in HLF tissues (Fig. 1B). Then we intersected the differential mRNA with a currently known transcription factor, and found that the six transcription factor (TCF7/CDX1/FOSL1/FOSB/FOXM1/EGR1) in HLF tissues significantly higher than those in non-HLF tissues, and five transcription factor (LMO3/NR2F2/RARB/TBX2/NOTCH3) significantly downregulated (Fig. 1C). Subsequently, KEGG analysis of the above differential transcription factors showed that they were mainly enriched in WNT signaling pathway, Notch signaling pathway, and IL-17 signaling pathway (Fig. 1D). The Wnt/β-catenin pathway signaling has been shown to propagates the initiation and progression of HLF [22], and TCF7 is essential for the typical WNT/β-catenin pathway [44]. However, the relationship between TCF7 and HLF pathogenesis is unclear and needs further study. The clinical samples were expanded to verify the mRNA expression of TCF7 in the above pathways in the non-HLF tissues and HLF tissues. The results of the RT-qPCR indicated that the mRNA expression of TCF7 in HLF tissue was significantly higher than that in non-HLF tissue (Fig. 1E), which was consistent with the mRNA sequencing results. In addition, the results of the IHC also demonstrated that the protein expression of TCF7 and β-catenin in HLF tissues was significantly increased compared with that of in non-HLF tissue (Fig. 1F). Moreover, the correlation analysis revealed that the mRNA expression of TCF7 were significantly positively correlation with LF thickness and fibrosis score (Fig. 1G). In addition, the cells isolated from the HLF tissues or non-HLF tissues were identified as LF cells by the observation of cell morphology and immunofluorescence detection of LF makers expression (Additional file 1: Fig. S1), and the results showed that the isolated cells had a typical LF cells phenotype and uniformly expressed of LF cells markers (collagen I and Vimentin), suggesting that the isolated cells is the high purity of the LF cells. Then the mRNA expression of TCF7 was measured in HLF cells and non-HLF cells by RT-qPCR, and the results indicated that TCF7 expression was significantly increased in HLF cells compared with that of in non-HLF cells (Fig. 1I). Together, these data indicated that TCF7 was markedly upregulated in HLF tissue and cells, and increased TCF7 in HLF tissues associated with LF thickness and fibrosis.
To explore whether TCF7 participates in the biological function of HLF cells, we analyzed the effect of overexpressing or silencing TCF7 (Fig. 2A) on viability, apoptosis, and fibrosis in HLF cells. The cell viability was detected using the CCK-8 assay, and the results showed that overexpression of TCF7 significantly promoted viability of HLF cells, whereas knockdown of TCF7 resulted in the opposite result (Fig. 2B). Then cell apoptosis was measured by using the flow cytometry and western blot. The results of flow cytometry indicated that overexpressing TCF7 inhibited apoptosis ratios of HLF cells, whereas knockdown of TCF7 promoted apoptosis ratios of HLF cells (Fig. 2C and D). Consistent with the results of flow cytometry, the results of western blot demonstrated that overexpression of TCF7 in HLF cells involved in inhibition of Bax and cleaved caspase-3 protein expression and activation of Bcl-2 protein expression, whereas knockdown of TCF7 resulted in the opposite result (Fig. 2E). Furthermore, to confirmed the relationship between the TCF7 expression and fibrosis in HLF cells, western blot was used to assess the effect of overexpressing or silencing TCF7 on the expression of fibrosis-related proteins (Collagen I, Collagen III, MMP13, MMP2, and TGF-β1) in HLF cells. The results of western blot revealed that overexpression or knockdown of TCF7 enhanced or suppressed the expression of fibrosis-related proteins (Collagen I, Collagen III, MMP13, MMP2, and TGFβ), respectively (Fig. 2F), suggesting TCF7 promoted fibrogenesis in HLF cells. Together, the above data demonstrated that TCF7 enhanced the proliferation, anti-apoptosis, and fibrosis in HLF cells.
Current studies have shown that the AAV vector system is a promising delivery vehicle of gene therapy because of its safe and long-term efficacy [23, 33]. In order to further confirm the role of the TCF7 in LF, we evaluated the therapeutic effect of TCF7 knockdown on mice with HLF by in situ injection of AAV-shNC or AAV-shTCF7. The results of HE staining and EVG staining indicated that LF area and the ratio of collagen fibers to elastic fibers significantly increased in the bipedal standing-induced HLF mice (Fig. 3A and B), which were consistent with the previous studies in humans and animals [30, 45, 46], suggesting that the mouse HLF model was successfully constructed in the study. The results of western blot demonstrated that the administration of the AAV-shNC had no effect on the high expression of TCF7 in mouse HLF tissues, while the administration of the AAV-shTCF7 significantly inhibited TCF7 expression in mouse HLF tissues (Fig. 3C and D). Further our data showed that no significant difference was observed in the LF area between the HLF mouse and HLF mouse treated with AAV-shNC (Fig. 3A and B), indicating that the administration of the AAV-shNC had no effect on HLF. Compared with the HLF mouse treated with AAV-shNC, the administration of the AAV-shTCF7 obviously decreased LF area and the ratio of collagen fibers to elastic fibers (Fig. 3A and B), suggesting that administration of the AAV-shTCF7 inhibited hypertrophy and fibrosis of LF induced by bipedal standing posture in mice. Moreover, the expression levels of apoptosis-related proteins (Bax, Bcl-2, and cleaved caspase-3) and fibrosis-related proteins (Collagen I, Collagen III, MMP13, MMP2, and TGFβ1) were detected by western blot in LF tissues of mice. The results indicated that the protein expression of the Bax and cleaved caspase-3 was decreased and the protein expression of Bcl-2, Collagen I, Collagen III, MMP13, MMP2, and TGFβ1 was increased in mice with HLF compared with that of in mice with non-HLF, and the above phenomena were reversed by the administration of the AAV2-shTCF7 (Fig. 3C, E, F, and G). Together, our data revealed that TCF7 knockdown could restrain the hypertrophy and fibrosis of LF in bipedal standing mouse model.
To further elucidate the underlying mechanism by which TCF7 promotes LF fibrosis, the TRRUST ver.7.3 (https://www.grnpedia.org/trrust/result.php) database and JASPAR database (https://jaspar.genereg.net/search?advanced=true) were used to predict the promoters of the SNAI2 genes. The results showed that promoter region of the SNAI2 contained three TCF7 binding sites (Fig. 4A). While the results of RT-qPCR and western blot showed that overexpressing TCF7 markedly increased the mRNA and protein expression of SNAI2 in HLF cells, while silencing TCF7 displayed the opposite effects (Fig. 4B). These results implied that TCF7 might bind to the SNAI2 promoter to positively regulate SNAI2 expression in HLF cells. ChIP assay confirmed that TCF7 can directly associate with the SNAI2 promoters, and observed successful recruitment of TCF7 by binding sites #1 rather than binding sites #2 and #3 (Fig. 4C). Consistently, the results of luciferase reporter assay showed that overexpressing TCF7 significantly increased SNAI2 promoter-driven reporter activity HLF cells (Fig. 4D), further confirming TCF7 directly targets SNAI2 and activates its transcription expression. Next, we explored whether the overexpression of TCF7 enhanced the proliferation and fibrosis by activation of SNAI2 in HLF cells. The increased viability of HLF cells induced by overexpressing TCF7 was also dramatically abrogated by the silencing SNAI2 (Additional file 2: Fig. S2A and Fig. 4E). Furthermore, the results of flow cytometry showed that silencing SNAI2 significantly decreased the inhibitory effect of TCF7 overexpression on the apoptosis rate (Fig. 4F). Consistently, the results of western blot indicated that silencing SNAI2 significantly reversed the effect of TCF7 overexpression on the protein expression of apoptosis-related markers (Bax, cleaved caspase-3, and Bcl-2) in HLF cells (Additional file 2: Fig. S2B). These results demonstrated that TCF7 inhibited apoptosis of HLF cells by upregulating SNAI2. Furthermore, the increased protein expression of fibrosis-related proteins (Collagen I, Collagen III, MMP13, MMP2, and TGFβ1) induced by overexpressing TCF7 was also markedly reversed by the silencing SNAI2 (Fig. 4G). Moreover, our data also showed that overexpressing SNAI2 significantly reversed the inhibition effect of TCF7 knockdown on the cell viability, anti-apoptosis, and the protein expression of fibrosis-related markers (Additional file 3: Fig. S3), indicating that silencing TCF7 inhibit the proliferation and fibrosis of HLF cells by downregulating SNAI2. Interestingly, we also found that the overexpressing SNAI2 in HLF cells significantly enhanced the cell viability, anti-apoptosis, and the protein expression of fibrosis-related markers (Additional file 3: Fig. S3 and Fig. 4E–G). Whereas silencing SNAI2 in HLF cells remarkably decreased the cell viability, anti-apoptosis, and the protein expression of fibrosis-related markers compared with vector group (Additional file 3: Fig. S3). Together, our data suggested that activation of SNAI2 contributes to TCF7-mediated LF hypertrophic and fibrotic phenotype in vitro.
As shown in Fig. 4 and Additional file 3: Fig. S3, SNAI2 is involved in the malignant biological phenotype of HLF cells, such as abnormal proliferation and fibrosis. However, the molecular mechanism by which SNAI2 regulated the malignant biological phenotype of HLF cells remained unclear. As a transcription factor, SNAI2 could inhibit the transcription by directly binding to miRNAs promoters [8, 9, 34]. The TransmiR v2.0 database (http://www.cuilab.cn/transmir) database was used to predict miRNAs that motif of SNAI2 binds to miRNAs promoters, and found that motif of SNAI2 had binding sites with the promoters of three miRNAs (miR-4306, miR-641, and miR-2278). The results of RT-qPCR showed that overexpressing or silencing SNAI2 markedly decreased or increased the miR-4306 expression in HLF cells, but the expression levels of miR-641 and miR-2278 were not regulated by SNAI2 (Fig. 5A). These data suggested that SNAI2 might bind to miR-4306 promoter to negatively regulate miR-4306 expression in HLF cells. To confirmed the binding regions of miR-4306 promoter regulated by SNAI2, two binding sites for SNAI2 motif on miR-4306 promoter region were predicted by the JASPAR database (Fig. 5B). ChIP assay demonstrated that SNAI2 could bind the promoter of miR-4306 directly, and observed successful recruitment of SNAI2 by binding sites #1 or site #2, and the effect of binding site #1 was better than binding site #2 (Fig. 5C). Consistently, the results of luciferase reporter assay showed that overexpressing SNIAI2 significantly decreased miR-4306 promoter-driven reporter activity (Fig. 5D), further confirming SNIAI2 directly targets miR-4306 and activates its transcription expression. Importantly, we found that overexpressing or silencing TCF7 markedly decreased or increased miR-4306 expression, the phenomenon was dramatically abrogated by the silencing or overexpressing SNAI2 (Fig. 5E), suggesting that TCF7 negatively regulated miR-4306 expression by mediating SNAI2 expression. Together, these data demonstrated that SNAI2 positively regulated by TCF7 inhibited the transcription of miR-4306 by binding to the promoter region of miR-4306. Previous studies have shown that TCF7 is negatively regulated by miRNAs [12, 28]. To explore whether miR-4306 negatively regulated TCF7 expression in HLF cells, the RAID and miRDB database were used to predict the interaction between TCF7 and miR-4306. The results showed that TCF7 3’UTR had potential binding sites with miR-4306. And the overexpressing miR-4306 markedly inhibited the mRNA and protein expression of TCF7 in HLF cells, while silencing miR-4306 displayed the opposite effect (Fig. 5F and G). these results suggested that TCF7 may be a target gene of miR-4306 in HLF cells. The relationship between miR-4306 and TCF7 was evaluated through RIP experiments, the results revealed the interaction between miR-4306 and TCF7 (Fig. 5H). Further dual-luciferase reporter assay was used to confirm the specific binding site of miR-4306 and TCF7. The sequence of TCF7 3′-UTR including the miR-4306 binding site (TCF7 3′-UTR-WT) or its corresponding mutation sequence (TCF7 3′-UTR-MTU) was inserted into the psiTM-Check2 luciferase vector, and then co-transfected 293 T cells with NC mimics or miR-4306 mimic and TCF7 3′-UTR-WT plasmids or TCF7 3′-UTR-MTU plasmids, respectively. The results showed that miR-4306 overexpression greatly inhibited the luciferase activity of TCF7 3′-UTR-WT reporter, but luciferase activity of TCF7 3′-UTR-MUT was not significantly impacted by miR-4306 overexpression (Fig. 5I), indicating that miR4306 directly binds to the TCF7 3′-UTR region to regulate TCF7 transcription. In summary, our data demonstrated that SNAI2 enhanced TCF7 expression by transcriptionally inhibiting miR-4306 expression.
It has been reported that miR-4306 is significantly down-regulated in HLF tissues (fold change = − 1.26, P = 0.005), and its expression level was significantly negatively correlated with LF/spinal canal area ratio (LSAR), suggesting that miR-4306 may be involved in the occurrence and development of HLF [22]. However, the role of miR-4306 in HLF cells has not been explored. HLF cells were transfected with miR-4306 mimics or miR-4306 inhibitor to evaluate the effects of miR-4306 on the viability, apoptosis, and fibrosis of HLF cells. We found that overexpressing miR-4306 inhibited viability of HLF cells, this inhibition effect was reversed by overexpressing SNAI2 (Fig. 6A and B). The results of flow cytometry revealed that overexpressing miR-4306 significantly increased the apoptosis ratios of HLF cells, this effect was weakened by overexpressing SNAI2 (Fig. 7C). Consistently, the results of western blot also indicated that overexpressing miR-4306 significantly increased the protein expression of cleaved caspase-3 and Bax and markedly decreased the Bcl-2 protein expression, this phenomenon was reversed by overexpressing SNAI2 (Fig. 6D). Furthermore, the overexpressing miR-4306 significantly decreased the protein expression of fibrosis-related proteins (Collagen I, Collagen III, MMP13, MMP2, and TGFβ1), the inhibition function was also markedly reversed by overexpressing SNAI2 (Fig. 6E). In addition, our data showed that silencing miR-4306 significantly promoted cell viability, anti-apoptosis, and the protein expression of fibrosis-related markers in HLF cells, this phenomenon was weakened by silencing SNAI2 (Additional file 4: Fig. S4). In summary, miR-4036 negatively regulated by SNAI2 inhibited the proliferation and fibrosis of HLF cells.
Although fibrosis is considered as the key pathological feature of HLF, but internal molecular mechanisms has not been fully elucidated. Herein, we confirmed for the first time that TCF7 significantly upregulated in HLF, and the TCF7 expression was remarkably positively correlated with the thickness and fibrosis degree of LF. Moreover, we demonstrated that silencing TCF7 inhibited LF hypertrophy and fibrosis by inhibiting LF cell proliferation, promoting apoptosis, and aggravating ECM degradation in vitro and vivo. Mechanically, our data revealed that augmented TCF7 led to transcriptional activation of SNAI2, and SNAI2 inhibited the transcription of miR-4306 by binding to the promoter region of miR-4306, which in turn promoted the TCF7 expression. Most importantly, we found that inhibition of TCF7/SNAI2/miR-4306 signaling suppressed LF hypertrophy and fibrosis, indicating that targeting TCF7/SNAI2/miR-4306 signaling may be a novel strategy for the prevention and treatment of HLF. Accumulating evidence indicates that TCF7 is a critical function downstream of the typical WNT/β-catenin signaling pathway, which is involved in biological processes of many diseases [2, 18, 44]. A recent study reported that TCF7 expression was elevated in mouse heart tissue after TAC and in cardiomyocytes treated with Ang-II, and inhibition of TCF7 suppressed the occurrence of cardiac hypertrophy [18]. Base on integrating analysis of RNA-sequencing, bioinformatics analysis and validation experiments, we identified for first time that the mRNA and protein expression of TCF7 was significantly increased in HLF tissues and cells. Correlation analysis showed that TCF7 expression had significant positive correlation with LF thickness and fibrosis score, suggesting that TCF7 involved in the HLF development. Then our data demonstrated that TCF7 overexpression significantly induced proliferation and fibrosis of HLF cells. On the contrary, the silencing TCF7 significantly suppressed proliferation and fibrosis of HLF cells in vitro and suppressed the LF fibrosis and hypertrophy in vivo. In addition to proliferation and fibrosis, apoptosis is also involved in the pathological process of HLF, but the role of apoptosis in HLF remains controversial. Several investigators have shown that activation of apoptotic pathways induce cell apoptosis in HLF tissue [6, 24]. However, some researchers have shown that apoptosis is inhibited in HLF tissue. For example, Zhou et al. revealed that inhibition of apoptosis in HLF tissue compared to non-HLF tissue, which manifested as inhibition of apoptosis marker (Bax and cleaved caspase3) expression and reduction of TUNEL-positive cell percentage in human HLF tissue, and reduction cleaved caspase3 expression in the rat model with HLF [47]. At the same time, they showed that LPAR1 significantly upregulated in HLF tissue compared with that in non-HLF tissue, overexpression of LPAR1 improved inhibited apoptosis in LF cells, whereas knockdown of LPAR1 has the opposite effect [47]. Sun et al. demonstrated that upregulated WISP1 in HLF decreased apoptosis of LF cells, which manifested as inhibition of Bax and activation of Bcl-2 [30]. Furthermore, DNMT1-mediated ACSM5 significantly downregulated in LFH tissue, and ACSM5 knockdown inhibited apoptosis of HLF cells in vitro [4]. Like these studies, our data showed that upregulated TCF7 could promoted apoptosis of HLF cells, whereas silencing TCF7 significantly promoted apoptosis of HLF cells in vitro. Thus, these results implied that TCF7 inhibition might be considered as a novel potential therapeutic strategy for HLF. Emerging evidence has demonstrated that dysregulated miRNAs is involved in the occurrence and progression of HLF [22, 43]. Yu et al. identified that miR-221 was down-regulated in HLF tissues, and overexpressing miR-221 inhibited the expression of collagens I and collagens III by sponging TIMP-2, thus inhibiting HLF formation [36]. Sun et al. revealed that miR-21 may play an important role in HLF, upregulation of miR-21 might contribute to the HLF by promoting inflammation and fibrosis via the induction of IL-6 expression [36]. The above studies suggested that miRNAs played pivotal roles in the occurrence and development of HLF, which has aroused great attention of scholars. Notably, previous study have identified that the down-regulation of miR-4306 in HLF tissues is significantly negatively correlated with increased LF/spinal canal area ratio (LSAR) [22], but the role and underlying mechanism of miR-4306 in HLF cells has not been investigated. Herein, we found that overexpression of miR-4306 in HLF cells suppressed cell hyper-proliferation and pro-fibrosis, whereas inhibition of miR-4306 displayed the opposite effect. These results showed that miR-4306 might play an anti-hypertrophy role in HLF. Furthermore, a growing body of research has revealed that miRNA-mediated target gene expression exerted an appreciable promoting or inhibiting HLF progression [5, 17, 31, 36, 43]. We conducted bioinformatics analysis using the RAID and miRDB software and found that TCF7 contained potential binding sequences for miR-4306. The RIP assay and dual luciferase activity assay confirmed that TCF7 was a direct target for miR-4306. Remarkably, a host of studies have shown that miRNAs expressions is regulated by transcription factors (TFs) in gene regulatory networks, and the interaction between TFs and miRNAs can precisely regulate gene expressions to maintain cell homeostasis [25]. The SNAI2 encoded by the SNAI2 gene is an evolutionarily conserved C2H2 zinc finger protein that orchestrates biological processes critical to tissue development and tumorigenesis, and its main role is to facilitate the epigenetic regulation of transcriptional programs [48]. And previous studies have demonstrated that SNAI2 interacts with miRNAs promoters to inhibit its expression and then regulates cell biological functions [8, 9, 34]. Consistent with previous studies, we identified that SNAI2 inhibited the transcription of miR-4306 by directly binding to the promoter region of miR-4306. Moreover, extensive studies have revealed that SNAI2 plays an important role in various cell proliferation and fibrosis processes [10, 11, 13, 16]. However, no studies have investigated the potential biological function of SNAI2 in HLF cells. Our results revealed that SNAI2 overexpression promoted proliferation and fibrosis of HLF cells, and the inhibition of SNAI2 suppressed proliferation and fibrosis of HLF cells, indicating SNAI2 may play pro-hypertrophy roles in LF. Further rescue experiments disclosed that silencing SNAI2 could eliminate the inhibitory effect of overexpression of miR-4306 on the proliferation and fibrosis of HLF cells. Thus, our results revealed that miR-4306 was directly inhibited at the transcriptional level by SNAI2, and thereby promoted the proliferation and fibrosis of HLF cells. In addition, we found that TCF7 directly targets SNAI2 promoter and activates its transcription expression, and activation of SNAI2 contributes to TCF7-mediated LF hypertrophic and fibrotic phenotype in vitro. Therefore, our data revealed that TCF7 promoted HLF formation through mediating the TCF7/SNAI2/miR-4306 feedback loop (Fig. 7).
Taken together, our study is the first to uncovered that TCF7/SNAI2/miR-4306 feedback loop promoted HLF formation by regulating proliferation and fibrosis of HLF cells, which will expand our understanding of the pathogenesis of HLF. More importantly, both in vitro and in vivo experiments implied that interfering with TCF7 could be an effective target for the prevention and treatment of HLF formation.
Additional file 1: Figure S1. Identify the ligamentum flavum (LF) cells. A Pictures showing the morphology of the isolated cells with 1st and 3rd passage from LF tissues. B Identification of the phenotype of cultured LF cells using immunofluorescence staining. Immunofluorescence staining for collagen I and Vimentin in cultured cells.Additional file 2: Figure S2. TCF7 inhibits the apoptosis of HLF cells by upregulating SNAI2. A The mRNA and protein expression of SNAI2 was evaluated by RT-qPCR and Western Blot in HLF cells transfected with vector, TCF7, SNAI2, and TCF7 + shSNAI2. B Western Blot was used to detect the protein expression of apoptosis-related genes (cleaved caspase3, Bax, and Bcl-2) in HLF cells transfected with vector, TCF7, SNAI2, and TCF7 + shSNAI2. shSNAI2, SNAI2 knockdown adenovirus; SNAI2, SNAI2 overexpressed adenovirus; TCF7 overexpressed adenovirus. #P < 0.05, ##P < 0.01, and ###P < 0.001.Additional file 3: Figure S3. Silencing TCF7 inhibits the cell proliferation and fibrosis through downregulating SNAI2 expression in HLF cells. A Western Blot was used to detect the protein expression of SNAI2 in HLF cells transfected with vector, shTCF7, shSNAI2, and shTCF7 + SNAI2. B The proliferation of HLF cells transfected with vector, shTCF7, shSNAI2, and shTCF7 + SNAI2 was determined by CCK-8 assays. C The apoptosis of HLF cells transfected with vector, shTCF7, shSNAI2, and shTCF7 + SNAI2 was determined by flow cytometry assays. D Western Blot was used to detect the protein expression of apoptosis-related genes (cleaved-caspase3, Bax, and Bcl-2) in HLF cells transfected with vector, TCF7, SNAI2, and TCF7 + shSNAI2. E Western Blot was used to detect the protein expression of fibrosis-related genes (collagen I, collagen III, MMP2, MMP13, and TGFβ1) in HLF cells transfected with vector, TCF7, SNAI2, and TCF7 + shSNAI2. shSNAI2, SNAI2 knockdown adenovirus; SNAI2, SNAI2 overexpressed adenovirus; shTCF7 knockdown adenovirus. #P < 0.05, ##P < 0.01, and ###P < 0.001.Additional file 4: Figure S4. The SNAI2 inhibits miR-4306 expression to promote the proliferation and fibrosis of HLF cells in vitro. A RT-qPCR was used to detect the miR-4306 expression in HLF cells transfected with vector, miR-4306 inhibitor, and miR-4306 inhibitor + shSNAI2. B The proliferation of HLF cells transfected with vector, miR-4306 inhibitor, and miR-4306 inhibitor + shSNAI2 was determined by CCK-8 assays. C The apoptosis of HLF cells transfected with vector, miR-4306 inhibitor, and miR-4306 inhibitor + shSNAI2 was determined by flow cytometry assays. D Western Blot was used to detect the protein expression of apoptosis-related genes (cleaved caspase3, Bax, and Bcl-2) in HLF cells transfected with vector, miR-4306 inhibitor, and miR-4306 inhibitor + shSNAI2. E Western Blot was used to detect the protein expression of fibrosis-related genes (collagen I, collagen III, MMP2, MMP13, and TGFβ1) in HLF cells transfected with vector, miR-4306 inhibitor, and miR-4306 inhibitor + shSNAI2. miR inh., miR-4306 inhibitor; SNAI2, SNAI2 knockdown adenovirus. #P < 0.05, ##P < 0.01, and ###P < 0.001.Additional file 5: Table S1. Patients information in this study.Additional file 6: Table S2. The sequences of shRNAs or miR-4306 inhibitor/mimics used in this study.Additional file 7: Table S3. The sequences of all the primer in qRT-PCR. | true | true | true |
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PMC9558598 | Rongbo Wang,Sung-Kwon Moon,Woo-Jung Kim,Sanjeevram Dhandapani,Hoon Kim,Yeon-Ju Kim | Biologically Synthesized Rosa rugosa-Based Gold Nanoparticles Suppress Skin Inflammatory Responses via MAPK and NF-κB Signaling Pathway in TNF-α/IFN-γ-Induced HaCaT Keratinocytes | 30-09-2022 | Nanotechnology-applied materials and related therapeutics have gained attention for treating inflammatory skin diseases. The beach rose (Rosa rugosa), belonging to the family Rosaceae, is a perennial, deciduous woody shrub endemic to northeastern Asia. In this study, R. rugosa-based gold nanoparticles (RR-AuNPs) were biologically synthesized under optimal conditions to explore their potential as anti-inflammatory agents for treating skin inflammation. The synthesized RR-AuNPs were analyzed using field emission-transmission electron microscopy, energy-dispersive X-ray spectrometry, selected-area electron diffraction, and X-ray diffraction. The uniformly well-structured AuNPs showed near-spherical and polygonal shapes. Cell viability evaluation and optical observation results showed that the RR-AuNPs were absorbed by human keratinocytes without causing cytotoxic effects. The effects of RR-AuNPs on the skin inflammatory response were investigated in human keratinocytes treated with tumor necrosis factor-α/interferon-γ (T + I). The results showed that T + I-stimulated increases in inflammatory mediators, including chemokines, interleukins, and reactive oxygen species, were significantly suppressed by RR-AuNP treatment in a concentration-dependent manner. The western blotting results indicated that the RR-AuNP-mediated anti-inflammatory effects were highly associated with the suppression of inflammatory signaling, mitogen-activated protein kinase, and nuclear factor-κB. These results demonstrate that plant extract-based AuNPs are novel anti-inflammatory candidates for topical application to treat skin inflammation. | Biologically Synthesized Rosa rugosa-Based Gold Nanoparticles Suppress Skin Inflammatory Responses via MAPK and NF-κB Signaling Pathway in TNF-α/IFN-γ-Induced HaCaT Keratinocytes
Nanotechnology-applied materials and related therapeutics have gained attention for treating inflammatory skin diseases. The beach rose (Rosa rugosa), belonging to the family Rosaceae, is a perennial, deciduous woody shrub endemic to northeastern Asia. In this study, R. rugosa-based gold nanoparticles (RR-AuNPs) were biologically synthesized under optimal conditions to explore their potential as anti-inflammatory agents for treating skin inflammation. The synthesized RR-AuNPs were analyzed using field emission-transmission electron microscopy, energy-dispersive X-ray spectrometry, selected-area electron diffraction, and X-ray diffraction. The uniformly well-structured AuNPs showed near-spherical and polygonal shapes. Cell viability evaluation and optical observation results showed that the RR-AuNPs were absorbed by human keratinocytes without causing cytotoxic effects. The effects of RR-AuNPs on the skin inflammatory response were investigated in human keratinocytes treated with tumor necrosis factor-α/interferon-γ (T + I). The results showed that T + I-stimulated increases in inflammatory mediators, including chemokines, interleukins, and reactive oxygen species, were significantly suppressed by RR-AuNP treatment in a concentration-dependent manner. The western blotting results indicated that the RR-AuNP-mediated anti-inflammatory effects were highly associated with the suppression of inflammatory signaling, mitogen-activated protein kinase, and nuclear factor-κB. These results demonstrate that plant extract-based AuNPs are novel anti-inflammatory candidates for topical application to treat skin inflammation.
In addition to its many crucial roles, such as storing lipids and water, creating sensation, preventing water and nutrient losses, and controlling body temperature, the skin is an important part of the immune system responsible for the primary defense against various external stimuli and for maintaining tissue homeostasis. However, abnormal or uncontrolled immune responses in the skin tissue induce skin inflammation. Moreover, persistent and pathological inflammatory responses in the skin tissue contribute to the development of inflammatory skin disease (ISD), which is known as dermatitis and includes atopic, allergic, contact, seborrheic, and stasis dermatitis. Particularly, atopic dermatitis is a chronic intractable ISD characterized by eczema, itching (pruritus), redness, lichenification, cracking, and infection. As ISDs are increasing worldwide because of rapid industrialization and environmental pollution, several medications, including topical steroid ointments, oral antihistamines, phototherapy, immunomodulators, and antibiotics, have been used to treat ISDs. However, long-term use of these agents is associated with serious side effects, such as skin thinning, atrophy, fragility, ecchymosis, poor wound healing, vascular expansion, and hormone dysfunction. Therefore, a new approach for developing alternative medications to treat ISDs is urgently required. Recent studies suggested that nanotechnology can be used to prevent and treat inflammatory diseases. Various nano-sized materials, particularly nanoparticles, have been studied to determine their roles in inflammatory responses. These materials can improve bioavailability and drug delivery at the inflammation site while causing few side effects and have a good safety profile. Several researchers have proposed using nanoparticles, such as polymeric nanoparticles, metallic nanoparticles, lipid nanoparticles, and vesicular systems, because of their stable, safe, and target-specific delivery characteristics for treating numerous disorders. In recent years, plant-based metallic nanoparticles produced using green synthesis methods have been explored to optimize the conventional efficacy of the original plants based on their advantages, including their high biocompatibility, low cost, and eco-friendly nature. Nevertheless, further research on metallic nanoparticles synthesized from various types of plants is needed to develop anti-inflammatory candidates. The beach rose (Rosa rugosa, RR), belonging to the family Rosaceae, is a perennial, deciduous woody shrub endemic to northeastern Asia, including Korea, China, and Japan. Beyond its traditional use in ornamentals and aromatics, RR exhibits several pharmacological effects, such as antioxidative, anti-inflammatory, anticancer, and antihypertensive effects. In a nanonization study, Dubey et al. synthesized silver and gold nanoparticles (AuNPs) with mean particle sizes of 12 and 11 nm, respectively, using RR leaf tissue. However, only the synthesis conditions and physiochemical characteristics of the nanoparticles were evaluated, without considering any pharmacological properties. Therefore, the physiological and medicinal characteristics of RR-based nanoparticles should be investigated. This study was conducted to prepare novel AuNPs using RR extracts and identify their physicochemical characteristics. In addition, we examined the effect of RR-based AuNPs (RR-AuNPs) on inflammatory responses in the skin and underlying molecular mechanisms in an inflammation-induced human keratinocyte model.
To establish the optimal biosynthesis conditions, several reaction parameters, including the extract of RR (RRE) concentrations (0.5–4 mg/mL), gold salt concentrations (0.5–2.5 mM), reaction temperatures (50–90 °C), and times (20–50 min), were monitored using ultraviolet–visible (UV–vis) spectrophotometry (Figure 1). The optimal conditions for RR-AuNPs biosynthesis were 3 mg/mL RRE and 2 mM gold salt incubated at 70 °C for 20 min. RR-AuNPs synthesized under optimal conditions had an λmax of 545 nm, whereas RRE and gold salts alone showed no plasmonic absorbance (Figure 2A). The stability of RR-AuNPs is presented in Figure S1. The result reveals that RR-AuNPs were quite stable at room temperature for 30 days after synthesis. Elemental mapping revealed that gold elements (red dots) were uniformly distributed within the nanoparticles, indicating that RR-AuNPs were synthesized into AuNPs without impurities (Figure 2B). The morphological and structural features of RR-AuNPs were observed using a field emission transmission electron microscope. The TEM images showed that RR-AuNPs had predominantly near-spherical and polygonal shapes with a mean diameter of 38.2 ± 3.7 nm (Figure 2C). From the dynamic light scattering (DLS) analysis, we were able to obtain the hydrodynamic size of the nanoparticles. DLS particle analysis revealed that average intensity, volume, and number distributions of RR-AuNPs were 293.0, 104.1, and 72.1 nm, respectively (Figure 2D–F). The crystallographic techniques selected area electron diffraction (SAED) and X-ray diffraction (XRD) were used to identify the crystalline nature of the RR-AuNPs. Four rings (111, 200, 220, and 311) were observed in the crystalline plane of the SAED pattern (Figure 3A) in addition to four diffraction peaks at θ values of 38.26, 44.42, 64.80, and 77.79° [corresponding to the (111), (200), (220), and (300) planes, respectively] shown in the XRD spectrum (Figure 3B), indicating that the RR-AuNPs had a face-centered cubic crystalline structure. Figure 3C shows the high density of the Au peak in the energy-dispersive spectroscopy (EDS) spectrum, indicating that gold was the predominant element in the RR-AuNPs. Additional signals originating from copper were also found in the EDX spectrum because of the use of the grid in EDX analysis. Fourier transform infrared spectroscopy (FT-IR) was performed to identify and compare the surface functional groups of RR-AuNPs and RRE (Figure 3D,E, respectively). The two samples exhibited different absorption patterns. According to the spectral library, the bands observed at 3372.8 and 3358.8 cm–1 in RR-AuNPs and RRE, respectively, are assigned to the phenolic hydroxyl and aliphatic hydroxyl groups. The bands observed at 2932.1 cm–1 in RR-AuNPs and 2929.3 cm–1 in RRE are associated with the C–H stretch of the methylene groups of the protein. The sharp signals from 2361.0 and 2338.9 cm–1 in the RRE correspond to C–H stretching, whereas this peak was faded in the AuNPs. The band at 1714.6 cm–1 for the RR-AuNPs is characteristic of the stretching C=O group. The peaks at 1610.6 cm–1 in RR-AuNPs and the peak at 1608.0 cm–1 in RRE may be due to the presence of C=C of benzene. The signals at 1446.2, 1232.1, and 1105.9 cm–1 in RR-AuNPs and signals at 1445.0, 1346.5, 1228.8, and 1033.9 cm–1 in RRE correspond to the C–H bending vibration, which arises from alkenes and aliphatic amine functional groups. These results indicate that the functional groups of RRE were modified by interactions with the gold salts. The results of FT-IR analysis strongly supported that capping of RRE endowed the synthesized RR-AuNPs with high stability.
Figure 4A shows the total internal reflection scattering (TIRS) microscopy system equipped with differential interference contrast (DIC) images of the RR-AuNPs. As shown in the TIRS image, bright light was generated inside the cells at 1 h after RR-AuNP treatment. At 3 h after treatment, more light was accumulated inside the cells. These results revealed that RR-AuNPs were absorbed by HaCaT cells in a time-dependent manner. A cytotoxicity test was performed to confirm the safety of the RR-AuNPs and RRE. HaCaT cells were treated with equivalent concentrations of RR-AuNPs and RRE for 24 h, and then a conventional 3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and live/dead cell staining were performed. The MTT assay revealed that RR-AuNPs were not significantly cytotoxic at any of the concentrations tested (25–100 μg/mL), whereas RRE exhibited a significant toxic effect at concentrations above 50 μg/mL (Figure 4B). Figure 4C shows a representative image of cells stained with live/dead cell-staining dye, and the quantified results are shown in Figure 4D. The results revealed no significant accumulation of red dots in RR-AuNP-treated cells at all concentrations tested, but the viability of cells treated with RRE at 50 and 100 μg/mL was significantly reduced.
To establish an in vitro skin inflammation model, HaCaT cells were stimulated with T + I. As shown in Figure 5, the qRT-PCR results showed that the gene expression levels of pro-inflammatory chemokines, such as primarily CC motif chemokine ligands (CCLs), including CCL5/regulated upon activation, normal T cell expressed and presumably secreted (RANTES), CCL17/thymus and activation-regulated chemokine (CCL17/TARC), CCL27/cutaneous T cell-attracting chemokine (CCL27/CTACK), CXC motif chemokine ligand 8 (CXCL8)/interleukin 8 (IL-8), and interleukin 6 (IL-6), were significantly upregulated in T + I-treated cells. RR-AuNP treatment significantly decreased the expression of these genes in a concentration-dependent manner. Particularly, RR-AuNP treatment at a high concentration (100 μg/mL) led to greater downregulation of these genes compared to that induced by dexamethasone treatment, which was used as a PC. To verify the inhibitory effects of RR-AuNPs, the secretory levels of IL-6, IL-8, and TARC proteins in the cell culture supernatant were determined using enzyme-linked immunosorbent assay (ELISA). As shown in Figure 6A–C, T + I-induced increases in IL-6, IL-8, and TARC were concentration-dependently decreased by RR-AuNP treatment. Interestingly, RR-AuNP treatment at all concentrations tested exhibited higher inhibitory effects on the three inflammatory mediators than in the PC group. These results demonstrate that RR-AuNPs effectively inhibited skin inflammation-associated mediators at the gene expression and protein secretion levels. Next, we investigated intracellular reactive oxygen species (ROS) production in T + I-induced HaCaT cells. Figure 6D shows representative images of cells stained with ROS staining dye, along with the quantified results. The results showed that HaCaT cells produced excessive intracellular ROS following T + I stimulation alone, and RR-AuNPs significantly decreased the production of toxic biomarkers in a dose-dependent manner. Specifically, cells treated with RR-AuNPs at a high concentration (100 μg/mL) showed higher ROS inhibitory effects compared to those in the PC group. This result suggests that RR-AuNP-induced suppression of intracellular oxidative stress is associated with anti-inflammatory responses in skin cells.
To identify the intracellular mechanism underlying RR-AuNP-induced inhibition of the skin inflammatory response, mitogen-activated protein kinase (MAPK) (Figure 7A) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) (Figure 7B) were evaluated using western blotting. In HaCaT cells, T + I stimulation significantly elevated the phosphorylated levels of three MAPKs (p38 kinase, ERK, and JNK) but did not alter their total levels. The T + I-induced increase in phosphorylated MAPKs was downregulated by RR-AuNP treatment in a concentration-dependent manner. Similar tendencies were observed for NF-κB p65. However, T + I treatment significantly upregulated the phosphorylation level of IκBα and markedly downregulated the total protein level. The increased expression of p-IκBα by T + I stimulation was significantly downregulated by RR-AuNP treatment in a concentration-dependent manner. These findings indicate that T + I-induced skin inflammation was markedly suppressed by RR-AuNP treatment via the MAPK and NF-κB pathways.
We explored the biosynthesis, characteristics, and anti-inflammatory activities of RR-AuNPs to investigate their potential for industrial application as anti-inflammatory agents. First, monitoring of various synthetic conditions of the nanoparticles showed that RR-AuNPs were successfully synthesized under optimal conditions (Figure 1). The synthesized RR-AuNPs were uniformly well-structured with near-spherical and polygonal shapes. Interestingly, the particle sizes of the RR-AuNPs differed (Figure 2C–F, respectively), possibly because of the difference in the analytical principles between different analyses. The intensity weighted distribution shows how different-size particles are detected from a fit to the autocorrelation function of the measured scattering. Based on the intensity, results can therefore be highly sensitive to very small numbers of aggregates or dust. The number and volume distribution show the relative proportion of the number of different-size particles and the volume occupied by different-size particles. As DLS analysis reveals the nanoparticle size based on the whole size of the conjugates or their hydrodynamic size in the colloids, the obtained sizes are generally noticeably larger than those obtained using TEM analysis. The structure and conformation of the surface functional groups of RR-AuNPs were coordinated compared with those of RRE (Figure 3D,E). In 2010, Dubey et al. reported that the biologically synthesized AuNPs have mostly hexagonal shapes and a mean size of 11 nm. Compared with RR-AuNPs (mean size of 38.2 nm), the smaller size of their AuNPs may have resulted from the shorter synthesis time (10 min). RR-AuNPs were absorbed into the HaCaTs without causing cytotoxic effects (Figure 4A). Compared with the cytotoxic effect induced by RRE, RR-AuNPs may be safer, although they act inside the cells following absorption. Next, the anti-dermatitis effect of RR-AuNPs was evaluated using T + I-stimulated HaCaT cells. Many previous studies have demonstrated that the pathogenesis of ISDs is triggered and motivated by keratinocyte-secreting chemokines, including CCL5/RANTES, CCL17/TARC, CCL22/macrophage-derived chemokine, CCL27/CTACK, and CXC8/IL-8, which are involved in recruiting leukocytes to inflammatory skin tissue. Particularly, the inflammatory cytokines TNF-α and IFN-γ, which are mainly secreted by macrophages and T cells, can stimulate the production and secretion of inflammatory chemokines in epidermal keratinocytes. T + I-stimulated inflammatory responses in keratinocytes are accompanied by intracellular ROS accumulation and their extracellular secretion. In addition to the basic role of forming a physical barrier by differentiating into corneocytes to protect the body, epidermal keratinocytes trigger and induce the progression of ISDs. Accordingly, numerous studies have applied in vitro models using T + I-induced epidermal keratinocytes to explore their potential as anti-inflammatory agents in the skin. RR-AuNPs considerably downregulated the expression of T + I-induced inflammatory genes, including RANTES, TARC, CTACK, IL-6, and IL-8 (Figure 5). Additionally, the secretion levels of IL-6, IL-8, and TARC proteins were significantly suppressed following pretreatment with RR-AuNPs (Figure 6A–C). These results indicate that RR-AuNPs can effectively inhibit inflammatory responses in keratinocytes. In addition, T + I-induced mitochondrial ROS production was considerably decreased by RR-AuNP treatment (Figure 6D), indicating that oxidative stress-associated damage during inflammatory responses can be alleviated by RR-AuNP treatment. T + I-stimulated inflammatory responses in keratinocytes mediate the generation of intracellular ROS, leading to the activation of inflammatory signaling cascades. Based on these results, we further explored the mechanism of action underlying the anti-inflammatory efficacy exerted by RR-AuNPs. MAPK and NF-κB signaling are major signaling pathways in various inflammatory responses, including skin dermatitis. In addition to its crucial function in regulating cell survival, such as differentiation, proliferation, mitosis, and death, activation of MAPK signaling contributes to the pathogenesis of diverse diseases, including chronic inflammation. Thus, searching for substances that can regulate compromised MAPK signaling may be useful for developing targeted therapies for inflammatory disorders. Three distinct MAPKs, ERK, JNK, and p38, are key targets for exploring the progression of diverse diseases. The NF-κB signaling pathway is closely involved in the pathogenesis of ISDs. The NF-κB subfamily comprises five transcription factors: NF-κB1 (p105/p50), NF-κB2 (p100/p52), RelA (p65), RelB, and c-Rel. Under physiological conditions, the activity of NF-κB proteins is inhibited by their inhibitor proteins, including IκBα, IκBβ, and IκBγ. Upon stimulation, the inactive form of the NF-κB/IκB complex in the cytoplasm is activated, followed by phosphorylation and release of IκB from the complex, translocation of NF-κB into the nucleus, and transcription initiation of inflammatory genes. We measured the phosphorylation levels of three MAPKs (p38, ERK, and JNK) and two NF-κB signaling-related molecules (IκBα and p65) to identify the mechanism of action underlying RR-AuNP-mediated suppression of the T + I-stimulated inflammatory reaction. As shown in Figure 7, RR-AuNPs considerably suppressed the T + I-stimulated activation of MAPK and NF-κB signaling molecules. Taken together, our results demonstrate that RR-AuNPs can be taken up by keratinocytes without causing cytotoxicity and suppress the production of T + I-stimulated inflammatory mediators (chemokines, cytokines, and ROS) by downregulating both MAPK and NF-κB signaling. To the best of our knowledge, this is the first study to demonstrate the physicochemical and anti-inflammatory properties of AuNPs prepared from RR.
We biologically synthesized uniformly shaped RR-AuNPs with a mean diameter of 38.2 nm using RR (RR-AuNPs) and gold salts under optimal synthesis conditions. The synthesized RR-AuNPs were absorbed by HaCaT cells without causing significant cytotoxic effects in HaCaT cells treated with RR-AuNPs compared to in cells treated with only RRE. Thus, the cytotoxic effect of RRE may be decreased via its conversion into RR-AuNPs, suggesting that nanonization using green synthesis is a useful technique for decreasing its cytotoxic effect in keratinocytes. In addition, the RR-AuNPs noticeably inhibited the generation of inflammatory mediators in T + I-induced HaCaT cells; these effects were associated with the downregulation of the MAPK and NF-κB signaling pathways. Our study provides valuable preliminary results on plant extract-based AuNPs and can be utilized to develop anti-inflammatory candidates for topical application. Nevertheless, possible toxicity following long-term treatment with RR-AuNPs should be evaluated in an animal model in further studies.
Branch tissue of wild RR was harvested from northern Gyeonggi, adjacent to the demilitarized zone in Korea. The plant was identified by Dr. J. K. Kim, a senior researcher at Gyeonggido Business and Science Accelerator, Gyeonggi Biocenter (Suwon, Korea). A voucher specimen was deposited in the department described above. Dried branches were extracted with five volumes (w/v) of 50% ethanol at 20–25 °C for 3 days. The extracts were filtered through a polyester filter cloth (20 μm; Hyundai Micro, Anseong, Korea) and evaporated using a rotary evaporator (Buchi Korea, Inc., Gwangmyeong, Korea) to remove the ethanol. The remaining solution was lyophilized using a freeze drier (Ilshin Biobase, Daejeon, Korea) for 3 days to yield a 50% ethanol extract of RR (RRE) with an extraction yield of 19.6%.
The biosynthesized RR-AuNPs were prepared from RRE as described previously. In addition, four reaction parameters were examined to optimize the biosynthesis of the RR-AuNP, including the RRE and tetrachloroauric(III) acid trihydrate (gold salts; Sigma-Aldrich, St. Louis, MO, USA) concentrations, reaction temperature, and reaction time. After the reaction of RRE and the gold salts, the color change was evaluated and absorbance at 300–800 nm was determined visually and using a UV–vis spectrophotometer (Agilent Technologies, Santa Clara, CA, USA), respectively. The synthesized RR-AuNPs were centrifuged at 13,475g for 10 min and washed five times with deionized water along with repeated centrifugation. The purified particles were lyophilized using a freeze drier (Ilshin Biobase) to obtain powdered RR-AuNPs.
The morphological, crystallographic, and elemental characteristics of the RR-AuNPs were measured using a high-resolution transmission electron microscope (JEOL JEM-2100F, Tokyo, Japan) equipped with EDS and SAED. The purity and crystalline nature of the RR-AuNPs were measured using an XRD (Bruker, Billerica, MA, USA). The intensity, volume, and number distribution of particle sizes were determined using a DLS particle analyzer (Otsuka Electronics, Shiga, Japan). The chemical surface of the RR-AuNPs was examined using FT-IR (PerkinElmer, Waltham, MA, USA) at wavelengths of 500–4000 cm–1.
HaCaT human keratinocytes (CLS GmbH, Eppelheim, Germany) were maintained in Dulbecco’s modified Eagle’s medium (DMEM; Gibco, Grand Island, NY, USA) supplemented with 10% fetal bovine serum (Gibco) and 100 U penicillin/100 μg/mL streptomycin (Gibco) in a humidified incubator with 5% CO2/95% air. The cells were added to a 96-well plate (SPL Life Sciences, Pocheon, Korea) at a density of 1 × 104 cells/well. After stabilization for 24 h, the medium was replaced with serum-free DMEM containing various concentrations of RR-AuNPs. Intracellular uptake and localization of RR-AuNPs were confirmed using a TIRS microscopy system equipped with DIC at 1 and 3 h. TIRS microscopy was performed using an upright Olympus BX51 microscope (Olympus Optical Co., Ltd., Tokyo, Japan). The equipment of DIC included a polarizer, beam-splitting modified Wollaston prism, beam-recombining modified Wollaston prism, and analyzer above a polished dove prism. The illumination light was provided by a 100 W halogen lamp. All images were obtained using MetaMorph 7.5 software (Universal Imaging, Sunnyvale, CA, USA). The cytotoxic effect of RR-AuNPs was evaluated at 24 h after RR-AuNP treatment using an MTT (Sigma) method according to a previous report and live/dead cell staining assay (Invitrogen, Carlsbad, CA, USA) using a fluorescence microscope (Leica Microsystems, Wetzlar, Germany) according to the manufacturer’s recommendations.
HaCaT cells were plated in 6-well plates (SPL Life Sciences) at a density of 2 × 105 cells/well. After stabilization for 24 h, the medium was changed to serum-free DMEM containing treatments for 1 h, and a recombinant protein mixture containing 10 ng/mL TNF-α (210-TA-100/CF; R&D Systems, Minneapolis, MN, USA) and 10 IFN-γ (285-IF-100/CF; R&D Systems) (T + I) was added to the cells to generate an in vitro inflammation model.
After T + I stimulation for 24 h, ROS was detected using an ROS detection assay kit (ab139476; Abcam, Cambridge, UK) and a fluorescence microscope (Leica Microsystems) according to the manufacturer’s recommendations.
After T + I stimulation for 24 h, the cells were rinsed twice with phosphate-buffered saline (PBS; pH 7.2). Total RNA extraction, reverse transcription of RNA into cDNA, and quantitative real-time PCR (qRT-PCR) were performed as described previously. The sequences of the gene-specific primers (Macrogen, Seoul, Korea) are listed in Table S1.
After T + I stimulation for 24 h, the cell culture supernatant was collected to quantify inflammatory cytokines according to the manufacturer’s recommendations. Detailed information on the quantitative ELISA kits used in this study is provided in Table S2. The cells were rinsed twice with PBS and extracted using RIPA lysis buffer (Thermo Fisher Scientific, Waltham, MA, USA) containing protease inhibitors (GenDEPOT, Katy, TX, USA). The collected proteins were normalized using a bicinchoninic acid protein assay kit (Thermo Fisher Scientific), separated on a 10% sodium dodecyl sulfate-polyacrylamide gel, and transferred to a polyvinylidene fluoride membrane (Thermo Fisher Scientific) according to a previously described method. Western blotting was used to evaluate NF-κB and MAPK signaling molecules as previously reported. The antibodies used in this study are listed in Table S3, which were detected using a chemiluminescent imaging system (WSE-6370 LuminoGraph III Lite; ATTA, Tokyo, Japan) and quantified using ImageJ software (https://imagej.nih.gov/ij/; NIH, Bethesda, MD, USA).
All experiments were performed in triplicate, and the data are expressed as the mean ± standard deviation. Student’s t-test was used for statistical comparison between two groups, and the results were considered significant at p < 0.05, p < 0.01, and p < 0.001. | true | true | true |
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PMC9558760 | Xin Liu,Shuda Chen,Jianfeng Tu,Wenwei Cai,Qiuran Xu | HSP90 inhibits apoptosis and promotes growth by regulating HIF-1α abundance in hepatocellular carcinoma | 03-10-2022 | HSP90 inhibits apoptosis and promotes growth by regulating HIF-1α abundance in hepatocellular carcinoma
Int J Mol Med 37: 825-835, 2016; DOI: 10.3892/ijmm.2016.2482 Subsequently to the publication of the above paper, the authors contacted the Editorial Office to explain that they had found several mistakes in Figs. 1B, 2B, 6B and 7B in their paper. The PCR results shown in Fig. 1B, the flow cytometric results in Figs. 2B and 6B, and the immunohistochemistry results in Fig. 7B were inadvertently chosen incorrectly when these images were selected from the pool of raw data. However, the authors retained access to their original data, and were able to re-assemble the data in these figures as they had intended. Consequently, the corrected versions of Figs. 1, 2, 6 and 7, containing the replacement data for Figs. 1B, 2B, 6B, and 7B, are shown below and on the next two pages. It should be emphasized that the errors that were made in assembling Figs. 1B, 2B, 6B and 7B did not have a major effect on either the results reported or the conclusions reached in this article. The authors are grateful to the Editor of International Journal of Molecular Medicine for allowing them the opportunity to publish this Corrigendum, and all of the authors agree to the publication of this Corrigendum. The authors sincerely apologize for their mistakes and regret any inconvenience that these errors may have caused. | true | true | true |
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PMC9558813 | 35831117 | Yui WAKE,Christopher A. VAKULSKAS,Steve E. GLENN,Takehito KANEKO | Amount of Cas9 protein introduced into mouse embryos via electroporation affects the genome-editing rate | 14-07-2022 | CRISPR/Cas,Electroporation,Embryos,Genome editing,Mouse | Genetically engineered animals can be produced quickly using genome editing technology. A new electroporation technique, technique for animal knockout system by electroporation (TAKE), aids in the production of genome-edited animals by introducing nucleases into intact embryos using electroporation instead of microinjection. It is difficult to confirm nuclease delivery into embryos after electroporation using the conventional TAKE method. We previously reported the successful visualization of fluorescently-labeled tracrRNA in embryos after electroporation Cas9 paired with the crRNA:tracrRNA-ATTO550 duplex. However, the amount of fluorescence signal from labeled tracrRNA in embryos did not correlate with the genome editing rate of the offspring. This study examined the visualization of Cas9 protein in embryos after electroporation and its correlation with the genome editing rate of the offspring using a fluorescent Cas9 fusion protein. The fluorescent Cas9 protein was observed in all embryos that survived following electroporation. We found that the efficiency of Cas9 protein delivery into embryos via electroporation depended on the pulse length. Furthermore, we demonstrated that the amount of fluorescent Cas9 protein detected in the embryos correlated with the genome editing efficiency of the embryos. These data indicate that the TAKE method using fluorescently-labeled nucleases can be used to optimize the delivery conditions and verify nuclease delivery into individual embryos prior to embryo transfer for the efficient production of genome-edited animals. | Amount of Cas9 protein introduced into mouse embryos via electroporation affects the genome-editing rate
Genetically engineered animals can be produced quickly using genome editing technology. A new electroporation technique, technique for animal knockout system by electroporation (TAKE), aids in the production of genome-edited animals by introducing nucleases into intact embryos using electroporation instead of microinjection. It is difficult to confirm nuclease delivery into embryos after electroporation using the conventional TAKE method. We previously reported the successful visualization of fluorescently-labeled tracrRNA in embryos after electroporation Cas9 paired with the crRNA:tracrRNA-ATTO550 duplex. However, the amount of fluorescence signal from labeled tracrRNA in embryos did not correlate with the genome editing rate of the offspring. This study examined the visualization of Cas9 protein in embryos after electroporation and its correlation with the genome editing rate of the offspring using a fluorescent Cas9 fusion protein. The fluorescent Cas9 protein was observed in all embryos that survived following electroporation. We found that the efficiency of Cas9 protein delivery into embryos via electroporation depended on the pulse length. Furthermore, we demonstrated that the amount of fluorescent Cas9 protein detected in the embryos correlated with the genome editing efficiency of the embryos. These data indicate that the TAKE method using fluorescently-labeled nucleases can be used to optimize the delivery conditions and verify nuclease delivery into individual embryos prior to embryo transfer for the efficient production of genome-edited animals.
Genetically engineered mice, including genome-edited strains, have recently been used to study human diseases [1,2,3]. These mice are generally produced by the introduction of nucleases into pronuclear stage embryos via microinjection [4]. However, the microinjection method is inconvenient because of the high skill level required to operate the micromanipulator. Furthermore, nucleases must be successively injected into embryos using a micromanipulator. Recently, genome-edited animals have been produced by a new technique using electroporation, known as the technology for animal knockout system by electroporation (TAKE). It could produce simply and effectively genome-edited animals using zinc-finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), and clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated (Cas) systems [5, 6]. This method can effectively introduce nucleases into intact embryos with a high survival rate using a new three-step electrical pulse program [7]. Microinjection can be used to reliably introduce nucleases via a direct injection into embryos using a thin glass pipette [4]. However, it is difficult to confirm nuclease delivery into embryos after electroporation using the conventional TAKE method. We have previously demonstrated the successful visualization of nucleases in embryos following electroporation using fluorescently-labeled tracrRNA as part of the guide RNA [8]. In that study, the genome-editing rate had significantly increased with increasing pulse length; however, no significant differences were observed in the average fluorescence intensities at the different pulse lengths. This suggests that the amount of Cas9 protein, not fluorescent tracrRNA, delivered into the embryos affects the genome editing rate of embryos after electroporation. This study examined the visualization of Cas9 protein in embryos after electroporation and its correlation with the genome editing rate of the offspring using a fluorescent Cas9 fusion protein.
C57BL/6J male and ICR female mice (Charles River Laboratories Japan Inc., Yokohama, Japan) were used in this study. Males older than 11 weeks and females aged 8–16 weeks were used as sperm and oocyte donors, respectively. ICR female mice, aged 10–16 weeks, were used as recipients for embryo transfer. All animals were maintained in an air-conditioned (temperature, 23 ± 3°C; humidity, 50 ± 10%) and light-controlled room (lights on from 0700 to 1900 h). Animal Research Committee of Iwate University approved that all animal care and procedures performed in this study conformed to the Guidelines for Animal Experiments of Iwate University.
Pronuclear stage embryos were produced using in vitro fertilization. Sperms collected from the cauda epididymis of C57BL/6J male mice were pre-cultured in human tubal fluid (HTF) medium [9] for 1 h at 37°C under 5% CO2 to induce capacitation. Superovulation was induced in ICR females via an intraperitoneal injection of 10 IU/body pregnant mare serum gonadotropin (ASKA Animal Health Co., Ltd., Tokyo, Japan), followed by an intraperitoneal injection of 10 IU/body human chorionic gonadotropin (hCG; ASKA Animal Health Co., Ltd.) 48 h later. Cumulus-oocyte complexes were collected from the oviducts of females 16 h after hCG injections. The cumulus-oocyte complexes and capacitated sperms (1 × 105 cells/ml) were then co-cultured at 37°C under 5% CO2. Pronuclear stage embryos were collected in fresh HTF medium 5 h after insemination. Embryos were maintained at 37°C under 5% CO2 until electroporation.
Cas9-green fluorescence protein (GFP) (cat no.10008100), crRNA, tracrRNA (cat no.1072533), and ATTO550-labeled tracrRNA (cat no. 1075928) were obtained from Integrated DNA Technologies Inc. (Coralville, IA, USA). crRNA was designed to target the tyrosinase gene of C57BL/6 mice (5′-GGGTGGATGACCGTGAGTCC-3′), which participates in melanin biosynthesis [10]. This gene is specifically expressed in retinal pigment epithelial cells of the eye, choroidal melanocytes, and hair follicle melanocytes in mammals [11]. It is possible to discriminate the results of genome editing from the eye color of offspring derived from C57BL/6 × ICR embryos without genetic analysis by knocking out the tyrosinase gene. The nuclease solution for embryo electroporation contained 200 ng/μl Cas9-GFP, 15 μM crRNA, 15 μM tracrRNA or a mixture solution with 7.5 μM tracrRNA and 7.5 μM tracrRNA-ATTO550 in Opti-MEM (Thermo Fisher Scientific Inc., MA, USA) [8] was prepared just before electroporation.
Nucleases were introduced into pronuclear stage embryos 22–24 h after hCG injection using the TAKE method [7]. A super electroporator NEPA21 (NEPA GENE Co., Ltd., Chiba, Japan) was used to introduce the nucleases. The nuclease solution (5 μl) was placed between metal plates of 1 mm gap electrodes on a glass slide (CUY501P1-1.5; NEPA GENE Co., Ltd.). Embryos were placed in a line between the electrodes. The poring pulse was set to voltage: 40 V, pulse length: 0.5 or 3.5 msec, pulse interval: 50 msec, number of pulses: 4, decay rate: 10%, and polarity: +. The transfer pulse was set to voltage: 15 V, pulse length: 50 msec, pulse interval: 50 msec, number of pulses: 5, decay rate: 40%, and polarity: +/−. Embryos were then discharged and transferred into the HTF medium. The nuclease solution was exchanged for two operations to avoid dilution. Embryos placed in the nuclease solution without electroporation were used as controls.
The fluorescence of electroporated embryos was observed using an inverted microscope (Figs. 1 and 3
Two-cell embryos were transferred into the oviducts of pseudopregnant ICR females that were mated with vasectomized males the day before embryo transfer. The number of offspring was counted 19 days after embryo transfer. Genome editing of the offspring was estimated based on the differences in eye color (Fig. 5
The experiments were repeated 3 times for each group. The fluorescence intensity of the embryos was analyzed using the Student’s t-test. The development and genome editing rates of the embryos after electroporation were analyzed using Fisher’s exact test.
Nucleases were introduced into pronuclear stage embryos using the TAKE method with a pulse length of either 0.5 msec or 3.5 msec for the poring pulse. After electroporation, 99% of the embryos survived, and all surviving embryos showed GFP fluorescence at either pulse length. No GFP fluorescence was observed in embryos placed in the nuclease solution without electroporation (Fig. 1). No significant differences were observed in the development of embryos to offspring or the rate of knockout in offspring using a pulse length of either 0.5 msec (52 and 81%, respectively) or 3.5 msec (40 and 97%, respectively) (Fig. 2A). The fluorescence intensity of each embryo electroporated using a 0.5 or 3.5 msec poring pulse was measured. Significant differences were observed in the mean gray values of fluorescence intensity using a pulse length of 0.5 msec (40.8) or 3.5 msec (43.1) (Fig. 2B). To confirm the introduction of tracrRNA, including crRNA, with Cas9-GFP in the embryo, the nuclease solution containing 200 ng/μl Cas9-GFP, 15 μM crRNA, and mixture solution with 7.5 μM tracrRNA and 7.5 μM tracrRNA-ATTO550 in Opti-MEM was introduced into pronuclear stage embryos by TAKE method using 0.5 or 3.5 msec pulse length for the poring pulse. After electroporation using a pulse length of 0.5 or 3.5 msec, 98 or 96% of embryos had survived. All embryos that survived had fluorescence of GFP and ATTO550 after electroporation using a pulse length of 0.5 or 3.5 msec (Fig. 4A). Significant differences were observed in the development of embryos to offspring and in the rate of knockout after electroporation using a pulse length of 0.5 msec (61 and 77%, respectively) or 3.5 msec (42 and 96%, respectively) (Fig. 4A). The mean gray values of fluorescence intensity of GFP in embryos electroporated using a pulse length of 0.5 msec (26.5) or 3.5 msec (27.3) also showed significant differences (Fig. 4B).
The TAKE method is an easy and simple method for producing genome-edited animals [5,6,7]. This method has been widely applied to genome editing using the ZFN, TALEN, and CRISPR-Cas systems in mice [12,13,14,15,16,17,18]. This method has also been used to produce genome-edited strains in other animals [19, 20]. It is difficult to confirm nuclease entry into embryos after electroporation using the conventional TAKE method. This problem was overcome by the successful visualization of nucleases in embryos after electroporation using fluorescently-labeled tracrRNA as part of the guide RNA [8]. This study further examined the visualization of the Cas9 protein in embryos after electroporation using a Cas9-GFP fusion protein. We demonstrated successful visualization of Cas9 protein in embryos after electroporation (Figs. 1 and 3). In addition, all embryos surviving electroporation showed fluorescence (Figs. 2A and 4A). In a previous study using tracrRNA-ATTO550, no significant differences were observed in the average fluorescence intensity at different pulse lengths, although the genome-editing rate had significantly increased with increasing pulse length [8]. However, this study demonstrated that the average fluorescence intensity of Cas9 protein and genome editing rate had significantly increased with increasing pulse length (Figs. 2B and 4B). These results indicate that the efficiency of Cas9 delivery into embryos via electroporation depends on the time duration of the use of poring pulse. Furthermore, it was suggested that the genome editing efficiency of embryos depend on the amount of Cas9 protein introduced into embryos via electroporation. In this study, the fluorescence intensity of the embryos was directly measured after electroporation. Fluorescence was observed in the cytoplasm; however, there was clear localization of fluorescence in the male and female pronuclei of embryos. The Cas9 protein used in this study had a nuclear localization signal. In microinjection method, nuclease solution, including nucleases, is directly injected into the pronuclei of embryos for efficient genome editing [21]. Horii et al. reported that injection of RNA into the cytoplasm was the most efficient method in terms of the number of viable blastocyst stage embryos, full-term pups generated, and knockout efficiency [22]. This study also demonstrated that Cas9-GFP with a nuclear localization signal introduced into the cytoplasm of embryos promptly transitioned into the pronuclei. This study demonstrated that the TAKE method can be reliably used to introduce nucleases into mouse embryos as all electroporated embryos had observable fluorescence that correlated with genome-editing rates. Furthermore, fluorescently labeled nucleases can be used to optimize delivery conditions and verify nuclease delivery into individual embryos prior to embryo transfer for the efficient production of genome-edited animals.
The authors declare no conflicts of interest. C.A.V. and S.E.G. are employees of Integrated DNA Technologies (IDT), which sold the reagents used in this study. C.A.V. holds equity in Danaher Corporation, which owns IDT. | true | true | true |
PMC9558858 | 36217828 | Haichuan Wang,Yu Zhang,Li Yan,Qiang Lv,Jie Lu,Bei Yun | Analysis of TRIM27 prognosis value and immune infiltrates in hepatocellular carcinoma | 11-10-2022 | Biomarker,tripartite motif-containing 27,hepatocellular carcinoma,immune infiltrates,prognosis | Up-regulation of tripartite motif-containing 27 (TRIM27) in varieties of tumors found that TRIM27 advanced tumor metastasis and invasion. Nevertheless, the relation of TRIM27 and immune infiltration in hepatocellular carcinoma (HCC) and the prognostic value of TRIM27 expression is unknown. We assessed TRIM27 association with immune infiltrates and the prognostic value of TRIM27 in HCC. From the Cancer Genome Atlas, we obtained TRIM27 transcriptional expression profiles of HCC and normal tissues. Using the Human Protein Atlas to evaluate the expression TRIM27, protein-protein interaction (PPI) networks were produced using the STRING database. Functional enrichment analysis was performed by using the clusterProfiler package. The tumor immune estimation resource was used to determine the relation of TRIM27 expression and immune infiltrates. We found that the expression of TRIM27 was up-regulated in HCC tissues compared with adjacent normal tissues. High TRIM27 expression correlated with high pathologic stage and high TNM stage. The receiver operating characteristic curve of TRIM27 area was 0.946. Kaplan–Meier analyses showed poor prognosis in HCC patients with high expression of TRIM27. Correlation analysis suggested that the expression of TRIM27 was related to immune infiltrates and tumor purity. This study indicated in HCC up-regulated the expression of TRIM27 is correlated to poor survival and immune infiltration. TRIM27 is an underlying target of immune therapy and is an underlying biomarker for poor prognosis in HCC. | Analysis of TRIM27 prognosis value and immune infiltrates in hepatocellular carcinoma
Up-regulation of tripartite motif-containing 27 (TRIM27) in varieties of tumors found that TRIM27 advanced tumor metastasis and invasion. Nevertheless, the relation of TRIM27 and immune infiltration in hepatocellular carcinoma (HCC) and the prognostic value of TRIM27 expression is unknown. We assessed TRIM27 association with immune infiltrates and the prognostic value of TRIM27 in HCC. From the Cancer Genome Atlas, we obtained TRIM27 transcriptional expression profiles of HCC and normal tissues. Using the Human Protein Atlas to evaluate the expression TRIM27, protein-protein interaction (PPI) networks were produced using the STRING database. Functional enrichment analysis was performed by using the clusterProfiler package. The tumor immune estimation resource was used to determine the relation of TRIM27 expression and immune infiltrates. We found that the expression of TRIM27 was up-regulated in HCC tissues compared with adjacent normal tissues. High TRIM27 expression correlated with high pathologic stage and high TNM stage. The receiver operating characteristic curve of TRIM27 area was 0.946. Kaplan–Meier analyses showed poor prognosis in HCC patients with high expression of TRIM27. Correlation analysis suggested that the expression of TRIM27 was related to immune infiltrates and tumor purity. This study indicated in HCC up-regulated the expression of TRIM27 is correlated to poor survival and immune infiltration. TRIM27 is an underlying target of immune therapy and is an underlying biomarker for poor prognosis in HCC.
Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer. The treatment methods for HCC patients have improved and include systemic therapy, trans-hepatic arterial chemotherapy, liver transplantation, and surgical resection. Nevertheless, the 5-year survival of patients with HCC is nonetheless unfavorable, second lowest only to pancreatic carcinoma. Early-stage patients may benefit from surgical resection, while chemotherapy is the first choice for patients with advanced and unresectable disease. Patients in early stage may obtain benefit from excision, whereas for advanced and unresectable disease patients, chemotherapy is the first choice. Advanced HCC patients with early intrahepatic recurrence after surgery present poorer prognoses, especially in the presence of vascular invasion. Recent studies have reported that the use of immunotherapy for patients with liver cancer is especially promising. Therefore, identifying prognostic biomarkers and therapeutic targets of HCC immunotherapy is essential. The tripartite motif (TRIM) protein family members are individualized by the existence of three domains: a coiled-coil region, a domain containing B-box domains and a RING finger domain; the TRIM proteins C-terminal region is highly variable. The TRIM27 protein, a member of the TRIM family, is appeared in most human organs. Recent studies have found a cancer-promoting role of TRIM27 in various cancer types, including lung cancer, endometrial cancer, and breast cancer. These evidences are consistent with the correlation between TRIM27 expression and the natural history of cancer, indicate the role of this gene and its coded outcomes in cancer development. Nevertheless, in HCC, the TRIM27 prognostic value and its expression has not been fully elucidated. In addition, in HCC, the relationship between TRIM27 and tumor immune infiltration remains indistinct. In our study, we assessed the expression of TRIM27 in a variety of human cancers. We discovered that TRIM27 is up-regulated in HCC, and the up-regulation of TRIM27 is related to adverse clinical features and risk factors in HCC patients. We found that TRIM27 overexpression is correlation with poor survival of HCC patients. This study ulteriorly found in HCC the TRIM27 diagnostic and prognostic value and the relationship between immune infiltrates and TRIM27.
We downloaded from The Cancer Genome Atlas (TCGA) database (https://genome-cancer.ucsc.edu/) about TRIM27 corresponding clinical information and transcriptional expression data. After normalizing the data, analyze the differential expression of TRIM27 was used by the R package limma (3.6.3).
The HPA (https://www.proteinatlas.org/) includes protein expression data from tumor tissues and normal tissues. We contrasted TRIM27 protein expression in HCC tissue and normal liver tissue by the HPA, the expressions of cancers/pericarcinomas with similar ages and the same location and quantity.
GEPIA (http://gepia.cancer-pku.cn/) is a network tool based on TCGA and Genotype Tissue Expression data for normal and cancer gene expression profiles and interactive analysis. Survival analysis of HCC patients was performed by GEPIA, including analyses of disease-free survival (DFS) and overall survival (OS). Log-rank p value <.05 was considered as statistically significant.
Online database of STRING version 11.0 (https://www.string-db.org/) to search for interacting genes to construct PPI networks. We performed a STRING search for co-expressing genes of TRIM27 and constructed a PPI network with an interaction score >0.4. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of co-expressing genes were performed using the “clusterProfiler” package and visualized by the “ggplot2” package.
Tumor immune estimation resource database (https://cistrome.shinyapps.io/timer/) is an online resource for the systematic analysis of immune infiltration in various cancer types. We used TIMER to determine the relationship between the expression level of TRIM27 and the level of immune cell infiltration in HCC. p value <.05 was considered as statistically significant.
All statistical analyses were performed with R (V 3.6.3) (https://www.r-project.org/) and R package ggplot2 (V 3.3.3) was used to visualize expression differences. The differences between HCC tissues and adjacent normal tissues were determined by Mann–Whitney U-test and Paired t-test. Using the ROC package Kaplan–Meier to perform ROC curve in order to detect the cutoff value of TRIM27. To evaluate the effect of TRIM27 on survival through log-rank tests with the survminer package (https://CRAN.R-project.org/package=survminer).
We assessed TRIM27 mRNA expression pattern in different cancer types using TCGA. As shown in Figure 1(a), in 16 of the 33 cancer types, markedly up-regulated of TRIM27 mRNA in tumor tissues compared with that in non-tumor tissues. Using data from TCGA and HPA to analyze the expression of TRIM27 showed that TRIM27 is more expressed in liver tumors than in hepatocyte. As shown in Figure 1(b), paired data analyses indicated that the mRNA expression of TRIM27 in HCC tissues was higher than that expression in adjacent normal hepatocyte (p < .001). Analysis of unpaired data also indicated that the mRNA expression of TRIM27 was more up-regulated in HCC tissues than that expression in adjacent normal hepatocyte (Figure 1(c), p < .001). HPA indicated that immunohistochemical staining of TRIM27 protein was higher in HCC tissues than that expression in normal hepatocyte (Figure 1(d)). These results revealed in HCC tissues that expressions of TRIM27 are up-regulated both in the mRNA and protein.
We next evaluated the correlation between TRIM27 mRNA expression with clinicopathological features in HCC patients from TCGA. Up-regulated expression of TRIM27 was associated with high T stage (p = .001) and high pathological stage (p = .001). Also, we observed no significant correlation between TRIM27 expression and other clinicopathological features, such as M stage (p = 1.000), N stage (p = .361), age (p = .232), body mass index (p = .463), gender (p = .658), AFP (p = .445), and Ishak fibrosis score (p = .240), as shown in Table 1. These results indicated that TRIM27 is associated with high TNM stage and high pathological stage. Therefore, TRIM27 may serve as a biomarker for poor prognosis in HCC.
We conducted ROC curve analysis of the distinction of HCC samples and normal samples for investigating the value of TRIM27 expression. And the results indicated that the AUC value of TRIM27 is 0.946 (95% CI: 0.923–0.970) (Figure 2(a)). With a cutoff value of 3.786, the specificity and sensitivity of TRIM27 are 91.4 and 88.0%, respectively. These findings showed that a promising biomarker of TRIM27 to distinguishing HCC tissues from normal tissues.
Using HCC samples from the GEPIA database, we conducted survival analysis of TRIM27 expression including two prognostic indicators of OS and RFS. In OS analysis, increased TRIM27 expression in HCC was significantly shorter, as shown in Figure 2(b) (p < .01). In RFS analysis, increased TRIM27 expression in HCC had an unfavorable prognosis (Figure 2(c), p < .05). These findings suggest TRIM27 may be an unfavorable prognostic biomarker for HCC patients.
We construct the PPI network and function annotations conducted by GO analyses, STRING database and KEGG. Figure 3(a) shows TRIM27 network and 10 co-expression genes of TRIM27. Changes in TRIM27 biological processes were related to mitotic nuclear division, nuclear division, and organelle fission, as shown in Figure 3. The relationships between TRIM27 expression and expressions of the 10 co-expressed genes in HCC from TCGA are shown in Figure 3(c)–(i).
Immune infiltration plays an important part about the formation and evolution of HCC. By the TIMER database, the study next examined the correlation between TRIM27 expression and seven forms of tumor-infiltrating immune cells. The SCNA defined using TIMER included arm-level deletions, diploid/normal, arm-level gain, and high amplification. TRIM27 SCNA (arm-level gain, high amplification) affected the levels of infiltrating B cells, macrophages, and neutrophils (Figure 4(a)). We next evaluated the relationship between TRIM27 expression and immune cell infiltration level. TRIM27 expression was positively related to macrophage (r = 0.245, p = 4.51e-06), CD4+ T cell (r = 0.254, p = 1.83e-06), neutrophil (r = 0.265, p = 5.92e-07), B cell (r = 0.195, p = 2.68e-04), and dendritic cell (r = 0.261, p = 1.07e-06) infiltration (Figure 4(b)). These results showed that in HCC, TRIM27 might be a part in immune infiltration.
In tumor immune escape, CTLA-4 and PD-1/PD-L1 are important primary immune checkpoints. Premeditating the latent oncogenic role of TRIM27 in HCC. We next examined the correlation between TRIM27 and CTLA-4 or PD-1, PD-L1 in HCC. TRIM27 expression was positively related to CTLA-4 and PD-1, PD-L1 in HCC, adjusted by purity, as shown in Figure 5(a)–(c). The findings indicate that TRIM27-mediated HCC oncogenic might through tumor immune escape.
HCC is a highly malignant disease; the poor overall prognosis of HCC patients is due to disease aggressiveness and frequency of recurrence. For patients with tumor of liver, the preferred treatment is operation. However, patients received operative resection relapsed within 5 years at a rate of 60%–70%. Clarifying the molecular mechanism of HCC oncogenic might supply important thread about the development of efficacious therapeutical aims and identification of the biomarkers of prognostic. In a variety of human cancers, TRIM27 supplies important thread in the occurrence and progression, including HCC. Nevertheless, knowledge in HCC of TRIM27 expression and prognostic value is still insufficient. A pan-cancer analysis carried out about the expression of TRIM27 through TCGA data in the study found that TRIM27 expression was increased in HCC tissues. Increased TRIM27 expression was positively correlative to highly pathological stage and TNM stage. TRIM27 may be a bright diagnostic biomarker for distinguishing HCC from normal tissues through ROC curve analysis. Through univariate analysis and Kaplan–Meier curve analysis, high TRIM27 expression shows relevance to short OS or RFS; also, TRIM27 might be a latent biomarker toward poorer prognosis in HCC. In conclusion, these founds indicate that TRIM27 may supply important thread in immune infiltration in HCC. The family of TRIM protein can still be thought to contain various regulative proteins of tumors. TRIM27, part of the TRIM family, exhibits a cancer-promoting role by enhancing tumor proliferation and metastasis in a variety of tumors. Research reported that knockdown TRIM27 remarkably weakened the transitivity and invasiveness of endometrial cancer cells, and also lowered the integrins b1 and a2 levels. The mutation of TRIM27 has been reported by Iwakoshi et al. that is contained in the signaling of epidermal growth factor receptor (EGFR) in lung cancer, and TRIM27 can be used as a prognostic factor of EGFR mutations in lung cancer. However, in HCC, TRIM27 expression and prognostic value of TRIM27 have still not been examined. In the study, pan-cancer analysis was performed and these findings were accordant to previous findings on the abnormal expression of TRIM27 mRNA in various cancers. We found that TRIM27 is up-regulated in HCC, and high TRIM27 expression is positively correlated with high pathological staging and TNM staging. These findings show in HCC that TRIM27 might serve as a latent biomarker of poorer prognosis. Confirmed the clinical worth of TRIM27 about HCC, we performed ROC curve analysis. These results indicated the potential value of TRIM27 in HCC detection. Our findings showed that TRIM27 might be a potential diagnostic biological marker to distinguish HCC from normal samples. In addition, log-rank test analysis and Kaplan–Meier curve showed a lower survival rate with higher TRIM27 expression in HCC patients. Based on the data, we conclude that TRIM27 may represent a latent biomarker of poorer prognosis of HCC. Our co-expression analysis showed that TRIM27 expression was significantly correlated with the expressions of ubiquitin specific peptidase 7 (USP7), recombinant small ubiquitin-related modifier protein 1 (SUMO1) and the product of murine double minute 2 gene (MDM2). TRIM27 is an important component of the TRIM27-USP7 complex and participates in cell metabolism. The ubiquitination–deubiquitination cascade mediated by the TRIM27-USP7 complex plays an important role in TNF-α–induced apoptosis. Maat et al. proposed a model in which USP7 counteracts the activity of TRIM27 E3 ligase, thereby maintaining the integrity and function of PRC1.1. Inhibiting USP7 may be a promising new strategy for the treatment of acute myeloid leukemia patients. TRIM27 is a member of the TRIM family of E3 ubiquitin ligases, MDM2 functioning as an E3 ubiquitin ligase mediated p53 degradation to regulate this critical tumor suppressor. Current functional information indicates that TRIM27 is associated with a variety of subcellular topologies and processes. Several interactions of TRIM27 with other proteins have been reported including with the E3 SUMO protein ligase PIAS3. We speculate that up-regulation of TRIM27 would affect the entire pathway, and this possibility should be examined in future studies. A large number of researches have certified that the prognostic and the efficacy of radiotherapy, immunotherapy, and chemotherapy of patients with cancer can be influenced by tumor immune cell infiltration. This study showed that TRIM27 was positively related to a variety of immune cells in HCC, involving macrophage, dendritic cell, CD4+ T cell, neutrophil, and B cell. In conclusion, TRIM27 is also remarkably positively related to these biomarkers of infiltrating immune cells. Our data show tumor immune infiltration might partly explain carcinogenic effect of TRIM27 in HCC. The effect of immune therapy not merely requires the tumor microenvironment sufficient infiltrate by immune cells, but also relies on the full immune checkpoints expression. Therefore, this study evaluated correlation between TRIM27 and immune checkpoints. Our findings showed the higher TRIM27 expression was closely related to CTLA-4 and PD-1, PD-L1 in HCC, suggesting that it improved the effect of immune therapy through targeting TRIM27 in HCC. There are definitely limitations to our study. A database used to confirm the correlation between the expression of TRIM27 and HCC to enlarge the sample size and make sure the accurateness of the experimental outcomes. The data we owned from multiplex databases to narrow the deviation that a single database might cause. Future studies need to carry out related animal and cell experiments, forward to study the potential roles of TRIM in HCC.
We demonstrated that TRIM27 is highly expressed in many types of human cancers including HCC and showed that TRIM27 represents a potential biomarker of poor prognosis to identify HCC patients with adverse clinical outcomes. Our results also showed that TRIM27 may exert its carcinogenic effects by increasing tumor immune cell infiltration and immune checkpoint expression. These findings should be verified by additional experiments and large-scale clinical trials. | true | true | true |
PMC9558886 | Jianfei Qiu,Li Chen,Jue Yang,Krishnapriya M. Varier,Babu Gajendran,Yao Yao,Wuling Liu,Jingrui Song,Qing Rao,Qun Long,Chunmao Yuan,Xiaojiang Hao,Yanmei Li | Garmultin-A Incites Apoptosis in CB3 Cells Through miR-17-5p by Attenuating Poly (ADP-Ribose) Polymerase-1 | 11-10-2022 | Garmultin-A,leukemia,apoptosis,miR-17-5p,PARP-1 | Background Leukemia accounts for a large number of deaths, worldwide, every year. Treating this ailment is always a challenging job. Recently, oncogenic miRNA leading to apoptosis are highly promising targets of many natural products. In this study, Garmultin-A (GA), isolated from the bark of Garcinia multiflora, was elucidated for its anti-leukemic effect in CB3 cells. Methods The effect of the compound on CB3 cell viability was detected by MTT assay and apoptosis by FITC Annexin V/PI and Hochest 33258 staining. The western blot analysis assessed the BAX, BCL2, cMYC, pERK, and PARP-1 protein levels. Autodock analysis predicted the ligand–protein interactions. q-RT-PCR quantified the miR-17-5p expression. Luciferase assay confirmed the interaction between PARP-1 and miR-17-5p. Results We uncover that GA leads to apoptosis by inducing overexpression of miR-17-5p and significantly downregulate PARP-1 protein levels in CB3 cells. The overexpression of miR-17-5p promotes apoptosis, and the miR-17-5p antagomirs restore GA-triggered apoptosis. Notably, we disclose that PARP-1 is a direct target of miR-17-5p. Increased pro-apoptotic and reduced anti-apoptosis protein levels were also observed in GA-treated CB3 cells. Conclusion These results provide critical insights that GA could induce apoptosis in CB3 cells through targeting miR-17-5p by attenuating PARP-1. Thus, GA could act as a novel therapeutic agent for erythroleukemia. | Garmultin-A Incites Apoptosis in CB3 Cells Through miR-17-5p by Attenuating Poly (ADP-Ribose) Polymerase-1
Leukemia accounts for a large number of deaths, worldwide, every year. Treating this ailment is always a challenging job. Recently, oncogenic miRNA leading to apoptosis are highly promising targets of many natural products. In this study, Garmultin-A (GA), isolated from the bark of Garcinia multiflora, was elucidated for its anti-leukemic effect in CB3 cells.
The effect of the compound on CB3 cell viability was detected by MTT assay and apoptosis by FITC Annexin V/PI and Hochest 33258 staining. The western blot analysis assessed the BAX, BCL2, cMYC, pERK, and PARP-1 protein levels. Autodock analysis predicted the ligand–protein interactions. q-RT-PCR quantified the miR-17-5p expression. Luciferase assay confirmed the interaction between PARP-1 and miR-17-5p.
We uncover that GA leads to apoptosis by inducing overexpression of miR-17-5p and significantly downregulate PARP-1 protein levels in CB3 cells. The overexpression of miR-17-5p promotes apoptosis, and the miR-17-5p antagomirs restore GA-triggered apoptosis. Notably, we disclose that PARP-1 is a direct target of miR-17-5p. Increased pro-apoptotic and reduced anti-apoptosis protein levels were also observed in GA-treated CB3 cells.
These results provide critical insights that GA could induce apoptosis in CB3 cells through targeting miR-17-5p by attenuating PARP-1. Thus, GA could act as a novel therapeutic agent for erythroleukemia.
Leukemia is one of the foremost causes of death due to blood malignancies in the human population worldwide. Natural products obtained from medicinal plants can provide changes like DNA methylation and histone arrangements, causing alterations in cellular signaling, epigenetically. These epigenetic changes may lead to either inhibition of the activity of onco-miRNAs or an increase in the expression of tumor suppressor miRNAs, which may finally inhibit cell proliferation through the induction of apoptosis. Recently, plant bioactive compounds are of high-throughput screening for the prevention and treatment of many cancers. Several scientific pieces of evidence have shown that many natural compounds exert anticancer effects via affecting the expression of many miRNAs, indicating that the regulation of miRNAs by natural products could be a novel strategy in cancer therapy. In this context, it is relevant to mention that the genus Garcinia (Guttiferae) is a genus reported to have several polycyclic polyprenylated acylphloroglucinols (PPAPs), xanthones, and flavonoids with a broad array of biological activities. In particular, for the lung cancer Phase II clinical trials, gambogic acid from Garcinia hanburyi was approved. Moreover, the bark of Garcinia multiflora is applied externally to reduce inflammation. Our previous study had obtained a series of novel PPAPs with good cytotoxic activity. Garmultin-A (GA) is one among those poly adenosine diphosphate-ribose polymerases (PARPs) with good cytotoxic activity against many cancer cells. The miRNAs are non-protein-coding small RNAs, a group of highly conserved 18–25 nucleotides, that repress mRNA translation or trigger mRNA degradation through binding to 3′ Un-Translated Regions (3′UTR) of target mRNAs. It estimated that miRNAs regulate over 60% of all human genes. The miRNAs directly regulate different biological processes that include proliferation and differentiation via affecting the expression of target genes. MiR-17-5p is a member of miR-17-92 cluster, which is a polycistronic miRNA gene encoding seven individual miRNAs, namely, miR-17-5p, miR-17-3p, miR-18a, miR-19a, miR-20a, miR-19b, and miR-92a. Plenty of evidence demonstrates the overexpression of miR-17∼92 clusters in hematologic malignancies and lung cancers. Its enhanced expression experimentally triggers tumor growth by targeting tumor suppressors. However, several other studies suggested that the deletion of miR-17∼92 cluster was observed in ovarian cancer patients. The miR-17-5p can act as both an onco-miRNA and a tumor suppressor in different cellular contexts. Specific overexpression of miR-17-5p blocks tumor cell growth and induces apoptosis by directly targeting oncogenes. Moreover, CircTLK1-mediated sponging of miR-17-5p could result in cardiomyocyte apoptosis through mitochondrial damage by oxidative stress. Thus, in this study, we have hypothesized to uncover the molecular target of GA that promotes cellular apoptosis in CB3 cells, which could be a novel anti-cancer agent for erythroleukemia.
GA was isolated and characterized according to our previous work by Tian et al, 2016. CB3 mouse erythroleukemia cell line and HL-7702 non-tumor lineage cells were obtained from the University of Toronto. The cells were well-bred in RPMI with 5% fetal bovine serum, 2 mmol/l L-glutamine, 100 U/ml penicillin, and 100 g/mL streptomycin (RPMI). Cells were incubated at 37°C in 5% CO2 with 95% air humidified atmosphere. All the chemicals used in the study are of analytical grade.
MTT (3-(4,5-dimethyl-thiazol-2yl)-2,5-diphenyl tetrazolium bromide) colorimetric assay was employed to determine cell viability. Logarithmic growth cells were harvested, resuspended in fresh medium containing 10% fetal bovine serum, and inoculated into 96 wells at a rate of about 8 × 103 cells per well. After 24 h, cells were treated with GA at the concentrations of 1.25, 2.5, 5, 10, and 20 μM, with DMSO control. After 48 h of drug addition, 10 μL of MTT (5 mg/mL; Beyotime Biotechnology, Beijing, China) was added, and the treated cells were cultured for another four hours. Later, the supernatant was removed by centrifugation, followed by the addition of 160 μL of DMSO to each well, and shaken horizontally until the precipitate completely dissolved. Later, the microplate was read at 490 nm in a microplate reader (Biotek USA).
Once the CB3 cells reached around 80% of confluence, they were counted in a cell counting chamber at 1:2 dilution with trypan blue dye exclusion (purchased from SIGMA-Aldrich). Around 5 × 103 CB3 cells per well were cultured in a 96-well plate to determine the proliferation parameters by the MTT method as described by Mosmann. The growth curves developed as per Ramírez. The cellular morphology changes on the treated cells were photographed in Nikon inverted microscope, according to Gajendran et al, 2020.
The apoptotic effects of GA against CB3 cells were examined by a FITC Annexin V and PI apoptosis detection kit I (BD Pharmingen™, USA) according to the manufacturer’s protocol. In brief, cells were treated (5 × 104/well) with 2.5, 5, and 10 μM of the compound for 24 and 48 h, harvested by centrifuging at 3000 r/min for 15 min. Later, the pellets were collected and washed in 100 μL of binding buffer. The specific binding of FITC Annexin V was achieved by incubating cells in 100 μL of binding buffer at room temperature for 15 min in the dark and then immediately analyzed by NovoCyte flow cytometry (ACEA NovoCyte, USA) and interpreted using NovoExpress software. Untreated cells served as a negative control.
The evaluation of the apoptotic cells was performed using Hochest 33258 staining. The CB3 cells at its logarithmic phase at the density of 2 × 104 cells/well were seeded explicitly in 24-well plates. After CB3 cells were treated with 0, 2.5, 5, and 10 μM of GA at 24 and 48 h of incubation, cells in the plates were centrifuged for 30 min at room temperature, followed by washing and staining with Hoechst 33258 at 37°C for 30 min. Later, the apoptotic cells were viewed by Nikon fluorescence microscope equipped with a UV filter and photographed.
CB3 cells treated with 5 and 10 μM of GA for 48 h were harvested and lysed. Proteins separated by 10% SDS/PAGE and transferred to nitrocellulose membranes. Afterward, the membranes were blocked by 5% non-fat milk and then incubated with rabbit polyclonal anti-BCL2 (1: 2000; ab32124; Abcam, USA), anti-BAX (1: 2000; ab32503; Abcam, USA), anti-pERK (1: 2000; #4370T; Cell Signaling Technology, USA), anti cMYC (1: 2000; #13987; Cell Signaling Technology, USA), anti-PARP-1 (1: 2000; ab191217; Abcam, USA), and β-actin (#4967S, Cell Signaling Technology, USA). The immunoblots were rinsed three times with TBS/TBS-T buffer, incubated with the secondary antibody (Anti-rabbit IgG (H+L) (DyLight™ 800 4X PEG Conjugate; #5151P; Cell Signaling Technology), and analyzed by enhanced IR fluorescence with Li-Cor/Odyssey infrared image system (LI-COR Biosciences, Lincoln, NE, USA). β-actin served as an internal control for total protein levels. Relative fluorescence levels were determined by dividing the normalized fluorescence readings of the bands of interest by the corresponding β-actin loading control band of each sample.
The molecular docking studies were conducted, according to Krishnapria et al, 2016. The 3-D structures of venetoclax, MLS006011554, and ravoxertinib were retrieved from PubChem and optimized for docking using the Discovery Studio. The structure of the GA was drawn in Chem-sketch. The protein crystallographic structures of receptors BCL2, pERK, and cMYC were retrieved from www.rcsb.org and prepared for docking using Discovery Studio. Then the obtained structures were used for the docking studies (Autodock 4.2).
CB3 cells were cultured in the presence of GA or DMSO (control), and the total RNA was extracted with TRIzol® reagent (Invitrogen, Carlsbad, CA, USA). An equal amount of RNA (1 μg) was reverse transcribed to cDNA using the HiFi Script cDNA Synthesis Kit (Takara, Dalian, China). A quantitative real-time PCR (Ultra SYBR Mixture with High ROX) performed in a StepOnePlus TM Real-time PCR System (Thermo Fisher Scientific, Waltham, MA, USA). miR-specific primers were used for the analysis of the expression of mature miR-17-5p, keeping β-actin as internal control.
For cloning purposes, precursor overhang sequences from 5′ NotI- and 3′ XhoI-restriction sites having specific gene primers (Forward primer TCTATTTCAAATTTAGCAGGAAAAA, Reverse primer GCACTCAACATCAGCAGG) were amplified to generate lentiviruses. The PCR products inserted into the lentiviral expression vector (pGFP-C-vector) generate pGFP-C-lenti-miR-17-5p. The confirmation of the insertions was performed using DNA sequencing of the plasmids. Anti-miR-17-5p was designed with the RNAi design algorithm for type 5 shRNA to generate miR-17-5p loss-of-function phenotypes. It was cloned into the BamHI and BsmBI sites of a modified pGFP-C-shLenti-miR (OriGene) to generate pGFP-C-shLenti-miR-17-5p.
The generation of lentiviruses was performed by co-transfecting lentiviral vector (5 mg), with packaging plasmids (6 mg), in 293T cells, by lipofectamine 2000 reagent having Lenti-shRNA of miR-17-5p. After 48 h of incubation, cells were centrifuged (3000 r/min/min), and supernatants were pooled. The collected supernatant was filtered (.45 μm) and used to infect cells.
Transfections were carried out as previously described. In brief, CB3 cells (2 × 105) were immersed in 3 mL medium in each well of a 6-well plate after adding .5 mL of lentiviral particles with polyarginine (Sigma) for 20 min.
Luciferase assay was carried out as previously described. In brief, NIH-3T3 cells (4 × 105) were seeded into 12-well plates. After 24 h, .2 mg of p MIR-REPORT Luciferase Reporter Plasmid expressing wild-type or mutated miR-17-5p binding sites in PARP1 3′-untranslated regions (3′-UTRs) and .8 mg pGFP-C-shlenti-miR-17-5p plasmid were added to each well using lipofectamine 2000 in triplicates. The Quick Change XL Mutagenesis Kit is used to perform mutagenesis of miR binding sites. Moreover, TargetScanHuman 8.0 was utilized to predict the interaction/binding site between PARP-1 and miR-17-5p.
All experiments were conducted at least three replicates and statistically analyzed by Student’s t-test using GraphPad Prism 8 Software (San Diego, CA, USA). The results were expressed as mean ± SD. * P-value < .05, ** P-value < .01, *** P-value < .001, and **** P-value < .0001 were considered statistically significant.
After 48 h of incubation with GA (Figure 1A), the cellular viability of CB3 cells was found to be reduced both in a time- and dose-dependent manner. The growth curve analysis revealed that the cell viability drastically deteriorated after 48 h of incubation (Figure 1B). The CB3 cells were administered with various concentrations of the compound for 48 h, to analyze the GA effect on cell viability. The cells were affected significantly from 2.5 μM treatment, with an IC50 value of 5.0 μM (Figure 1C). Moreover, the cellular loss dose-dependently found in trypan blue analysis (Additional file 1). The cellular morphology analysis revealed that GA was able to cause a dose-dependent cellular shrinkage and loss of the cells when compared with the DMSO control group (Figure 1D). Moreover, the cytotoxicity analysis of GA on normal liver cell line HL-7702 failed to show significant cellular toxicity at the selected doses of the drug, after 48 h of incubation (Additional file 2).
For studying the apoptosis-inducing effect of GA, CB3 cells with different doses of the compound (2.5, 5, and 10 μM) for 24 or 48 h were analyzed. The CB3 cells after GA treatment were analyzed by FITC Annexin V/PI staining using flow cytometry for its action on cellular apoptosis. The flow cytometry results showed that GA induced apoptosis in CB3 cells in a dose- and time-dependent manner. Even though there was a little effect on CB3 cells after 24 h treatment with 5 and 10 μM of GA, the apoptotic rate was observed to be highly significant after 48 h of incubation. At this juncture, the treatment of cells with 5 μM of GA significantly increased the apoptosis rate to 45.8 ± 2.13% from 22.2 ± 1.32% (at 24 h of incubation). Similarly, 10 μM treatment increased the apoptotic rate from 92.6 ± 3.27% to 98.7 ± 4.25%. However, in DMSO control cells, apoptotic rates were 2.67 ± .51% and 4.5 ± .32%, respectively, after 24 and 48 h of incubation (Figures 2A and 2B). To further confirm whether apoptosis caused nuclear loss, Hochest 33258 staining was performed. It revealed that the drug was able to create a dose- and time-dependent loss of the nucleus. It even showed that nuclear condensation was affected by the formation of apoptotic bodies and cellular apoptosis, after GA treatment (Figures 2C and 2D).
For determining the molecular targets of apoptosis in CB3 cells, after GA treatment, the expression was analyzed for onco- and tumor suppressor proteins. The results demonstrated that GA treatment could significantly downregulate BCL2, cMYC, pERK, and PARP-1 protein levels. Similarly, it upregulated the BAX protein level expressions in a dose-dependent manner when compared with the DMSO control cells (Figure 2D).
The molecular interactive sites of the downregulated proteins were investigated by autodocking. The interacting amino acids in the concerned proteins were depicted in 3D interaction images (Figures 3A, 3C, and 3E). The ligand was predicted to develop several favorable interactive sites with BCL2, cMYC, as well as pERK, namely, conventional hydrogen bonds, carbon-hydrogen bonds, van der Waals forces, attractive charged bonds, alkyl, and pi-Alkyl bonds (Figures 3B, 3D, and 3F). The study revealed that the binding energy values of GA with BCL2, cMYC, and pERK were predicted as −8.5, −11.1, and −8.3 Kcal/Mol (Figure 3G) with ligand efficacy of .06, .05, and .03, respectively. The interaction was much favorable with relatively better binding energy than the already known BCL2 (Additional file 3), cMYC (Additional file 4), and pERK (Additional file 5) inhibitors. The well-known inhibitors venetoclax, MLS006011554, and ravoxertinib showed only −7.4, −6.2, and −7.3 Kcal/mol of binding energies (Additional file 6) with corresponding ligand efficiencies as .02, .03, and .01, which is relatively less, compared to GA interactions. The most crucial finding was that none of the favorable interaction was observed between the PARP-1 and the ligand. It led us to think that the drug was unable to interact directly with PARP-1 but could indirectly downregulate its expression. It led us to work on miR-17-92 cluster genes, which are targets for alleviating PARP-1.
To determine whether miR-17-92 cluster genes are involved in anti-leukemia action, miR-17-5p levels were analyzed, viz, qPCR analysis upon treatment with GA. MiR-17-5p expression significantly upregulated in CB3 cells treated with GA compared with the DMSO group (P < .001; Figure 4A) unless other genes were involved in the cluster. Interestingly, this suggested a possible targeting relationship between miR-17-5p and the PARP-1 protein.
The study revealed that the 3′UTR of PARP-1 is the potential target of miR-17-5p (Figure 4B). Luciferase assays with NIH-3T3 cells transiently transfected with a reporter plasmid containing binding sites, along with vector miR-17-5p expression, were consistent with regulation of PARP-1 by miR-17-5p. Mutation of the binding sites for miR-17-5p, in PARP-1, restored luciferase activity (Figure 4C). The level of PARP-1 in the cells decreased after vector transfection with miR-17-5p (Figures 4D and 4E). Overexpression of miR-17-5p in CB3 cells significantly increased GA-induced apoptosis, compared with control (Figure 4F). Conversely, infection with antisense miR-17-5p vector decreased GA-induced apoptosis significantly (Figure 4G).
The natural products have always been a choice of great interest for experimentation by the scientist to treat various ailments. In the same fashion, ruling out of the potential molecular targets of the bioactive compounds remains a challenging job. Thus, in this study, we have attempted to figure out the molecular target of GA in CB3 mouse erythroleukemia cells, which demonstrated prominent anticancer action. The cell viability analysis proved that the compound could cause cell death in a dose- and time-dependent manner in CB3 cells. Further, the study revealed that cellular loss is mainly due to the apoptosis process after GA treatments. Our previous work has identified that GA could selectively kill various cancer cells via unknown mechanisms of action 6. Possessing a piece of defective apoptotic machinery leads to uncontrolled proliferation. There are two types of death models for apoptosis: the extrinsic (mitochondrial independent) and the intrinsic pathway (mitochondrial independent). Alternation in BAX/BCL2 ratio accounts for the intrinsic type of apoptosis mechanism. Likewise, in this study, we could see that the GA-treated cells had a variation in their BAX/BCL2 ratio compared to the control cells. Moreover, cMYC promotes cell proliferation and impair cell apoptosis by activating or repressing the growth-promoting genes or growth-suppressing genes. Inhibition of PARP-1 could modulate the cMYC-induced cell process. Moreover, that activation of PARP-1 is associated with ERK-mediated cell proliferation, apoptosis, and migration. Inhibition of PARP-1 could impair BCL2 expressing tumor cells, which are resistant to apoptosis. Likewise, our data proved that there was a downregulation of PARP-1, after GA administration, resulting in the reduction of cMYC, BCL2, and pERK, as well. However, on the contrary, this study provides an insight into the interplay between miR-17-5p and PARP-1 in GA-induced apoptotic cell death. Most of the cancer cells can overcome apoptosis via the activation of PARP-1, which can repair both single-stranded and double-stranded DNA breaks. The inhibition of PARP-1 results in a vast amount of DNA damage in cancer cells and apoptosis follows as the genetic mutations reach a lethal level. The above studies are consistent with our finding that GA promotes apoptosis with a significant decrease of PARP-1 in CB3 cells. However, the autodock analysis failed to reveal a direct interaction between PARP-1 and GA, which made us think about the alternative target of the drug, causing downregulation of PARP-1 levels, which could be the miR-17-5p. Specific overexpression of miR-17-5p blocks tumor cell proliferation and promotes apoptosis by directly targeting oncogenes. The miR-17-92 cluster encodes six miRNAs: miR-17, miR-19a, miR-18, miR-19b, miR-20, and miR-92. As oncogenes, these miRNAs promote cell proliferation, block apoptosis, and induce tumor angiogenesis. However, the miR-17-5p, in exceptional cases, negatively regulates cell proliferation, inhibiting cell migration leading to invasion. We have previously found that miR-17-5p can promote apoptosis by targeting BCL2 in leukemia cells. The miR-17-5p can even inhibit cMYC-induced cell proliferation by functioning as a tumor suppressor in many cancer cells. A recent study showed that the cMYC translation was downregulated by miR-17-5p, in lymphoma cells. Here, we also showed that overexpression of miR-17-5p could directly promote CB3 cell apoptosis and significantly enhance GA-induced apoptosis by reducing PARP-1 levels. It reported that knockdown of PARP-1 inhibited cancer cell proliferation, induced cancer cell apoptosis by reducing BCL2, and led to inactivation of the ERK1/2 signaling pathway. The inhibition of PARP-1 could suppress cMYC-mediated transactivation. The PARP-1 inhibition increased the BAX promoter activation which could promote cell apoptosis. The overexpressed PARP-1 is observed in various types of breast, lung, hepatocellular, gastric, and leukemia cancers. Also, it has been reported that the PARP-1 expression level can be a prognostic indicator and is related to a poor survival prognosis. PARP-1 inhibition was shown to be a useful aid to enhance cancer patients’ survival rates. Here, we suggest that GA-mediated overexpression of miR-17-5p promotes cell apoptosis by downregulating expression of PARP-1, BCL2, and cMYC and upregulating expression of BAX in CB3 cells. This mechanism adds to previous mechanisms of miR-17-5p action as a tumor suppressor in leukemic cells. In our study, we could see that there was a significant elevation in the expression of miR-17-5p, after GA treatment. However, the luciferase assay showed that the knockdown of 3′UTR of the MiR-17-5p restored the fluorescence. Moreover, the anti-MiR-17-5p significantly restored the GA-triggered apoptosis. This could clearly rule out the role of miR-17-5p in GA-induced apoptosis. Thus, the study reveals that the treatment with GA in CB3 cells could cause apoptosis and nuclear damage in a dose- and time-dependent manner. The drug, entering the cytoplasm, alters the BAX/BCL2 ratio (Figure 5). The drug could even inhibit the expression levels of cMYC and pERK molecules. On the other hand, the bioactive compound could enhance the expression of miR-17-5p, causing diminished expression levels of PARP-1. All these molecular machineries work together for apoptosis in the mouse erythroleukemia cells.
The present study revealed that miR-17-5p-mediated apoptotic signaling contributed to the GA-induced cellular apoptosis in CB3 erythroleukemia cells. The study suggested that miR-17-5p may be a promising target for natural compounds by attenuation of PARP-1, causing apoptosis. Thus, the study reveals that GA could be a viable drug of choice to treat erythroleukemia.
Click here for additional data file. Supplemental Material for Garmultin-A Incites Apoptosis in CB3 Cells Through miR-17-5p by Attenuating Poly (ADP-Ribose) Polymerase-1 by Jianfei Qiu, Li Chen, Jue Yang, Krishnapriya M. Varier, Babu Gajendran, Yao Yao, Wuling Liu, Jingrui Song, Qing Rao, Qun Long, Chunmao Yuan, Xiaojiang Hao, and Yanmei Li in Dose-Response | true | true | true |
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PMC9558900 | Jia Su,Ji Cheng,Yingchu Hu,Qinglin Yu,Zhenwei Li,Jiyi Li,Nan Zheng,Zhaoxia Zhang,Jin Yang,Xiaojing Li,Zeqin Zhang,Yong Wang,Keqi Zhu,Weiping Du,Xiaomin Chen | Transfer RNA-derived small RNAs and their potential roles in the therapeutic heterogeneity of sacubitril/valsartan in heart failure patients after acute myocardial infarction | 29-09-2022 | tsRNA,expression profile,sacubitril/valsartan,lipid and atherosclerosis signal pathway,heart failure | Background It has been reported that sacubitril/valsartan can improve cardiac function in acute myocardial infarction (AMI) patients complicated by heart failure (HF). However, a number of patients cannot be treated successfully; this phenomenon is called sacubitril/valsartan resistance (SVR), and the mechanisms remain unclear. Methods In our present research, the expression profiles of transfer RNA (tRNA)-derived small RNAs (tsRNAs) in SVR along with no sacubitril/valsartan resistance (NSVR) patients were determined by RNA sequencing. Through bioinformatics, quantitative real-time PCR (qRT-PCR), and cell-based experiments, we identified SVR-related tsRNAs and confirmed their diagnostic value, predicted their targeted genes, and explored the enriched signal pathways as well as regulatory roles of tsRNAs in SVR. Results Our research indicated that 36 tsRNAs were upregulated and that 21 tsRNAs were downregulated in SVR. Among these tsRNAs, the expression of tRF-59:76-Tyr-GTA-2-M3 and tRF-60:76-Val-AAC-1-M5 was upregulated, while the expression of tRF-1:29-Gly-GCC-1 was downregulated in the group of SVR. Receiver operating characteristic (ROC) curve analysis demonstrated that these three tsRNAs were potential biomarkers of the therapeutic heterogeneity of sacubitril/valsartan. Moreover, tRF-60:76-Val-AAC-1-M5 might target Tnfrsf10b and Bcl2l1 to influence the observed therapeutic heterogeneity through the lipid and atherosclerosis signaling pathways. Conclusion Hence, tsRNA might play a vital role in SVR. These discoveries provide new insights for the mechanistic investigation of responsiveness to sacubitril/valsartan. | Transfer RNA-derived small RNAs and their potential roles in the therapeutic heterogeneity of sacubitril/valsartan in heart failure patients after acute myocardial infarction
It has been reported that sacubitril/valsartan can improve cardiac function in acute myocardial infarction (AMI) patients complicated by heart failure (HF). However, a number of patients cannot be treated successfully; this phenomenon is called sacubitril/valsartan resistance (SVR), and the mechanisms remain unclear.
In our present research, the expression profiles of transfer RNA (tRNA)-derived small RNAs (tsRNAs) in SVR along with no sacubitril/valsartan resistance (NSVR) patients were determined by RNA sequencing. Through bioinformatics, quantitative real-time PCR (qRT-PCR), and cell-based experiments, we identified SVR-related tsRNAs and confirmed their diagnostic value, predicted their targeted genes, and explored the enriched signal pathways as well as regulatory roles of tsRNAs in SVR.
Our research indicated that 36 tsRNAs were upregulated and that 21 tsRNAs were downregulated in SVR. Among these tsRNAs, the expression of tRF-59:76-Tyr-GTA-2-M3 and tRF-60:76-Val-AAC-1-M5 was upregulated, while the expression of tRF-1:29-Gly-GCC-1 was downregulated in the group of SVR. Receiver operating characteristic (ROC) curve analysis demonstrated that these three tsRNAs were potential biomarkers of the therapeutic heterogeneity of sacubitril/valsartan. Moreover, tRF-60:76-Val-AAC-1-M5 might target Tnfrsf10b and Bcl2l1 to influence the observed therapeutic heterogeneity through the lipid and atherosclerosis signaling pathways.
Hence, tsRNA might play a vital role in SVR. These discoveries provide new insights for the mechanistic investigation of responsiveness to sacubitril/valsartan.
Acute myocardial infarction (AMI) is one of the most critical cardiovascular diseases in humans, and heart failure (HF) is the most common complication after AMI. Evidence has shown that the probability of HF within 30 days to 6.7 years after the onset of AMI is as high as 13.1–37.5% (1). AMI combined with HF often indicates a poor prognosis and is associated with mortality 20.9 times higher than that of patients without HF (2). Therefore, HF has become an important factor affecting the long-term survival of myocardial infarction patients and their quality of life. The pathogenesis of HF after AMI is related to the activation of the neuroendocrine system, ventricular remodeling, and inflammatory factors (3, 4). In the early stage of myocardial infarction, a large number of cardiomyocytes undergo necrosis and apoptosis, which reduces myocardial contractility and ventricular output, resulting in heart pump failure and compensatory activation of the renin-angiotensin-aldosterone system (RAAS) as well as natriuretic peptide system. Sacubitril/valsartan, which was the first dual inhibitor of enkephalinase and angiotensin receptor to be developed, can simultaneously regulate the natriuretic peptide system and RAAS and plays a dual cardioprotective role (5). The multicenter, randomized, double-blind, phase III PARADISE-MI study revealed that sacubitril/valsartan treatment could delay or reverse ventricular remodeling and improve cardiac function in patients with AMI complicated by HF (6). However, there is variation in the response to sacubitril/valsartan treatment, which may be related to the clinical characteristics and genetic factors of patients. One study showed that after treatment with sacubitril/valsartan, 31% of patients showed no change in the left ventricular ejection fraction (LVEF), and 19% showed a decrease in LVEF, which may be related to a lower basic LVEF value, non-ischemic cardiomyopathy, the lack of an implantable cardioverter defibrillator and a shorter history of HF (7). We refer to this phenomenon of the therapeutic heterogeneity of sacubitril/valsartan as sacubitril/valsartan resistance (SVR). A sum of clinical research works have discovered that SVR may be interrelated to the medication dose, troponin, sex, race, left ventricular end-systolic volume, etiology, and other factors (8–12). However, there is a lack of in-depth research concerning the specific pharmacodynamic mechanism of SVR at present. Transfer RNA (tRNA) is a kind of RNA that is widespread in the human body, accounting for 4–10% of total cellular RNA. More than 500 tRNAs have been identified in the human body to date (13), and approximately half of them have been proven to come from actively expressed genes (14). When cells are exposed to conditions such as hypoxia, oxidative stress, starvation and high temperature, precursor and mature tRNAs can be cleaved by corresponding nucleases to form tRNA-derived small RNAs (tsRNAs) with specific functions (15–17). tsRNA retains the diversity of tRNA functions and shows the characteristics of high expression, fixed conservation, and good stability (18). It can play a role as an epigenetic regulator of mRNA stability, protein translation, and gene expression (16). tsRNA can be considered not only a therapeutic target but also a biomarker that may be used in diagnosis and prognosis assessment (19), and one study has shown that tRF-Gly-GCC can promote the regulation of cell adhesion, proliferation, migration as well as phenotypic transformation in Human umbilical vein endothelial cells (HUVECs) and vascular smooth muscle cells (VSMCs) by inhibiting the expression of MERVL-related genes (20). tsRNA has now been confirmed to produce a marked effect on cardiovascular diseases (21, 22). Therefore, this study aimed to screen the differential tsRNA expression profiles of patients with SVR or with no sacubitril/valsartan resistance (NSVR) and to explore the possible underlying molecular mechanism to achieve greater prognostic benefits and realize individualized treatment.
From October 2019 to December 2021, patients who were diagnosed with ST-elevation AMI with a reduced ejection fraction in HF were selected from Ningbo No. 1 Hospital, on the east coast of China. They all came from the Han population, had undergone complete revascularization, and had received the maximum tolerated dose of sacubitril/valsartan for at least 6 months. According to the baseline LVEF and the changes in LVEF after sacubitril/valsartan administration, the patients in this study were divided into NSVR group and SVR group: (1) a cardiac function improvement group, referred to as the NSVR group, showing an LVEF >45 and ≥10% higher than baseline at the last review; and (2) a group with poor improvement of cardiac function, referred to as the SVR group, showing an LVEF ≤40 or <10% higher than baseline at the last review. The clinical data collected included basic clinical information (age, sex, height, weight, BMI, systolic blood pressure, smoking and alcohol history, coexisting diseases, and so on), blood laboratory test indices (e.g., blood routine, CRP, hepatic and renal function, blood glucose and lipid, coagulation function, aTnI, and NT-proBNP results), cardiac ultrasound indexes before and after treatment with sacubitril/valsartan (LVEF, left ventricular diastolic diameter, and left ventricle systolic diameter), coronary artery disease characteristics, and the clinical medication regime (medication strategy, dosage, and time). This study was approved by the ethics committee of Ningbo No. 1 Hospital, and every person Included signed a written informed consent form before the investigation. The whole research was implemented in line with the principles of the Helsinki Declaration.
The studied patients were included in the light of the followings: (1) age greater than 18 years and less than 75 years; (2) meeting the diagnostic criteria for ST-elevate AMI (23); (3) having undergone complete revascularization; (4) LVEF ≤45%; (5) a Killip classification (24) of Class II–IV; and (6) having been continuously and regularly treated for 6 months or more. If any of the following criteria were met, the patient was excluded: (1) contraindications for sacubitril/valsartan (including systolic blood pressure <95 mmHg, potassium >5.4 mmol/L, glomerular filtration rate <30 ml/min/1.73 m2); (2) cardiac insufficiency due to other heart diseases (e.g., valvular heart disease, dilated cardiomyopathy, and hypertensive cardiac insufficiency); (3) pregnancy or lactation in women; or (4) incomplete information.
From 22 subjects with SVR and equal numbers of NSVR, the peripheral blood samples were collected after 6 months of sacubitril/valsartan treatment. Ten of these patients were used for the systemic analysis of tsRNA expression profiles (these 5 SVRs and 5 NSVRs were well-matched), and the remaining samples (17 SVR along with 17 NSVR) were arranged for validation. After PBMC isolation, total RNA in samples were obtained by using TRIzol reagent, and the purity and concentration of them were determined with the instrument of NanoDrop ND-1000. If the OD was in the range of 1.8–2.0, the RNA was included in the follow-up experiment. According to rtStar tRF and tiRNA Pretreatment Kit protocols (Arraystar, USA), the total RNA samples were pretreated to remove RNA modifications, which would interfere with the library construction of small RNA-seq. Then, the samples were sequentially ligated to 3′ and 5′ small RNA adapters. After adding Illumina’s proprietary RT primers and amplification primers, cDNA was synthesized and amplified. Next, the PCR-amplified fragments (134–160 bp PCR amplified fragments corresponding to 14–40 nt small RNA size range) were extracted and purified from the PAGE gel. And with an Agilent 2100 Bioanalyzer, the integrated libraries were quantified, denatured and diluted. Lastly, according to the manufacturer’s instructions, the diluted libraries were loaded onto a reagent cartridge and forwarded for sequencing using NextSeq 500/550 High Output v2 Kits (FC-404-2004, Illumina, USA).
Base detection and image analysis were operated with the Solexa Pipeline, and the original data were subjected to quality inspection with FastQC software. The trimmed valid data were compared with pre-tRNA and mature tRNA sequences by using Bowtie software. These trimmed reads were aligned to mature-tRNA and pre-tRNA sequences from GtRNAdb and tRNAscan-SE. The exactly matched reads were thought as tsRNAs. In view of comparative statistical analysis, the tsRNA expression profiles of the SVR and NSVR groups were finally obtained. The differentially expressed tsRNAs were analyzed with R package edgeR by GEO (Gene Expression Omnibus). The calculated P-values and fold changes (FCs) were used to compare the tsRNAs of the two groups. A FCs more than 1.5 and P value less than 0.05 were considered significant. Then, the differentially expressed tsRNAs were represented via volcano map, heatmap, and scatter map.
Five treatment-related tsRNAs (tRF-1:28-Gly-GCC-1, tRF-1:29-Glu-CTC-1-M2, tRF-1:29-Gly-GCC-1, tRF-59:76-Tyr-GTA-2-M3, and tRF-60:76-Val-AAC-1-M5) showing relatively high FC values were selected for cross-validation through quantitative real-time PCR (qRT-PCR) in triplicate. First, applying the rtStar™ tRF and tiRNA First-Strand cDNA Synthesis Kit (Arraystar), total RNA was reverse-transcribed into cDNA according to the manufacturer’s protocol. Then, qRT-PCR amplification was carried out through an ABI 7500 qRT-PCR System (Applied Biosystems, Foster City, CA, USA) and 2 × PCR master mix (Arraystar). The conditions of PCR amplification were as followings: (1) incubation (95°C, 10 min), (2) 40 PCR cycles (95°C, 10 s; 60°C, 60 s for fluorescence collection), and (3) after the PCR amplification reaction, the melting curve was established on the basis of the following program: 95°C, 10 s; 60°C, 60 s; 95°C, 15 s. The levels of relative tsRNA expression were reckoned by the 2–Δ Δ Ct method and were normalized to U6 as a housekeeping gene. The target mRNAs of selected tsRNAs were confirmed via qRT-PCR too. The protocol was similar to that described above, including cDNA synthesis with the PrimeScript™ RT Reagent Kit and gDNA Eraser (TaKaRa Bio, Kusatsu, Japan), template cDNA dilution and real-time PCR. Here, GAPDH was set as normalization. The software of Premier 8.0 was applied to primers design (Table 1) for tsRNA and mRNA in the qRT-PCR assays.
Transfer RNA-derived small RNAs contain many seed sequences that may correspond to the cross-linked central regions of their target mRNAs. As tsRNAs show an miRNA-like function and can silence the expression of their target mRNAs, our group searched two algorithms to predict target mRNAs of treatment-related tsRNAs: tRFTar and tsRFun (25, 26). The genes, which were predicted by both algorithms at the same time, were considered significant.
The target genes corresponding to the differentially expressed tsRNAs were analyzed by Gene Ontology (GO) annotation as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation. The GO database is used for the classification of gene function and is the most comprehensive and widely used knowledge base focused on gene function. The functions indicated by the GO analysis of genes are divided into three major categories: cellular component (CC), molecular function (MF), and biological process (BP). Each GO entry corresponds to a P-value indicating significance, where the smaller the P-value is, the stronger the relationship between the GO entry and the corresponding differentially expressed gene. Kyoto Encyclopedia of Genes and Genomes is a database for systematically analyzing the metabolic pathways of gene products in cells and the functions of these gene products, which is helpful for understanding the higher-level systemic functions of cells and organisms, such as metabolic processes in cells, human diseases and biological functions. The smaller the P-value of each KEGG entry, the greater the relationship between the signal pathway corresponding to the KEGG entry and the differentially expressed gene.
Human umbilical vein endothelial cells obtained commercially from Haixing Biosciences (Suzhou, China) were cultured in sterile and thermostatic cell incubators with RPMI 1640 medium (Thermo Fisher Scientific, USA) supplemented with 10% fetal bovine serum (Thermo Fisher Scientific, USA). The cells were incubated in 5% carbon dioxide with saturated humidity at 37°C. During the exponential phase of growth, HUVECs were seeded into six-well plates at a density of 2 × 106 cells/well for transfection. The tRF-60:76-Val-AAC-1-M5 mimic (ACCGGGCGGAAACACCA) and the negative control (NC; UUUGUACUACACAAAAGUACUG) were obtained from Aksomics (Shanghai, China). According to the manufacturer’s instructions, the transfection of the mimic and NC was operated through Lipofectamine 3000 (Invitrogen, USA) at the concentration of 100 nmol. All experiments were performed in triplicate. And 48 h later, the transfected cells were harvested for RNA isolation. The relative mRNA levels of hsa05417 related genes were tested by qPCR. The specific primers are summarized in Table 1, and the relevant protocols were the same those as described above.
The statistic analysis was carried out with SPSS 22.0 software. The measurement data conforming to the normal distribution were expressed as the mean ± SD, and the comparisons between the two groups were performed via t-test. If the measurement data did not conform to a normal distribution, the data were analyzed with a non-parametric test. Count data were expressed as frequencies and percentages. The χ2 test or Fisher’s exact probability method was applied for comparisons between these groups. The diagnostic value of tsRNA was assessed via receiver operating characteristic (ROC) curve analysis. GraphPad Prism 8.0 software was adopted to assemble the figure panels.
A sum of 44 subjects (22 SVR and 22 NSVR) were included in our research. Ten of them were used for tsRNA expression profile analysis (5 SVR and 5 NSVR patients), and the other samples (17 SVR and 17 NSVR) were used for validation. The clinical characteristics of these 10 patients (5 SVR and 5 NSVR) are presented in Table 2. Except for the ARNI effect, the clinical baselines were identically matched, and no remarkable differences were observed between these two groups. The characteristics of the validation cohort are listed in Table 3. There was no obvious difference between the SVR and NSVR groups in terms of the basic clinical data, cardiac structure, or medication used except for the ARNI effect.
Transfer RNA-derived small RNAs sequencing (tsRNA-Seq) analysis (the data has been successfully deposited on the web of GEO) was used to assess the differential expression of tsRNAs in SVR and NSVR patients. The reads quality score and statistical information are shown in Supplementary Tables 1, 2. The aligned percentage depends on multiple factors, including sample quality, library quality, and sequencing quality. Table 4 was listed top five tsRNAs with the highest expression fold changes. A total of 683 tsRNAs were sequenced in present research, after comparing alignments with GtRNAdb (see text footnote 1) and tRNAscan-SE (see text footnote 2), of which 152 were included in the tRF database (mintbase and tRFbd), and the remaining 531 were not found in the database (Figures 1A,B). Figures 1C,E show the distribution of the numbers of tsRNA subtypes with a group average threshold Log2(CPM) ≥ 20 sequenced in this study. The tsRNA subtypes were reclassified according to the differences in the amino acids transported by the source tRNA and anti-codons (Figures 1D,F). We also drew a scatter diagram (Figure 1G) and a volcano diagram (Figure 1H) according to the expression differences between the SVR and NSVR groups. In the scatter plot, in SVR group, 146 tsRNAs were upregulated, and 121 tsRNAs were downregulated. As show in the volcano plot, 36 tsRNAs were upregulated and 21 were downregulated in SVR group.
We used a heatmap to cluster the data. The heatmap shows the differential expression of tsRNAs between SVR and NSVR patients (Figure 2A). The upregulated and downregulated tsRNAs are listed in Supplementary Data 1. We selected five tsRNAs with high FCs and complete data in expression profiles (tRF-1:28-Gly-GCC-1, tRF-1:29-Glu-CTC-1-M2, tRF-1:29-Gly-GCC-1, tRF-59:76-Tyr-GTA-2-M3, and tRF-60:76-Val-AAC-1-M5) to validate the tsRNA-Seq results in 17 SVRs and 17 NSVRs. As shown in Figures 2A–C, with the exception of tRF-1:28-Gly-GCC-1 and tRF-1:29-Glu-CTC-1-M2, the other three differentially expressed tsRNAs were consistent with the results of RNA sequencing. Relative to the NSVR group, the expression of tRF-59:76-Tyr-GTA-2-M3 (P < 0.01) and tRF-60:76-Val-AAC-1-M5 (P < 0.05) was upregulated, while the expression of tRF-1:29-Gly-GCC-1 (P < 0.05) was downregulated in the group with SVR. We further evaluated the diagnostic value of three differentially expressed tsRNAs using ROC curves. Figure 2D shows the ROC curves of tRF-59:76-Tyr-GTA-2-M3 and tRF-60:76-Val-AAC-1-M5. The areas under the ROC curves were, respectively, 0.875 and 0.847 and were thus greater than 0.5. Figure 2E shows the ROC curve of tRF-1:29-Gly-GCC-1, with downregulated expression, and the area under the ROC curve was 0.819. All of these results indicated that these three tsRNAs were potential biomarkers of the therapeutic heterogeneity of sacubitril/valsartan.
We used tRFTar (see text footnote 4) and tsRFun (see text footnote 5) to forecast the target mRNAs of the above differentially expressed tsRNAs. The biological function analysis showed that tRF-59:76-Tyr-GTA-2-M3 could target 261 genes, tRF-60:76-Val-AAC-1-M5 could target 517 genes, and tRF-1:29-Gly-GCC-1 could target 336 target genes (Supplementary Data 2). Meanwhile, the results of the GO enrichment analysis for tRF-59:76-Tyr-GTA-2-M3, tRF-60:76-Val-AAC-1-M5, and tRF-1:29-Gly-GCC-1 are shown in Figures 3A–C. Then, KEGG enrichment analysis was performed, and the results are shown in Figures 4A–C, which indicated that the target genes of tRF-60:76-Val-AAC-1-M5 might participate in regulation via the lipid and atherosclerosis pathway, the Ras signaling pathway, the NF-κB signaling pathway and insulin secretion (Table 5).
The hsa05417 (lipid and atherosclerosis) pathway is closely related to human diseases. A total of 6 genes were enriched in the lipid and atherosclerosis signaling pathway (CAMK2B, VAV3, PLCB3, NFATC3, TNFRSF10B, and BCL2L1), and these genes were regulated by tRF-60:76-Val-AAC-1-M5. We first compared the relative mRNA expression levels between SVR and NSVR patients and found that the mRNA expression of CAMK2B, TNFRSF10B, and BCL2L1 was lower in the SVR group (Figure 5A). Next, we carried out an experiment to reveal the relationship between tsRNAs and the target genes of hsa05417 in vitro. After overexpressing tRF-60:76-Val-AAC-1-M5 in HUVECs, Tnfrsf10b and Bcl2l1 were remarkably downregulated (P < 0.05), but Camk2b, Vav3, Plcb3, and Nfatc3 showed no change (P > 0.05) (Figure 5B). These results indicated that tRF-60:76-Val-AAC-1-M5 might target Tnfrsf10b and Bcl2l1 to influence the therapeutic heterogeneity of sacubitril/valsartan through the lipid and atherosclerosis signaling pathway.
Sacubitril/valsartan, which was the first dual enkephalinase and angiotensin receptor inhibitor to be developed, is a monocrystal formed by sacubitril and valsartan at a molar ratio of 1:1 (5). Sacubitril can be transformed into the active compound LBQ657 through metabolic processes and can inhibit the degradation of endogenous natriuretic peptides by enkephalinase, resulting in reduced sympathetic tension and relaxed blood vessels and promoting the excretion of urine and sodium (27). The other component, valsartan, can selectively act on the angiotensin II type I receptor, thereby reducing the production and release of angiotensin and aldosterone and inhibiting heart injury caused by excessive RAAS activity (28). Hence, this drug plays a dual cardioprotective role in AMI patients with HF. However, many AMI patients with HF do not benefit to cardiac function after treatment with sacubitril/valsartan. Results obtained from the CHAMP-HF registry (29) revealed that after treatment with sacubitril/valsartan, LVEF declined in 19% of patients and remained unchanged in 31%. These findings may be related to sex, drug doses, baseline LVEF, etiology, pacemaker implantation, and other factors, but the specific mechanism is not clear. Transfer RNA-derived small RNAs are a type of non-coding RNA with regulatory functions formed by the precise cleavage of tRNAs, including tRFs and tiRNAs, which can exert biological activity in a variety of ways (30). An increasing number of researches have reported that tsRNAs are inextricably linked with the pathological process of various diseases, especially tumors, inflammatory and immune diseases. In the cytoplasm of patients with breast cancer, mutated nucleotides have been identified in the tRNA-His-GUG at the 5′ end of the 5′ half. ANG selectively cleaves the tRNA missing the −1 nucleotide to form this specific tsRNA, which then accumulates, thus accelerating the progression of breast cancer (31). Another study showed that after Rickettsia bacteria infect the human body, they carry exogenous ANG into the nucleus of endothelial cells, activate RNA transcription, and then quickly enter the cytoplasm to induce the production of the smaller tRF-5S to promote the phosphorylation reaction of endothelial adhesion protein and reduce its stability, thereby weakening the function of the endothelial barrier and leading to the development of a maculopapular rash (32). Therefore, tsRNA has become a hotspot in various medical researches these days. In addition to the participation of tsRNA in the regulation of the occurrence and development of many disorders, for instance, tumors, alcoholic fatty liver, neurodegenerative diseases, infectious diseases, and stress diseases, tsRNA has now been confirmed to produce a marked effect on cardiovascular diseases (21, 22). tsRNA is also closely related to ventricular remodeling. Myocardial hypertrophy induced by isoproterenol was identified in an animal experiment. The expression of tsRNA in a rat model was shown to be more abundant than that in a healthy control group, in which tRFs1 and tRFs2 were positively correlated with the expression of the cardiac hypertrophy factors ANF, β-MHC, and NBP (33). Another study also showed that tRF-5 was abundant in the sperm of mice with myocardial hypertrophy and inhibited the mRNA expression of the hypertrophy regulator TIMP3 by binding its 3′UTR sequence, thereby aggravating cardiomyocyte hypertrophy, increasing cardiac fibrosis and promoting apoptosis (34). During this investigation, since we evaluated the expression profiles of tsRNAs and compared the differential expression of tsRNAs between SVR and NSVR patients and found that relative to the NSVR group, the expression of tRF-59:76-Tyr-GTA-2-M3 and tRF-60:76-Val-AAC-1-M5 was upregulated, while the expression of tRF-1:29-Gly-GCC-1 was downregulated in the group with SVR. ROC curve analysis revealed that these three tsRNAs were potential biomarkers of the therapeutic heterogeneity of sacubitril/valsartan. Another pharmacological study of Buyang-Huanwu decoction also indicated that tsRNA could be a novel therapeutic target in intracerebral hemorrhage (35). Although a study with a larger sample size will help further verify our conclusion, this study is the first to address the genetic contribution to the heterogeneity of sacubitril/valsartan and has revealed some key tsRNAs. All of these findings provide new perspectives for future exploration to explain the underlying mechanisms. Moreover, we performed GO enrichment analysis of the mRNAs targeted by tsRNAs and showed that the upregulated tsRNA-targeted mRNAs were mainly involved in the regulation of calcium and sodium transmembrane transport and action potential depolarization in atrial myocytes and atrioventricular node cells, among other BPs. Due to ischemia or the necrosis or apoptosis of cardiomyocytes in patients with AMI, ventricular contractility is reduced and heart pumping function is weakened, and this condition is often complicated by HF. The electrical conduction function of cardiomyocytes is destroyed simultaneously, which causes the heart to contract asynchronously, further increasing the development of stress failure. The upregulated differentially expressed tsRNAs may regulate the contractile activity of cardiomyocytes by affecting ion channels. The downregulated tsRNA-targeted mRNAs were mainly involved in angiogenesis. It is important to increase cardiac perfusion and promote the establishment of collateral circulation after myocardial infarction to improve the prognosis. A continuous cardiac hypoperfusion state leads to a progressive decline in cardiac function and even cardiogenic shock. Downregulated differentially expressed tsRNAs may significantly decrease cardiac function by inhibiting vascular remodeling and collateral angiogenesis. When we carried out enrichment analysis of KEGG pathway, we discovered that the target mRNAs of tRF-60:76-Val-AAC-1-M5 were enriched in the lipid and atherosclerosis signaling pathway, NF-κB signaling pathway, and Ras pathway, which are involved in the regulation of SVR. Previous articles have reported that the above three pathways are intensively correlated to the inflammatory immune response, atherosclerosis and angiogenesis (36, 37). Although tRNA was one of the highly modified RNAs in cells, a latest study found that unmodified tRF-3 could also result in gene silencing through luciferase reporting experiments (38). In this study, our group used unmodified tRF fragments for overexpression research and confirmed that tRF-60:76-Val-AAC-1-M5 might target Tnfrsf10b and Bcl2l1 to influence the therapeutic heterogeneity of sacubitril/valsartan through the lipid and atherosclerosis signaling pathway. In AMI patients with HF, if a lipid metabolism disorder or arteriosclerosis progress cannot be controlled, it is not conducive to the regeneration of blood vessels, the recovery of the myocardium and the improvement of cardiac function after myocardial infarction. Second, NF-κB is the most important regulator of the inflammatory response (39). Studies have shown that under the stress imposed by AMI (40), proinflammatory factors bind to TNF receptors on the cell membrane and activate the specific phosphorylation of the serine residue of κB, resulting in the activation of NF-κB, its entry into the nucleus; in the nucleus, NF-κB acts on gene promoters to accelerate the pathological process of atherosclerosis by advancing an inflammatory response, damaging the vascular endothelium, promoting the proliferation and migration of VSMCs and promoting vascular cell apoptosis (41). Finally, studies have revealed that RAS is closely related to angiogenesis (42). VEGF is a specific mitogen of endothelial cells that targets endothelial cells and plays a large role in promoting endothelial cell mitosis and angiogenesis. Activated Ras can activate the VEGF transcription factor through the Ras-Raf-ERK1/2 signaling pathway (43), and RAS can improve the stability of VEGF mRNA through the Ras-Rac-MEKK1-JNKK signaling pathway (44) to enhance the expression of VEGF and promote angiogenesis (45). All of the above signaling pathways might participate in the regulation of cardiac function after MI and provide new insights for investigating SVR mechanisms. Hence, on the basis of the present study, it could construct a new prediction system for identifying the patients promptly without a clear benefit from sacubitril/valsartan in HF patients after AMI, and it could significantly help to select patients benefiting from alternative approaches such as cardiac resynchronization therapy (CRT), device therapy, and even LVAD implantation. What was more, the above findings would give the opportunity to better classify the molecules and pathways activated in SVR patients, which might represent an additional benefit to identifying the new molecular targets to improve the outcome of the optimal medical therapy. Although we made great efforts to avoid errors in this research, this study still has inherent limitations. First, the drug response might be affected by additional factors, such as pharmacodynamics and the internal environment. The possible influence of these confounding factors on our results cannot be excluded. Moreover, is was a single-center study, in which the population included were the patients with AMI complicated by HF. The confirmation of the obtained conclusion will require a larger sample size to increase the reliability of present results. Finally, in vivo animal validation studies and a more in-depth mechanistic exploration will improve our understanding in the future.
To sum up, this research determined the expression profiles of tsRNAs in SVR and NSVR patients and found that the expression of tRF-59:76-Tyr-GTA-2-M3 and tRF-60:76-Val-AAC-1-M5 was upregulated, while the expression of tRF-1:29-Gly-GCC-1 was downregulated in the group with SVR. ROC curve analysis indicated that these three tsRNAs can potentially be used as biomarkers of the therapeutic heterogeneity of sacubitril/valsartan. Moreover, tRF-60:76-Val-AAC-1-M5 might target Tnfrsf10b and Bcl2l1 to influence this therapeutic heterogeneity through the lipid and atherosclerosis signaling pathway. These discoveries provide new insights for the mechanistic investigation of the responsiveness of sacubitril/valsartan and will help clinicians identify prognostic benefits in patients to realize individualized treatment.
Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE207882.
The studies involving human participants were reviewed and approved by the Ethics Committee of Ningbo No. 1 Hospital. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.
JS, KZ, WD, and XC designed the experiments. JC, YH, QY, ZL, JL, ZeZ, XL, and JS carried out the experiments. NZ, ZhZ, and JY analyzed the experimental results. JS, JC, and YH wrote the manuscript. YW, WD, and XC contributed to helping with project administration and manuscript review and editing. All authors contributed to the article and approved the submitted version. | true | true | true |
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PMC9558999 | Feng Wu,Jian-Ying Wang,Brooke Dorman,Ahmad Zeineddin,Rosemary Ann Kozar | c-Jun-mediated miR-19b expression induces endothelial barrier dysfunction in an in vitro model of hemorrhagic shock | 12-10-2022 | Lung microvascular endothelial cells,Hypoxia/reoxygenation,miR-19b,c-Jun,Endothelial barrier | Background Our previous data demonstrated that miR-19b expression was increased in human lung microvascular endothelial cells in-vitro-, in-vivo and in patients with hemorrhagic shock, leading to a decrease in syndecan-1 mRNA and protein and resulting in loss of endothelial barrier function. However, the mechanism underlying increased miR-19b expression remains unclear. The objective of the current study was to determine if c-Jun mediates the early responsive microRNA, miR-19b, to cause endothelial barrier dysfunction. Method Human lung microvascular endothelial cells (HLMEC) or HEK293T cells were transfected with c-Jun overexpressing vector, c-Jun siRNA, miR-19b promoter vector, miR-19b mutated promoter vector, miR-19b oligo inhibitor, then subjected to hypoxia/reoxygenation as in-vitro model of hemorrhagic shock. Levels of protein, miRNA, and luciferase activity were measured. Transwell permeability of endothelial monolayers were also determined. Plasma levels of c-Jun were measured in injured patients with hemorrhagic shock. Result Hypoxia/reoxygenation induced primary (pri-)miR-19b, mature miR-19b, and c-Jun expression over time in a comparable timeframe. c-Jun silencing by transfection with its specific siRNA reduced both pri-miR-19b and mature miR-19b levels. Conversely, c-Jun overexpression enhanced H/R-induced pri-miR-19b. Studies using a luciferase reporter assay revealed that in cells transfected with vectors containing the wild-type miR-19b promoter and luciferase reporter, c-Jun overexpression or hypoxia/ reoxygenation significantly increased luciferase activity. c-Jun knockdown reduced the luciferase activity in these cells, suggesting that the miR-19b promoter is directly activated by c-Jun. Further, chromatin immunoprecipitation assay confirmed that c-Jun directly bound to the promoter DNA of miR-19b and hypoxia/reoxygenation significantly increased this interaction. Additionally, c-Jun silencing prevented cell surface syndecan-1 loss and endothelial barrier dysfunction in HLMECs after hypoxia/reoxygenation. Lastly, c-Jun was significantly elevated in patients with hemorrhagic shock compared to healthy controls. Conclusion Transcription factor c-Jun is inducible by hypoxia/reoxygenation, binds to and activates the miR-19b promoter. Using an in-vitro model of hemorrhagic shock, our findings identified a novel cellular mechanism whereby hypoxia/ reoxygenation increases miR-19b transcription by inducing c-Jun and leads to syndecan-1 decrease and endothelial cell barrier dysfunction. This finding supports that miR-19b could be a potential therapeutic target for hemorrhage shock. Supplementary Information The online version contains supplementary material available at 10.1186/s10020-022-00550-0. | c-Jun-mediated miR-19b expression induces endothelial barrier dysfunction in an in vitro model of hemorrhagic shock
Our previous data demonstrated that miR-19b expression was increased in human lung microvascular endothelial cells in-vitro-, in-vivo and in patients with hemorrhagic shock, leading to a decrease in syndecan-1 mRNA and protein and resulting in loss of endothelial barrier function. However, the mechanism underlying increased miR-19b expression remains unclear. The objective of the current study was to determine if c-Jun mediates the early responsive microRNA, miR-19b, to cause endothelial barrier dysfunction.
Human lung microvascular endothelial cells (HLMEC) or HEK293T cells were transfected with c-Jun overexpressing vector, c-Jun siRNA, miR-19b promoter vector, miR-19b mutated promoter vector, miR-19b oligo inhibitor, then subjected to hypoxia/reoxygenation as in-vitro model of hemorrhagic shock. Levels of protein, miRNA, and luciferase activity were measured. Transwell permeability of endothelial monolayers were also determined. Plasma levels of c-Jun were measured in injured patients with hemorrhagic shock.
Hypoxia/reoxygenation induced primary (pri-)miR-19b, mature miR-19b, and c-Jun expression over time in a comparable timeframe. c-Jun silencing by transfection with its specific siRNA reduced both pri-miR-19b and mature miR-19b levels. Conversely, c-Jun overexpression enhanced H/R-induced pri-miR-19b. Studies using a luciferase reporter assay revealed that in cells transfected with vectors containing the wild-type miR-19b promoter and luciferase reporter, c-Jun overexpression or hypoxia/ reoxygenation significantly increased luciferase activity. c-Jun knockdown reduced the luciferase activity in these cells, suggesting that the miR-19b promoter is directly activated by c-Jun. Further, chromatin immunoprecipitation assay confirmed that c-Jun directly bound to the promoter DNA of miR-19b and hypoxia/reoxygenation significantly increased this interaction. Additionally, c-Jun silencing prevented cell surface syndecan-1 loss and endothelial barrier dysfunction in HLMECs after hypoxia/reoxygenation. Lastly, c-Jun was significantly elevated in patients with hemorrhagic shock compared to healthy controls.
Transcription factor c-Jun is inducible by hypoxia/reoxygenation, binds to and activates the miR-19b promoter. Using an in-vitro model of hemorrhagic shock, our findings identified a novel cellular mechanism whereby hypoxia/ reoxygenation increases miR-19b transcription by inducing c-Jun and leads to syndecan-1 decrease and endothelial cell barrier dysfunction. This finding supports that miR-19b could be a potential therapeutic target for hemorrhage shock.
The online version contains supplementary material available at 10.1186/s10020-022-00550-0.
miRNAs have been linked to endothelial cell dysfunction (Zheng et al. 2021; Chang et al. 2021). We have been interested in the molecular mechanisms regulating endothelial cell dysfunction after hemorrhagic shock (Wu et al. 2021; Chipman et al. 2021) and identified miR-19b as a key molecule (Wu et al. 2020). miR-19b belongs to the miR-17-92 family of miRNA clusters. This miRNA has been shown to play a role in cancer and to be associated with both acute inflammatory conditions such as sepsis as well as chronic inflammatory conditions such as diabetes, rheumatoid arthritis and atherosclerosis (Hu et al. 2018; Li et al. 2018; lv et al. 2014; Niu et al. 2018). Li et al. demonstrated elevated systemic levels of miR-19b in patients with unstable angina and documented its endothelial cell origin (Li et al. 2014; Li et al. 2019). Endothelial cell dysfunction can be caused by oxidative stress from hypoxia and is a key mechanism of cellular damage. We have previously demonstrated miR-19b inhibited syndecan-1, leading to lung vascular leakage after hemorrhage shock (Wu et al. 2021; Chipman et al. 2021). Additionally, miR-19b inhibition attenuated inflammation and vascular leakage in shock lungs (Wu et al. 2020; Chipman et al. 2021). These results support that miR-19b is a pro-inflammatory miRNA that leads to endothelial barrier dysfunction. However, the exact mechanism by which miR-19b expression is regulated remains unknown. During hypoxia/oxygenation in-vitro or hemorrhagic shock in-vivo, hypoxia triggers changes in metabolism, the intracellular redox state, and the expression of acute phase proteins (de Jager et al. 2021; Sims and Baur 2017). Reperfusion of ischemic tissues is then associated with an induction in reactive oxygen species (ROS) that cause direct cell damage by oxidation of cellular components (Sims et al. 2017), and indirectly through the activation of early responsive genes, such as c-Jun N-terminal kinases (JNK) (Yang et al. 2013; Relja et al. 2009). Following activation, JNK translocate into the nucleus where they physically associate with and activate their targets, one of which is c-Jun. c-Jun is a member of the Jun family of proteins that are primary components of the activating protein (AP-1) transcription factor (Paxian et al. 2002; Relja et al. 2009). AP-1 regulates a number of miRNAs by directly binding to their target promoters at specific DNA elements (Zhang et al. 2018; Zhong et al. 2019). Although c-Jun, JunB, and JunD have similar DNA binding affinity, their expression patterns vary, with c-Jun being an immediate early response gene that has been implicated in organ damage and inflammation following hemorrhagic shock (Dosch and Kaina 1996; Relja et al. 2009). In the current study, we sought to investigate if c-Jun induces miR-19b early responsive expression to mediate endothelial barrier dysfunction.
Human lung microvascular endothelial cells (HLMEC; Sigma) were grown to confluence in endothelial basic medium-2 (EBM-2; Lonza) supplemented with 5% FBS, human recombinant epidermal growth factor, human recombinant insulin-like growth factor-1, human basic fibroblast growth factor, vascular endothelial growth factor, hydrocortisone, ascorbic acid, heparin, gentamicin, and amphotericin B. Endothelial cells (passages 5–10) were used for following experiments.
H/R was used as an in-vitro model of hemorrhagic shock and was conducted as we described previously (Wu et al. 2021). For normoxia, cells were cultured in EBM-2. For H/R, cells were cultured in EBM2 and exposed to 94% N2, 1% oxygen, and 5% CO2 for 18 h followed by normoxia for indicated periods of time in the figure legends.
Endothelial cells were lysed in NuPAGE LDS samples buffer (Thermo Scientific) for Western blot analysis using antibodies including anti-c-Jun (#9165, Cell Signaling Technology). Blots were also probed with anti-GAPDH antibody (PA1-987, Thermo Scientific) for the reference of sample loading.
Total RNA was extracted from cells using Trizol reagent and was reversely transcribed using Qiagen miScript RT kit. Real-time PCR was performed using Qiagen miScript SYBR Green PCR kit and miR-19b-3p miScript Primer (Qiagen). Pri-miR-19b (hsa-mir-92a-1 primer assay) and mature miR-19b primer was obtained from Taqman. RNU6 miScript Primer (Qiagen) was used as an endogenous control. Relative RNA amount was calculated using the 2−ΔΔCt method.
HLMECs were seeded in 6-well plates and grown for 24 h in antibiotic-free EBM-2 containing 5% FBS and supplements. Cells were then transiently transfected by incubation with 100 nM miR-19b oligo inhibitor, c-Jun siRNA, or scrambled RNA (scRNA) and 2.5 ul/ml Lipofectamine 2000 (Thermo Fisher Scientific) in antibiotic-free Opti-MEM for 24 h. The medium was then changed to the growth medium, and the cells were cultured for another 48 h prior to assays. Silencing of the respective proteins was validated by quantitative real-time PCR or Western blot analysis.
HEK293T cells were transfected with pMIEG3-c-Jun overexpression vector or empty vector (pMIEG3) obtained from Addgen (Watertown, MA) using Lipofectamine 2000 following the manufacturer’s recommended procedures. After 3 day-transfection, the expression of c-Jun-GFP was examined under inverted fluorescent microscopy and images obtained. The cells were further exposed to hypoxia for 18 h or exposed to normoxia only for pri-miR-19b induction.
The full human miR-19b promoter (miR-17-92 gene cluster promoter, positions 5786 to 8494 in accession# NG_032702) was inserted into lentivirus pEZX-LvPG04 dual-reporter vector (GeneCopoeia, MD). This vector uses Gluc (Gaussia Luciferase) as the promoter reporter and SEAP (secreted Alkaline Phosphatase) as the internal control for signal normalization. Mutated miR-19b promoter vector was produced by GeneCopoeia by deleting the two c-Jun binding sites at positions 6237–6243 (TGACTCT) and 7495–7501 (TGTGTCA) in accession# NG_032702 as predicted by PROMO (http://alggen.lsi.upc.es/cgi-bin/promo_v3/promo/promoinit.cgi?dirDB=TF8.3) using 3% dissimilarity in comparison to the c-Jun consensus sequence (TGAC/GTCA). HEK293T cells were transfected with the vectors containing wild-type miR-19b promoter, mutated miR-19b promoter, or empty vectors in 96-well plates. Some HEK293T cells were also co-transfected with pMIEG3-c-Jun overexpression vector (Addgen, MA) to overexpress c-Jun or empty vector (pMIEG3) for negative control. Some HEK293T cells were exposed to hypoxia for 18 h then normoxia for 3 h to induce c-Jun overexpression. The culture medium of the transfected cells was harvested for assays of promoter activity using Secrete-Pair™ Gaussia Luciferase Dual Luminescence Assay Kit (GeneCopoeia). In the assay, the activities of Gluc and SEAP were detected and Gluc activity was normalized to SEAP activity.
HLMECs were grown directly on 8-well chambers (Corning). Cells were then transiently transfected by incubation with 100 nM c-Jun siRNA or scrambled RNA (scRNA) and 2.5 μl/ml Lipofectamine 2000 in antibiotic-free Opti-MEM for 24 h. The medium was then changed to the growth medium, and the cells were cultured for another 48 h prior to assays. Silencing of the respective proteins was validated by Western blot analysis. After being exposed to hypoxia (94% N2, 1% oxygen, and 5% CO2) for 18 h, cells were fixed in 4% paraformaldehyde for 15 min and blocked with 2% bovine serum albumin (BSA) in PBS for 1 h at room temperature. Cells were then incubated with anti-syndecan1 antibody (1:100; Cell Signaling) in 1% BSA at 4 °C overnight and followed by incubating with Alexa fluor 488 conjugated anti-mouse IgG (1:200; Invitrogen) in 1% BSA for 2 h at room temperature. The fluorescence intensity was quantified using Quantity One and reported as relative fluorescence units.
HLMECs were seeded on culture inserts (3 μm pore size, Costar) in 24-well companion plates and grown to confluence in EBM-2 containing 5% FBS and supplements. In some experiments, monolayers were transfected with 100 nM miR-19b oligo inhibitor, c-Jun siRNA, or scRNA before seeding the inserts. Subsequently, FITC-labeled dextran (40 kDa, Sigma) was added to the upper chamber at a concentration of 100 μg/ml, and phosphate buffered saline (PBS) to the lower chamber (to prevent the formation of an oncotic pressure gradient) for 1 h. Medium was collected from the lower chamber, and the fluorescence was measured using a fluorimeter (485 nm excitation, 530 nm emission). The fold change in FITC-dextran fluorescence intensity over controls was used as a measure of monolayer permeability.
After exposure to hypoxia for 18 h then normoxia for 3 h, cells were fixed with 1% formaldehyde to crosslink chromatin. Chromatin immunoprecipitation (ChIP) analysis was performed using Piece Magnetic ChIP kit (cat# 26157) and anti-c-Jun antibody (cs#39165, Cell Signaling Technology). The bound-DNA was isolated and purified for quantitative PCR. As described above, the miR-19b promoter contains two c-Jun binding sites at positions 6237–6243 (TGACTCT) and 7495–7501 (TGTGTCA). The primers to detect DNA around position 6237–6243 were 5′-CCTTGTGCGACATGTGCTG -3′ and 5′-GATGGCATGCCGTTAATTTT -3′ (174 bp) and around position 7495–7501 were 5′-GCCACGTGGATGTGAAGATT -3′ and 5′- AAGTGGTGGCTCTTCCAATG -3′ (165 bp). Isotype IgG was used as a negative control. DNA isolated from the whole cell lysates served as input DNA control.
Available plasma samples from a recently completed prospective observational clinical study in trauma patients (Zeineddin et al. 2022) were used to measure c-Jun. The present study was approved by the Institutional Review Board of the University of Maryland Baltimore. Informed consent was obtained from all patients and included the consent to investigate biologic markers of endothelial dysfunction in the present study. Samples were de-identified and stored prior to bulk analysis. All experimental procedures were conducted in compliance with the University of Maryland Baltimore and the National Institutes of Health guidelines. This study included severely injured patients in hemorrhage shock, defined as a systolic blood pressure < 90 mm Hg and requiring blood component therapy upon arrival. Plasma was collected at admission in the trauma bay and stored in – 80 °C until time of experiment. For healthy donor controls, aliquots were obtained from 13 random donor units of fresh frozen plasmas obtained from Tennessee Blood Services (Memphis, TN). Plasma c-Jun was measured by ELISA (catalog# NBP2-75279, Novus Biologicals).
Data are expressed as mean ± SE. Values from different groups were analyzed by T test or one-way analysis of variance (ANOVA) with Bonferroni multiple comparison tests with significance set at level at p < 0.05.
We proposed that miR-19b is a miRNA responsive to H/R and thus measured pri-miR-19b and mature miR-19b. As shown in Fig. 1A and B, pri-miR-19b was significantly increased in the cells immediately after hypoxia, remained significantly high at 3 h post H/R, and returned to baseline levels at 6 h post H/R. Mature miR-19b began to increase immediately after hypoxia, it was significantly increased at 3 h post H/R but decreased to baseline levels at 6 h. The time delay may reflect the processing time from pri-miR-19b to mature miR-19b. Cells respond to H/R by activating a number of transcription factors, including activator protein 1 (AP-1), and c-Jun protein is a component of H/R-induced AP-1 complex (Yang et al. 2013; Relja et al. 2009). Our results indicate that hypoxia alone significantly increased c-Jun protein expression and it remained elevated at 3 h post H/R compared with normoxic control (Fig. 1C and D). c-Jun expression then decreased over time during normoxia, returning to baseline levels by 6 h.
To study the regulatory effects of c-Jun on miR-19b transcription, we first used small interfering RNA (siRNA) to examine the influence of c-Jun silencing on miR-19b expression in endothelial cells. As shown in Fig. 2A, c-Jun protein was increased by H/R but substantially diminished after siRNA transfection in both normoxic and H/R cells, whereas GAPDH protein remained unchanged. c-Jun knockdown significantly reduced levels of both pri-miR-19b and mature miR-19b in normoxic and H/R cells whereas scrambled RNA cells had the expected increase in pri-miR-19b and mature miR-19b after H/R (Fig. 2B and C). These results indicate that miR-19 expression is dependent upon c-Jun. Previously we have identified that miR-19b targeted syndecan-1 mRNA and decreased syndecan-1 expression, leading to lung vascular leakage in mice after hemorrhage shock (Wu et al. 2020). To investigate the biologic consequences of c-Jun-mediated enhancement of miR-19b expression, we first measured the expression of cell surface syndecan-1 after exposure to H/R. The representative phase contrast images are shown in Fig. 2D. Our results indicated that H/R significantly decreased cell surface syndecan-1 and this decrease was attenuated by c-Jun silencing with siRNA, confirming that c-Jun mediated syndecan-1 inhibition in H/R (Fig. 2E and F). We further examined c-Jun/miR-19b pair involvement in regulating endothelial cell permeability. Transfection with miR-19b oligo inhibitor or siRNA targeting c-Jun attenuated H/R-induced monolayer hyperpermeability (Fig. 2G and H), supporting that c-Jun-dependent miR-19b expression mediates endothelial barrier dysfunction. We next examined the effect of over-expressing c-Jun gene on the expression level of miR-19b by transfecting HEK293T cells with pMIEG3-c-Jun overexpression vector (cJun-ov) or empty vector control (Ctrl) then exposed the cells to H/R or normoxia. As shown in Fig. 3A and B, transfection of pMIEG3-c-Jun overexpression vector induced large amounts of c-Jun protein in cells as demonstrated by both immunofluorescent microscopy and Western blot analysis. We next measured the pri-miR-19b in cells after overexpression of c-Jun in normoxic and H/R conditions and found that H/R induced a threefold increase in the cells transfected with empty vector. However, H/R induced a 14-fold increase in the cells transfected with pMIEG3-c-Jun overexpression vector (Fig. 3C). These results further documented that miR-19b expression is dependent upon c-Jun (Additional file 1).
In the following experiments, we used a luciferase reporter assay to determine if miR-19b promoter is activated by c-Jun. As shown in Fig. 4A, we prepared three types of miR-19b promoter vectors containing luciferase reporter: wild-type miR-19b promoter, mutated miR-19b promoter, and empty vectors. Compared with the cells transfected with empty vector, cells transfected with wild-type miR-19b promoter vector had significantly higher baseline luciferase activity (Fig. 4B). However, following transfection with pMIEG3-c-Jun overexpression vector, cells transfected with miR-19b promoter vector expressed twofold higher levels of luciferase activity compared with the cells transfected with empty vector (Fig. 4B). When cells were transfected with promoter vector and exposed to H/R, there was a significant increase in luciferase activity compared to empty vector H/R controls (Fig. 4C). Western blot analysis confirmed that cells exposed to H/R had increased c-Jun protein levels (Fig. 4D). To examine if the constitutive c-Jun expression in HEK293T cells may contribute to the increase in baseline luciferase activity in cells after transfecting with miR-19b promoter vector, we thus silenced c-Jun protein expression in HEK293T cells using siRNA knockdown. As shown in Fig. 4E, HEK293 cells transfected with miR-19b promoter vector expressed about a twofold higher baseline luciferase activity compared with the cells transfected with empty vector. c-Jun knockdown reduced luciferase activity in either promoter vector-transfected cells or empty vector-transfected cells, supporting the notion that miR-19b promoter is activated by c-Jun. We proposed that c-Jun targets miR-19b promoter DNA to initiate transcription and predicated two possible binding sites for c-Jun (AP1) binding at positions 6237–6243 (TGACTCT) and 7495–7501 (TGTGTCA). We thus produced a mutated miR-19b promoter vector by deleting these two c-Jun (AP1) binding sites. As shown in Fig. 4F, HEK293T cells co-transfected with wild-type miR-19b promoter vector plus pMIEG3-c-Jun overexpression vector demonstrated significantly increased luciferase activity compared with the cells transfected with wild-type miR-19b promoter vector plus c-Jun empty vector. However, when transfected with the mutated miR-19b promoter vector plus pMIEG3-c-Jun overexpression vector, the increase in luciferase activity was attenuated. These results further support that the miR-19b promoter is activated by c-Jun.
Using chromatin immunoprecipitation (ChiP) assay and anti-c-Jun antibody, we next isolated the c-Jun-bound DNA and performed quantitative PCR using two pairs of primers shown in Fig. 5A. We found that c-Jun bound to position #7495–7501 but not to position # 6237–6243 and that c-Jun antibody trapped more miR-19b promoter DNA in cells exposed to H/R than in the cells exposed to normoxia (Fig. 5B), with approximately a sevenfold increase after H/R (Fig. 5C). These data therefore confirmed that c-Jun directly interacts with the promoter of miR-19b, suggesting direct regulation of miR-19b promoter activity.
We measured plasma c-Jun in 25 trauma/hemorrhage shock patients and 13 heathy donors. The results indicated that hemorrhage shock patients had a significantly higher level of plasma c-Jun compared to healthy donor controls (121 ± 22 vs 64 ± 18 ng/ml, p < 0.05) (Fig. 6), indicating that c-Jun is an early responsive gene after hemorrhage shock. Demographic data is shown in Additional file 1.
Among multiple mechanisms involved in the pathogenesis of endothelial cell dysfunction following hemorrhagic shock, miR-19b has emerged as a novel microRNA contributing to endothelial dysfunction (Wu et al. 2020). To study the molecular mechanisms governing the response in endothelial cells after hemorrhage, we developed an in-vitro model of hemorrhagic shock which was used in the current study (Wu et al. 2020; Peng et al. 2013). We have now uncovered that miR-19b is an early responsive miRNA which is mediated by transcription factor c-Jun. Further, we found that circulating c-Jun protein was indeed increased in the plasma of severely injured patients with hemorrhage shock. In other ischemia conditions such as stroke and myocardial infarction, miR-19b has been identified as an early responsive miRNA. For examples, miR-19b is up-regulated in response to oxygen glucose deprivation in an in-vitro model of ischemia in neuroblastoma cells (Dhiraj et al. 2013) and has been reported to be upregulated in a rodent model of cerebral artery occlusion (Jeyaseelan et al. 2008). Circulating miR-19b levels are increased in patients with acute myocardial infarction (Wang et al. 2016) and are associated with the development of diabetic cardiomyopathy (Copier et al. 2017). miR-19b has also been reported to be a downstream effector of vascular endothelial growth factor (VEGF) (Chamorro-Jorganes et al. 2016), which mediates angiogenesis and vascular leakage (Chamorro-Jorganes et al. 2016; Zhang et al. 2000). Barrier dysfunction with its associated vascular leakage is an important sequalae after hemorrhage and one we have shown is mediated by miR-19b. Hemorrhagic shock is known to induce a global stress response following cellular hypoperfusion and hypoxia with release of pro-inflammatory cytokines into the systemic circulation. c-Jun-N-terminal kinase (JNK) is activated by cytokines and prior studies have demonstrated the important role of tissue hypoxia in its activation. We determined that circulating c-Jun protein was increased in hemorrhage shock in the present study. Hepatic JNK activation has been demonstrated in in-vivo models of liver ischemia/reperfusion (Bradham et al. 1997) and in in-vitro models of hepatocyte H/R (Crenesse et al. 2001). Additionally, McCloskey et al (2004) identified tissue hypoxia as a key factor in activating early signaling events in the liver following hemorrhagic shock as measured by JNK phosphorylation while Relja et al (2009) demonstrated liver protection by JNK inhibition following hemorrhage. There is less known, however, on the role of JNK in endothelial cells. Zakkar et al (2008) found that JNK was activated constitutively in endothelial cells at atherosusceptible sites but expressed in its an inactive form at atheroprotected sites, suggesting that a pro-inflammatory or pro-hypoxia environment is important. This is consistent with the current study in that c-Jun was present constitutively in endothelial cells, but its expression was markedly increased by hypoxia. Upon activation, JNK regulates the activity of several transcription factors, including c-Jun, ATF-2, Elk-1, p53, and c-Myc, and is involved in the regulation of many cellular functions from proliferation to cell death. c-Jun is a major component of the AP-1 transcriptional complex. It can form either homodimers or heterodimers with other AP-1 components from the Jun family (Jun B and Jun D) or the Fos family (c-Fos, Fra-1, Fra-2, and Fos B), which directly bind to AP-1 consensus site (Angel and Karin 1991). In the present study, we documented that miR-19b expression is mediated by c-Jun which has been shown to have pathologic effects in vascular endothelial cells (Wang et al. 1999). Indeed, our results indicate that H/R induces pri-miR-19b, mature miR-19b, and c-Jun expression over time in a comparable timeframe in human endothelial cells. c-Jun silencing by siRNA transfection reduced both pri-miR-19b and mature miR-19b expression. Conversely, c-Jun overexpression enhanced H/R-induced pri-miR-19b. Using a luciferase reporter assay, we observed that in cells transfected with vectors containing the wild-type miR-19b promoter and luciferase reporter, c-Jun overexpression or H/R significantly increased luciferase activity. c-Jun knockdown reduced the luciferase activity in these cells, suggesting that the miR-19b promoter is directly activated by c-Jun. Finally, as assessed by chromatin immunoprecipitation assay, we confirmed that c-Jun binds to the promoter DNA of miR-19b and H/R significantly increased this interaction. Our previous study demonstrated that miR-19b targeted syndecan-1 mRNA and decreased syndecan-1 expression, leading to lung vascular leakage in mice after hemorrhage shock. Overexpression of miR-19b reduced syndeccan-1 expression and increased permeability in pulmonary endothelial cells after H/R (Wu et al. 2020; Chipman et al. 2021). The present study further confirmed that c-Jun mediates miR-19b increase, cell surface syndecan-1 decrease, and endothelial barrier dysfunction in H/R. Additionally, circulating c-Jun protein was increased in the plasma of severely injured patients with hemorrhage shock.
Transcription factor c-Jun is inducible by hypoxia/reoxygenation, and it binds to and activates the miR-19b promoter. Using an in-vitro model of hemorrhagic shock, our findings identified a novel cellular mechanism whereby hypoxia/reoxygenation increases miR-19b transcription by inducing c-Jun and leads to syndecan-1 decrease and endothelial cell barrier dysfunction. Our results also show that c-Jun is increased in patients with hemorrhagic shock. Thus, our study supports that miR-19b could be a potential therapeutic target for hemorrhage shock.
Additional file 1. Additional Table 1: Trauma/hemorrhage shock patient demographics | true | true | true |
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PMC9559204 | Seungwha Paik,Kyeong Tae Kim,In Soo Kim,Young Jae Kim,Hyeon Ji Kim,Seunga Choi,Hwa-Jung Kim,Eun-Kyeong Jo | Mycobacterial acyl carrier protein suppresses TFEB activation and upregulates miR-155 to inhibit host defense | 28-09-2022 | Mycobacterium tuberculosis,transcription factor EB,phagosome-lysosome fusion,microRNA-155-5p,acyl carrier protein,bone marrow-derived macrophages | Mycobacterial acyl carrier protein (AcpM; Rv2244), a key protein involved in Mycobacterium tuberculosis (Mtb) mycolic acid production, has been shown to suppress host cell death during mycobacterial infection. This study reports that mycobacterial AcpM works as an effector to subvert host defense and promote bacterial growth by increasing microRNA (miRNA)-155-5p expression. In murine bone marrow-derived macrophages (BMDMs), AcpM protein prevented transcription factor EB (TFEB) from translocating to the nucleus in BMDMs, which likely inhibited transcriptional activation of several autophagy and lysosomal genes. Although AcpM did not suppress autophagic flux in BMDMs, AcpM reduced Mtb and LAMP1 co-localization indicating that AcpM inhibits phagolysosomal fusion during Mtb infection. Mechanistically, AcpM boosted the Akt-mTOR pathway in BMDMs by upregulating miRNA-155-5p, a SHIP1-targeting miRNA. When miRNA-155-5p expression was inhibited in BMDMs, AcpM-induced increased intracellular survival of Mtb was suppressed. In addition, AcpM overexpression significantly reduced mycobacterial clearance in C3HeB/FeJ mice infected with recombinant M. smegmatis strains. Collectively, our findings point to AcpM as a novel mycobacterial effector to regulate antimicrobial host defense and a potential new therapeutic target for Mtb infection. | Mycobacterial acyl carrier protein suppresses TFEB activation and upregulates miR-155 to inhibit host defense
Mycobacterial acyl carrier protein (AcpM; Rv2244), a key protein involved in Mycobacterium tuberculosis (Mtb) mycolic acid production, has been shown to suppress host cell death during mycobacterial infection. This study reports that mycobacterial AcpM works as an effector to subvert host defense and promote bacterial growth by increasing microRNA (miRNA)-155-5p expression. In murine bone marrow-derived macrophages (BMDMs), AcpM protein prevented transcription factor EB (TFEB) from translocating to the nucleus in BMDMs, which likely inhibited transcriptional activation of several autophagy and lysosomal genes. Although AcpM did not suppress autophagic flux in BMDMs, AcpM reduced Mtb and LAMP1 co-localization indicating that AcpM inhibits phagolysosomal fusion during Mtb infection. Mechanistically, AcpM boosted the Akt-mTOR pathway in BMDMs by upregulating miRNA-155-5p, a SHIP1-targeting miRNA. When miRNA-155-5p expression was inhibited in BMDMs, AcpM-induced increased intracellular survival of Mtb was suppressed. In addition, AcpM overexpression significantly reduced mycobacterial clearance in C3HeB/FeJ mice infected with recombinant M. smegmatis strains. Collectively, our findings point to AcpM as a novel mycobacterial effector to regulate antimicrobial host defense and a potential new therapeutic target for Mtb infection.
Tuberculosis (TB) is a worldwide infectious disease that has claimed many lives, and the fight against TB still faces many challenges. According to the World Health Organization’s global TB report 2020, TB caused an estimated 10 million new cases and 1.5 million deaths in 2020, making it the second most deadly infectious disease caused by a single pathogen after COVID-19. Mycobacterium tuberculosis (Mtb), the bacteria that causes tuberculosis, has a variety of defense mechanisms to evade the host’s innate immune system, including autophagy, apoptosis, and inflammation (1). Mtb can also survive as a latent infection for a long time in alveolar macrophages, making it resistant to anti-TB drugs and difficult to eradicate (2). To control Mtb, it’s crucial to understand the dynamics of the host-pathogen interaction. To date, several mycobacterial factors, such as SapM (3), ESAT-6/CFP-10 (4), nuoG (5), Eis (6), LprG (7), PE_PGRS47 (8), SecA2 (9, 10), LprE (11), PknG (12), and phthiocerol dimycocerosates (PDIM) (13), are known to influence how Mtb suppresses host defenses through modulating various innate immune strategies against Mtb in host immune cells. Nonetheless, new mycobacterial components that alter the host’s innate immune response must be discovered to better understand the molecular mechanisms underlying mycobacterial pathogenesis and develop new therapeutic targets. Mtb requires a unique acyl carrier protein (AcpM), the second most glycosylated protein involved in mycolic acid biosynthesis (14). Mycolic acids, which protect Mtb from the host environment while also eluting virulence, are one of the most important components of the mycobacterial cell wall (15). AcpM interacts with PptT, which transfers 4′-phosphopantetheine (Ppt) from coenzyme A (CoA) to AcpM in Mtb for mycolic acid synthesis (16). According to a recent study, a small compound called “8918” inhibited PptT action by binding to the Ppt pocket in the active site, resulting in selective antimicrobial activity comparable to rifampin (17). These findings raise concerns about the intrinsic properties of the AcpM and how they affect Mtb virulence. Although AcpM is essential for Mtb growth by producing lipid-rich cell walls, little is known about its immunological properties in host-pathogen interactions. This study investigated the mechanisms by which the AcpM protein prevents nuclear translocation of transcription factor EB (TFEB) and phagosomal maturation in host macrophages. AcpM appeared to inhibit autophagy in bone marrow-derived macrophages (BMDMs) by lowering the LC3 I to II ratio; however, it did not affect autophagic flux in BMDMs. Rather than this, AcpM markedly reduced nuclear translocation of TFEB and several autophagy-related genes including lysosomal-associated membrane protein 1 (Lamp1), which was regulated by TFEB, in macrophages. Moreover, AcpM activated the protein kinase B (Akt) pathway, which is associated with Mtb survival in host cells, by inducing miR-155, which targets SH2-domain-containing inositol 5-phosphatase 1 (SHIP1) (18). AcpM prevented Mtb from fusing with lysosomes in BMDMs, thus increasing Mtb intracellular survival (ICS). Finally, in the lung lysates of recombinant M. smegmatis-infected mice, AcpM overexpression increased Mtb colony-forming unit (CFU) levels while decreasing several autophagy and lysosomal genes. Taken together, these findings help us to explore the relationship between the host immune response and mycobacterial infection in terms of Mtb AcpM, revealing its potential as a target for novel tuberculosis therapies.
Female C57BL/6 and BALB/c mice were purchased from Samtako Bio (Gyeonggi-do, Korea) at 6–7 weeks of age, and C3HeB/FeJ mice were obtained from the Jackson Laboratory (Bar Harbor, ME, USA). Mice were maintained under specific pathogen-free conditions. All animal experimental methods and procedures were performed following the relevant ethical guidelines and regulations approved by the Institutional Research and Ethics Committee at Chungnam National University, School of Medicine (202009A-CNU-155; Daejeon, Korea) and the guidelines of the Korean Food and Drug Administration.
Bone marrow cells were isolated from C57BL/6 mice (6-8 weeks old) and cultured in Dulbecco’s modified Eagle’s medium (DMEM; Lonza, Walkersville, USA) containing 10% fetal bovine serum (FBS; Gibco, NY, USA) and antibiotics (Lonza). Differentiating for 4–5 days in the presence of 25 μg/ml of recombinant mouse macrophage colony-stimulating factor (M-CSF) (R&D Systems) in a 37°C humidified atmosphere containing 5% CO2 produced primary BMDMs. Approximately 4 x 105 cells/well in the 24-well cell culture plate (SPL Life Science Co., Gyeonggi-do, Korea) or 2 x 105 cells/well in the 48-well cell culture plate (Corning, NY, USA) were used for the entire in-vitro analysis.
Recombinant AcpM protein was prepared according to the previous study (19). Briefly, mycobacterial acpM was amplified from genomic DNA of Mtb H37Rv ATCC 27294 using the forward (5’-CATATGCCTGTCACTCAGGAAGAAATC-3’) and reverse primers (5’-AAGCTTCTTGGACTCGGCCTCAAGCCT-3’), and the PCR product was inserted into the pET-22b (+) vector (Novagen, Madison, WI, USA). The recombinant plasmids were transformed into E. coli BL21 cells by heat-shocking for 1 min at 42 °C. Cell disruption was used to obtain the overexpressed AcpM protein, which was then purified using NI-NTA resin. The purified recombinant protein was dialyzed and incubated with polymyxin B-agarose (Sigma Chemical Co.) to remove residual endotoxin. The purified endotoxin-free AcpM was filter sterilized and kept frozen at -80°C until use. To collect anti-AcpM antibodies, BALB/c mice were injected three times intraperitoneally with purified AcpM (25 μg per mouse) emulsified in incomplete Freund’s adjuvant. One week after the final immunization, serum was collected and stored frozen until use with proper dilution.
Mycobacterial acpM was amplified from genomic DNA of Mtb H37Rv ATCC 27294 using the forward (NdeI site, 5’-CATATGCCTGTCACTCAGGAAGAAATC-3’) and reverse primers (HindIII site, 5’-AAGCTTCTTGGACTCGGCCTCAAGCCT-3’) as in the previous study (19). Then, amplified acpM was inserted into the pVV16 vector to create pVV16_AcpM. The pVV16 (vector only) and pVV16_AcpM plasmids were electroporated into suspensions of M. smegmatis mc2155 competent cells at 2.5 kV, 1,000 Ω, and 25 μF using a Gene Pulser (Bio-Rad, San Diego, CA, USA) to construct Ms_Vec and Ms_AcpM, respectively. Western blot image of AcpM expression in Ms_Vec and Ms_AcpM using anti-AcpM antibody was presented in Supplementary Figure S1 .
BMDMs cultured in 24-well cell culture plates were lysed in 150 μl of radioimmunoprecipitation assay (RIPA) buffer (LPS solution, CBR002) added with protease and phosphatase inhibitor cocktail (Roche, Mannheim, Germany). The whole mouse lung was homogenized in 1 ml of PBS containing 0.05% Tween 80 (PBST) and then half of the homogenates were centrifuged and lysed in 500 μl of RIPA buffer containing protease and phosphatase inhibitor cocktail. The cell lysates were mixed with Protein 5X Sample Buffer (ELPIS BIOTECH, EBA-1052) and boiled for 10 min. Prepared protein extracts were separated by SDS-polyacrylamide gel electrophoresis (PAGE) and then transferred to polyvinylidene difluoride (PVDF; Millipore, Burlington, MA, USA) membranes. The membranes were then blocked using 1X blocking solution (Biofact) for 1 h at room temperature (RT) and then incubated overnight with primary antibodies at 4 °C. After washing with tris-buffered saline supplemented with 0.1% Tween 20 (TBST), the membranes were incubated with the secondary antibodies for 1 h at RT. Immunoblotting was performed using an enhanced chemiluminescence reagent (Millipore, WBKL S0500) and a UVitec Alliance mini-chemiluminescence device (UVitec, Rugby, UK). The densitometric values were calculated using ImageJ software and data were normalized to loading controls shown in the figures. Bafilomycin A1 (B1793) was purchased from Sigma-Aldrich (St. Louis, MO, USA) The primary and secondary antibodies used were as follows: Anti-p62 (1:1000 diluted; P0067) and anti-LC3 (1:1000 diluted; L8918) antibodies were purchased from Sigma-Aldrich. anti-LAMP1 (1:1000 diluted; sc-20011) was purchased from Santa Cruz Biotechnology (Dallas, TX, USA), Anti-β-actin (1:2000 diluted; 5125s), anti-phospho-mTOR (1:1000 diluted; 2971s), anti-mTOR (1:1000 diluted; 2983s), anti-phospho-Akt (1:1000 diluted; 4060s), anti-Akt (1:1000 diluted; 9272s), anti-TFEB (1:1000 diluted; 4240s), anti-ATG5 (1:1000 diluted; 12994s), anit-SHIP1 (1:1000 diluted; 2728s), anti-FOXO3a (1:1000 diluted; 12829s), anti-mouse IgG (1:5000 diluted; 7076s), and anti-rabbit IgG (1:5000 diluted; 7074s) antibodies were purchased from Cell Signaling Technology (Danvers, MA, USA).
Mtb H37Rv was kindly provided by Dr. R. L. Friedman (University of Arizona, Tucson, AZ, USA). Mtb was grown at 37 °C with shaking in Middlebrook 7H9 broth (Difco, Paris, France) supplemented with 0.5% glycerol, 0.05% Tween-80 (Sigma-Aldrich), and oleic albumin dextrose catalase (OADC; BD Biosciences). Mtb-expressing enhanced red fluorescent protein (Mtb-ERFP) and recombinant M. smegmatis strains were grown in Middlebrook 7H9 medium supplemented with OADC and 50 μg/ml kanamycin (Sigma-Aldrich). Bacterial strains were then harvested by centrifugation at 3000 rates per min for 30 min and the pellets were resuspended in ice-cold phosphate-buffered saline (PBS). All mycobacterial suspensions were aliquoted and stored at −80 °C until just before use. For all experiments, mid-log-phase bacteria (O.D = 0.6) were used. The number of CFUs of the inoculum was verified by serially diluting and plating on Middlebrook 7H10 agar (Difco).
BMDMs were cultured on coverslips in 24-well cell culture plates. After the appropriate infection or treatment, cells were washed twice with PBS, fixed with 4% paraformaldehyde for 15 min, and permeabilized with 0.25% Triton X-100 (Sigma-Aldrich) for 10 min. Cells were incubated with anti-TFEB antibody (1:400 diluted; Bethyl Laboratories, A303-673A) or anti-LAMP1 Ab (1:400 diluted; Santa Cruz Biotechnology, SC-19992) overnight at 4°C. Cells were washed with PBS to remove excess primary antibodies and then incubated with secondary anti-rabbit or anti-rat IgG-Alexa Fluor 488 Ab (1:400 diluted; Invitrogen, A11008 or A11006) for 1 h at RT. Nuclei were stained using Fluoromount-G™, with DAPI mounting medium (Thermo Fisher Scientific, 00-4959-52). Immunofluorescence images were acquired using a confocal laser-scanning microscope (Zeiss, LSM-900). Quantification of TFEB-nuclear translocation was performed by manual calculation and the degree of colocalization between Mtb-ERFP and LAMP-1 was analyzed using the JACoP plugin of the ImageJ software.
Total RNA from BMDMs was isolated using QIAzol lysis reagent (Qiagen, Hilden, Germany) and miRNeasy Mini Kits (Qiagen) according to the manufacturer’s instructions. RNA quality was assessed by Agilent 2100 bioanalyzer using the RNA 6000 Pico Chip (Agilent Technologies, CA, USA), and quantification was performed using a NanoDrop 2000 Spectrophotometer system (Thermo Fisher Scientific, MA, USA). For messenger RNA-sequencing (mRNA-seq), the library was constructed using QuantSeq 3’ mRNA-Seq Library Prep Kit (Lexogen, Wien, Austria) according to the manufacturer’s instructions. In brief, each sample was prepared with 500 ng of total RNA, an oligo-dT primer with an Illumina-compatible sequence at its 5’ end was hybridized with the RNA, and reverse transcription was performed. After degradation of the RNA template, second-strand synthesis was initiated by a random primer with an Illumina-compatible linker sequence at its 5’ end. The double-stranded library was purified using magnetic beads to remove all reaction components and amplified to add the complete adapter sequences required for cluster generation. The finished library was purified from PCR components, and then high-throughput sequencing was performed as single-end 75 sequencings using NextSeq 500 (Illumina, CA, USA). For micro RNA-sequencing (miRNA-seq), the construction of the library was performed using the NEBNext Multiplex Small RNA Library Prep kit (New England BioLabs, MA, USA) according to the manufacturer’s instructions. Briefly, for library construction, total RNA from each sample was used 1 µg to ligate the adaptors, and then cDNA was synthesized using reverse-transcriptase with adaptor-specific primers. PCR was performed for library amplification, and libraries were cleaned up using QIAquick PCR Purification Kit (Qiagen) and AMPure XP beads (Beckman Coulter, CA, USA). The Agilent 2100 Bioanalyzer instrument assessed the yield and size distribution of the small RNA libraries for the High-sensitivity DNA Assay (Agilent Technologies). The NextSeq500 system produced High-throughput sequences to single-end 75 sequencings (Illumina). All raw reads received the quality check using BBduk, a tool in the BBMap package (https://sourceforge.net/projects/bbmap), to remove low-quality bases (< Q20). The remaining reads from QuantSeq 3’ mRNA-Seq and miRNA-seq were mapped to the mouse mm10 genome reference and mature miRNA sequences of the miRBase database (20) using Bowtie2 software (21), respectively. Read counts of genes were calculated with Bedtools (22) and the raw counts were transformed into counts per million (CPM) for exclusion of very lowly expressed genes using edgeR (version 3.36.0) (23). Genes with one or more log2-CPM in at least two samples were kept for further analysis. Next, normalization factors were calculated with the trimmed mean of M-values (TMM) method using the calcNormFactors function in edgeR. For Z-score normalization, the TMM-adjusted log CPM counts were calculated, and Gaussian normalization was performed. To identify differentially expressed genes (DEGs), gene expression levels were statistically tested between groups using the glmFit and glmLRT functions embedded in the edgeR package. Benjamini and Hochberg’s false discovery rate (FDR) method was used to correct for multiple testing. Genes with the fold change over two and the significance (adjusted p-value) below 0.01 were considered DEGs. The binding site between miRNA and the 3’ untranslated region (UTR) of target mRNA was predicted by miRWalk 3.0 at http://mirwalk.umm.uni-heidelberg.de/ (last accessed February 2022).
For mRNA expression analysis, total RNA from BMDMs cultured in 48-well cell culture plates or mouse lung tissue homogenates was extracted using TRIzol reagent (Invitrogen; 15596026) according to the manufacturer’s instructions, followed by RNA quantitation and assessment using QIAxpert (Qiagen). Complement DNA from total RNA was synthesized using the reverse transcription master premix (ELPIS Biotech; EBT-1515c) as manufacturer’s instruction. Two-step quantitative real-time PCR (qRT-PCR) was carried out using cDNA, primers, and Rotor-Gene SYBR Green PCR Kit (Qiagen, 204074). Reactions were run on a Rotor-Gene Q 2plex system (Qiagen, 9001620). The samples were amplified for 40 cycles as follows: 95°C for 5 s and 60°C for 10 s. Data were expressed as relative fold changes using the 2-ΔΔ threshold cycle (Ct) method with β-actin (BMDMs) or Gapdh (lung tissue homogenates) as an internal control gene. The primer sequences used are shown in Supplementary Table 1 . For miRNA expression analysis, total RNA from BMDMs cultured in 48-well cell culture plates was isolated using QIAzol lysis reagent (Qiagen, 79306) and miRNeasy Mini Kits (Qiagen, 217004) according to the manufacturer’s instructions. Next, cDNA from total RNA was synthesized using miScript II RT Kits (Qiagen, 218161) by the manufacturer’s instructions. Three-step qRT-PCR was performed using the miScript SYBR Green PCR Kit (Qiagen, 218073), and samples were amplified for 50 cycles as follows: 95°C for 15 s, 55°C for 30 s, and 72°C for 30 s. Small nuclear RNA (RNU6-6P RNA; Qiagen, MS00033740) was used for the normalization of the expression of miR-155-3p and miR-155-5p. The primer sequences used are shown in Supplementary Table 2 .
BMDMs cultured in 48-well cell culture plates were transiently transfected with a miRNA mimic negative control (20 nM), miR-155-5p mimic (20 nM), miRNA inhibitor negative control (100 nM), or miR-155-5p inhibitor (100 nM) using the Lipofectamine 3000 Transfection Kit (Invitrogen, L3000-008) according to the manufacturer’s instructions. Genolution (Seoul, South Korea) provided the miR-155-5p mimic (5′-UUAAUGCUAAUUGUGAUAGGGGU-3′) and miR-155-5p inhibitor (5′-ACCCCUAUCACAAUUAGCAUUAA-3′), and Ambion (Austin, TX, USA) provided the miRNA mimic negative control (4464058) and inhibitor negative control (4464076).
BMDMs cultured in 48-well cell culture plates were transiently transfected with miRNA inhibitor negative control or miR-155-5p inhibitor before infecting with Mtb H37Rv at a multiplicity of infection (MOI) of 3 for 4 h. The infected cells were washed with PBS to remove extracellular bacteria and further incubated in the fresh medium for the indicated periods. Cells were then lysed in sterile distilled water for 30 min, serially diluted with PBS, and plated on the Middlebrook 7H10 agar plates containing OADC. Plates were incubated for 2-3 weeks at 37°C and colonies were enumerated to assess intracellular bacterial viability.
Frozen bacterial cells were centrifuged after thawing, and the pellet was resuspended in PBST. After anesthetizing C3HeB/FeJ mice, 1×106 CFU/mouse of Ms_Vec or Ms_AcpM were inoculated intranasally. At the indicated times after infection, mice were euthanized and the lungs were collected to assess the bacterial burden. Lung tissues were homogenized using a tissue homogenizer (Omni International Inc., Warrenton, VA, USA) in PBST. Serial dilutions of the homogenates were planted in 7H10 agar plates, and colonies were counted after 3-4 days of incubation at 37°C.
All of the experiments were repeated as indicated in figure legends, with consistent results. An unpaired Student’s t-test was used to determine the significance of differences between two groups, and an one-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test was used to determine the significance of differences among three or more groups using Prism® software version 8 (GraphPad Software, San Diego, CA, USA). Data are expressed as means ± standard deviation (SD) or standard error of the mean (SEM); statistical significance was defined as *p < 0.05, **p < 0.01, and ***p < 0.001.
To find the key molecule governing the host defense in AcpM-treated BMDMs, mRNA-seq analysis was performed ( Figure 1A ; Supplementary Table 3 ). Several autophagy-related genes, including Tfeb, were significantly downregulated in AcpM-treated BMDMs (AcpM) when compared to untreated cells (Un) ( Figure 1A ). Since TFEB is known to play a pivotal role in the regulation of lysosomal biogenesis and autophagy (24), qRT-PCR and western blot analysis were conducted to confirm its relative expression. Over time, AcpM treatment reduced the gene ( Figure 1B ) and protein ( Figure 1C ) levels of TFEB. Furthermore, AcpM treatment effectively suppressed the nuclear translocation of TFEB. The degree of TFEB in the nucleus reduced at early time points after AcpM addition in BMDMs, as shown by confocal images with TFEB staining in green ( Figure 1D ).
TFEB enters the nucleus to function as a transcription factor inducing lysosomal biogenesis. Since AcpM blocks its nuclear translocation ( Figure 1D ), various genes related to autophagy or lysosomal activity were thought to decrease with AcpM treatment in BMDMs. In detail, AcpM treatment significantly reduced the levels of Lamp1, Lamp2, autophagy-related gene 5 (Atg5), Atg 7, and several Tfeb downstream genes such as Uvrag and Vps11 over time ( Figure 2A ). AcpM also significantly suppressed the expression of Rap7a, Gabarap, Beclin-1 (Becn1), and damage-regulated autophagy modulator 2 (Dram2) at most time points ( Figure 2A ). Moreover, both LAMP1 and ATG5 protein levels in BMDMs were significantly reduced at 48 h after AcpM treatment ( Figure 2B ). Collectively, AcpM addition blocks nuclear translocation of TFEB, thereby downregulating the expression of various autophagy and lysosomal genes in BMDMs.
To determine whether AcpM affected autophagy in murine BMDMs, p62 and LC3 levels were validated by western blotting. AcpM treatment increased p62 while decreasing the LC3-II band over time ( Figure 3A ). To confirm the effect of AcpM in autophagic flux, the vacuolar type H+-ATPase (V-ATPase) inhibitor bafilomycin A1 (Baf-A1) was used. Baf-A1 was added 1 h before AcpM treatment to inhibit the lysosomal activity. After 8 h and 24 h, LC3-II bands in the AcpM-treated cells showed a significant difference in Baf-A1-untreated and -treated conditions, indicating that AcpM had no effect on the basal autophagic flux ( Figure 3B ). Furthermore, at 24 h after AcpM treatment, p62 levels were higher in Baf-A1-treated cells than in Baf-A1-untreated cells, implying that p62 accumulation in AcpM-treated conditions is not due to a block in autophagic flux. These findings indicate that, while AcpM inhibits LC3-II/LC3-I ratio over time, it has no effect on autophagic flux in BMDMs.
The next question was whether adding AcpM protein to Mtb-infected macrophages would affect phagosomal maturation. BMDMs were infected with an Mtb-ERFP strain, which was followed by AcpM treatment in fresh media. The cells were then stained with LAMP1 antibody to visualize lysosomes in confocal microscopy analysis. The colocalizing rate between Mtb and LAMP1 was significantly lower in the AcpM-treated conditions than in the untreated group ( Figure 4 ). Therefore, AcpM helps Mtb circumvent phagosomal maturation by blocking phagosome and lysosome fusion.
Previous studies have highlighted the importance of miRNAs in the regulation of host immune response (25–27). To see if AcpM was involved in the increase of specific miRNAs, miRNA-seq analysis was performed. The expression rates of miRNA-155p-3p and miRNA-155p-5p were the highest among the miRNAs that showed a significant change in the miRNA-seq analysis of AcpM-treated BMDMs when compared to untreated cells ( Figure 5A , Supplementary Table 4 ). However, the qRT-PCR analysis revealed that miR-155-5p increased more than tenfold with increasing AcpM concentration in BMDMs, while miR-155-3p showed no significant change ( Figure 5B ). Previous studies showed that SHIP1 prevented Akt phosphorylation, thus blocking the Akt-mTOR pathway (18, 28). Also, as miR-155 was shown to target SHIP1 from an earlier study ( Figure 5C ) (29), the gene expression and protein amount of SHIP1 was investigated under AcpM treatment in BMDMs. At 3 and 6 h-post AcpM treatment, Ship1 expressions analyzed with two different primers were significantly suppressed ( Figure 5D ). In western blot analysis, total SHIP1 expression was also significantly reduced from 3 to 18 h after AcpM administration, which was accompanied by an increase in phosphorylation of Akt and mTOR ( Figure 5E ). Along with increased Akt phosphorylation, there was also a reduction in FOXO3 levels ( Figure 5E ). To further demonstrate the ability of AcpM-induced miR-155-5p to regulate SHIP1 expression, miR-155-5p mimic and inhibitor (m155 and i155, respectively), as well as negative controls of miRNA mimic and inhibitor (mNC and iNC, respectively), were transfected into BMDMs. It was discovered that either m155 transfection or AcpM addition suppressed SHIP1 effectively and that i155 transfection could counteract AcpM-induced miR-155-5p expression and restore SHIP1 levels ( Figure 5F ). Overall, these findings suggest that AcpM-induced miR-155-5p plays a role in Akt-mTOR activation by targeting SHIP1.
Because AcpM inhibited Mtb fusion with lysosomes ( Figure 4 ), Mtb ICS was thought to be increased. As expected, the Mtb CFU level was significantly higher in BMDMs 3 days after AcpM treatment than in the untreated group (Un) ( Figure 6A ). Furthermore, when i155-transfected groups were compared to iNC-transfected groups, CFU level in the AcpM-treated groups was significantly reduced ( Figure 6B ). Relative miR-155-5p expression in the same experimental settings as in Figure 6B revealed a positive correlation between the miR-155-5p and the Mtb CFU levels in BMDMs ( Figure 6C ). According to the findings, AcpM is thought to promote Mtb survival in BMDMs by upregulating miR-155-5p expression.
To evaluate the effect of AcpM secretion in-vivo, recombinant M. smegmatis strains overexpressing AcpM (Ms_AcpM) and a vector plasmid carrying control (Ms_Vec) were used. C3HeB/FeJ mice were challenged with either Ms_Vec or Ms_AcpM via nasal route and sacrificed at 1, 4, and 7 days post-infection (dpi). One day after infection, there was no significant difference in CFU levels between lung lysates from two recombinant strains-infected mice, indicating that an equal amount of strains was properly administered through the nasal airways ( Figure 7A ). However, the viability of Ms_AcpM was significantly higher than that of Ms_Vec at 4 and 7 dpi ( Figure 7A ), suggesting that AcpM overexpression improves M. smegmatis in-vivo survival. Interestingly, qRT-PCR analysis of the samples obtained from the same mice revealed a decrease in several autophagy and lysosomal genes including Tfeb ( Figure 7B ). These data suggest that AcpM overexpression helps M. smegmatis survival in mouse lungs, possibly by altering TFEB downstream pathways as shown in murine macrophages.
In this study, AcpM, an essential protein for Mtb survival and mycolic acid synthesis (30), was newly discovered as a mycobacterial effector for pathogenesis through blocking TFEB activation and increasing miR-155-5p expression. A schematic summary of the AcpM’s suggested mode of action was presented in Figure 8 . Previously, the apoptosis inhibiting feature of AcpM was also described (19). In murine BMDM settings, AcpM did not directly affect autophagic flux, but significantly suppressed multiple autophagy gene expression, which may influence host defense pathways in an autophagy-independent manner. Importantly, we found that the mRNA and protein expression of LAMP1, which is regulated by TFEB (31), was down-regulated by AcpM, suggesting that AcpM affects lysosomal biogenesis during Mtb infection. In addition, our data highlights the AcpM function in the elevation of miR-155-5p, which was shown to target SHIP1 (29, 32, 33). Previous studies showed that SHIP1 plays an essential role in the activation of Akt pathway, thereby enhancing intracellular Mtb survival (18). In addition, miR-155 can target FOXO3 (34), which is associated with the gene expression of multiple autophagy-related genes such as Atg5, Atg12, Becn1, Lc3 and Bnip3 (35, 36). However, the role of Mtb-induced miR-155 expression in regulating host defense in the early stages of infection has sparked debate. Wang et al. reported that miR-155 induced autophagy to eliminate intracellular mycobacteria by targeting Ras homolog enriched in brain (Rheb) in RAW264.7 cells (37). Indeed, the miR-155 level is elevated in both Mtb-infected macrophages (37) and active TB patients (38). On the other hand, Rothchild et al. demonstrated that miR-155 promoted Mtb survival in BMDMs through targeting SHIP1 in the early stages of infection, even though it also activated Mtb-specific T cell function in the adaptive immune response to effectively reduce bacterial survival in the late stages of infection (28). Kumar et al. also discovered that overexpression of miR-155 reduced the expression of BTB and CNC homology 1 (BACH1) and SHIP1, allowing Mtb to survive in macrophages (18). These results show a partial correlation with ours that miR-155 favors mycobacterial survival in macrophages by targeting SHIP1-Akt axis. Although the role of miR-155 in host defense regulation varies depending on the host cell type or bacterial strain, it appears that miR-155 inhibits antimicrobial host defense in macrophages in the early stages of infection. TFEB is known as a master regulator of lysosomal biogenesis (24). Previous research reported that the suppression of the Akt-mTOR pathway enhances nuclear translocation of TFEB to induce transcriptional activation of lysosomal and autophagy-related genes (39, 40). According to our findings, AcpM increased Akt and mTOR phosphorylation ( Figure 5E ) while decreasing TFEB expression and its nuclear translocation ( Figure 1 ), which likely leads to the downregulation of autophagy and lysosomal genes ( Figure 2 ). Recent studies showed that TFEB activation is critically involved in the regulatory node of antimicrobial responses against Mtb in macrophages (41–43). Importantly, we found that AcpM did not affect the induction of autophagy or activation of autophagic flux when treated with Baf-A1 in basal conditions at both 8 h and 24 h after AcpM treatment ( Figure 3 ). Thus, the AcpM’s role in the suppression of antimicrobial responses against Mtb infection seems to be associated with the inhibition of TFEB, but not directly related to the suppression of autophagy. In addition, a recent study revealed that TFEB activation is required for the induction of mitochondrial itaconate synthesis to control intracellular bacterial growth (44, 45), suggesting the critical function of TFEB in terms of antimicrobial defense in macrophages. Future studies will clarify whether AcpM is involved in the regulation of immunometabolic remodeling in macrophages to further affect TFEB-induced antimicrobial responses during Mtb infection. We also found that AcpM increased miR-155 production, which targets SHIP1 to prevent its negative regulation on Akt phosphorylation, resulting in the increased Mtb survival in host cells. Because AcpM-induced miR-155-5p upregulates the Akt/mTOR pathway by targeting SHIP1, it is supposed that miR-155-5p-mediated Akt/mTOR activation leads to the suppression of TFEB activation. Since the level of miR-155 is related to the virulence of infected mycobacterial strains (18, 37), the present data is important to show the function of AcpM as an inducer of miR-155 to further regulate the host protective responses during infection. In this regard, identifying other mycobacterial factors that stimulate miR-155 expression and elucidating the exact mechanism of how mycobacteria activate miR-155 production would help us better understand mycobacterial pathogenesis. To further understand the function of AcpM during mycobacterial infection, an attempt was made to construct an AcpM-conditional knockout system using the Mtb H37Rv strain. However, we were unable to achieve it, most likely due to the AcpM’s essential role in Mtb survival. Thus, M. smegmatis strains, Ms_AcpM and Ms_Vec, were used to test if AcpM overexpression could increase the number of surviving bacteria in lung tissues of infected mice. Because M. smegmatis strains are non-pathogenic, they have little tolerance for the host’s innate immune system. To slow down the declining survival rate of recombinant M. smegmatis strains, an in-vivo challenge was conducted using C3HeB/FeJ mice (46). As a result, CFU levels of Ms_AcpM were significantly higher than that of Ms_Vec, implying that AcpM overexpression improves the survival of M. smegmatis in-vivo ( Figure 7A ). Thus, AcpM expressed in mycobacteria is likely to suppress the tfeb and tfeb-downstream autophagy-related gene expression in the lung tissues in the same way that recombinant AcpM protein does in macrophages. Recently, a small molecule called “8918,” which selectively binds to PptT, was discovered to have anti-tuberculosis efficacy comparable to rifampin, a first-line anti-tuberculosis drug (17). In addition, a newly discovered Ppt hydrolase, PptH, which removes Ppt from AcpM, made Mtb more sensitive to 8918, even when PptT was only partially inhibited (17). Therefore, it’s possible to believe that Mtb virulence is influenced by the formation and maintenance of holo-AcpM. Finding small chemical compounds that can selectively target AcpM could be helpful in the development of new anti-mycobacterial drugs. In summary, AcpM’s role in modulating antimicrobial host defense was revealed in this work. AcpM was discovered to effectively reduce TFEB nuclear translocation and downregulate the expression of autophagy and lysosomal genes in macrophages. In addition, AcpM-mediated miR-155-5p activated the Akt/mTOR pathway by targeting SHIP1. AcpM also improved intracellular mycobacterial survival by reducing phagosome-lysosome fusion. These findings highlight the importance of understanding host-pathogen interactions in the context of the Mtb virulence factors and provoke future studies targeting AcpM to expand the development of novel Mtb therapeutics.
All mRNA-seq and miRNA-seq data generated in this study are available through the NCBI Gene Expression Omnibus through accession numbers SRR18614842-SRR18614845 and SRR18615277-SRR18615280 under BioProject PRJNA823491.
The animal study was reviewed and approved by Institutional Research and Ethics Committee at Chungnam National University, School of Medicine (202009A-CNU-155; Daejeon, Korea).
SP was in charge of the majority of the data processing and analysis. SP, KK, IK, YK, and H-JK carried out the experiments and data analysis. SP and SC constructed and purified the recombinant AcpM protein and the M. smegmatis strains used in this study. SP, KK, IK, and YK wrote the manuscript, which was then peer-reviewed by H-JK and E-KJ. SP and E-KJ guided and supervised the work. All authors contributed to the article and approved the submitted version.
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2021R1C1C2006968 and 2017R1A5A2015385).
We are grateful to Prof. Sung Jae Shin (Yonsei University, Korea) and Prof. Jin Kyung Kim (Keimyung University, Korea) for providing and harvesting Mtb-ERFP, respectively.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | true | true | true |
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PMC9559480 | Xing Wu,Na Zhang,Jing Li,Zihao Zhang,Yulong Guo,Donghua Li,Yanhua Zhang,Yujie Gong,Ruirui Jiang,Hong Li,Guoxi Li,Xiaojun Liu,Xiangtao Kang,Yadong Tian | gga-miR-449b-5p Regulates Steroid Hormone Synthesis in Laying Hen Ovarian Granulosa Cells by Targeting the IGF2BP3 Gene | 09-10-2022 | laying hens,gga-miR-449b-5p,granulosa cell,proliferation,steroid synthesis,IGF2BP3 | Simple Summary The aim of this study was to explore the regulatory effect of gga-miR-449b-5p on GC proliferation and steroidogenesis in laying hens. Our results showed that gga-miR-449b-5p had no effect on the proliferation of GCs, but regulated the expression of key genes involved in steroid synthesis and the secretion of P4 and E2. In addition, gga-miR-449b-5p could target IGF2BP3 and inhibit its mRNA and protein expression. Therefore, we concluded that gga-miR-449b-5p played an important role in the synthesis of steroid hormones in laying hens. Abstract MiRNAs have been found to be involved in the regulation of ovarian function as important post-transcriptional regulators, including regulators of follicular development, steroidogenesis, cell atresia, and even the development of ovarian cancer. In this study, we evaluated the regulatory role of gga-miR-449b-5p in follicular growth and steroid synthesis in ovarian granulosa cells (GCs) of laying hens through qRT-PCR, ELISAs, western blotting and dual-luciferase reporter assays, which have been described in our previous study. We demonstrated that gga-miR-449b-5p was widely expressed in granulosa and theca layers of the different-sized follicles, especially in the granulosa layer. The gga-miR-449b-5p had no significant effect on the proliferation of GCs, but could significantly regulate the expression of key steroidogenesis-related genes (StAR and CYP19A1) (p < 0.01) and the secretion of P4 and E2 (p < 0.01 and p < 0.05). Further research showed that gga-miR-449b-5p could target IGF2BP3 and downregulate the mRNA and protein expression of IGF2BP3 (p < 0.05). Therefore, this study suggests that gga-miR-449b-5p is a potent regulator of the synthesis of steroid hormones in GCs by targeting the expression of IGF2BP3 and may contribute to a better understanding of the role of functional miRNAs in laying hen ovarian development. | gga-miR-449b-5p Regulates Steroid Hormone Synthesis in Laying Hen Ovarian Granulosa Cells by Targeting the IGF2BP3 Gene
The aim of this study was to explore the regulatory effect of gga-miR-449b-5p on GC proliferation and steroidogenesis in laying hens. Our results showed that gga-miR-449b-5p had no effect on the proliferation of GCs, but regulated the expression of key genes involved in steroid synthesis and the secretion of P4 and E2. In addition, gga-miR-449b-5p could target IGF2BP3 and inhibit its mRNA and protein expression. Therefore, we concluded that gga-miR-449b-5p played an important role in the synthesis of steroid hormones in laying hens.
MiRNAs have been found to be involved in the regulation of ovarian function as important post-transcriptional regulators, including regulators of follicular development, steroidogenesis, cell atresia, and even the development of ovarian cancer. In this study, we evaluated the regulatory role of gga-miR-449b-5p in follicular growth and steroid synthesis in ovarian granulosa cells (GCs) of laying hens through qRT-PCR, ELISAs, western blotting and dual-luciferase reporter assays, which have been described in our previous study. We demonstrated that gga-miR-449b-5p was widely expressed in granulosa and theca layers of the different-sized follicles, especially in the granulosa layer. The gga-miR-449b-5p had no significant effect on the proliferation of GCs, but could significantly regulate the expression of key steroidogenesis-related genes (StAR and CYP19A1) (p < 0.01) and the secretion of P4 and E2 (p < 0.01 and p < 0.05). Further research showed that gga-miR-449b-5p could target IGF2BP3 and downregulate the mRNA and protein expression of IGF2BP3 (p < 0.05). Therefore, this study suggests that gga-miR-449b-5p is a potent regulator of the synthesis of steroid hormones in GCs by targeting the expression of IGF2BP3 and may contribute to a better understanding of the role of functional miRNAs in laying hen ovarian development.
The egg production performance of laying hens depends on the function of ovaries and the developmental ability of follicles, which are regulated by a complex and delicate network. Many studies have shown that the synthesis of steroid hormones in follicular theca cells (TCs) and granulosa cells (GCs) is essential for the regulation of follicular development and maturation, cell proliferation, differentiation and apoptosis [1,2,3,4]. The hypothalamic-pituitary-ovarian axis plays an important role in the reproduction of animals by regulating steroid hormone synthesis. However, numerous studies have proven that ovarian steroidogenesis is also regulated by various factors in the ovary, including key steroidogenesis-related genes, hormones and other regulatory factors. In general, hormones can exert their biological effects only when they specifically combine with their receptors to form hormone-receptor complexes. Progesterone (PR), androgen (AR) and estrogen (ER) receptors are located in the nucleus of GCs and TCs and bind specifically to hormones to form hormone receptor complexes, which are involved in follicular growth and development, maturation and ovulation, as well as the synthesis of steroids [5,6,7,8]. The genes such as steroidogenic acute regulatory protein (StAR), cytochrome P450 family 11 subfamily A member 1 (CYP11A1), 3β-hydroxysteroid dehydrogenase (3β-HSD), and cytochrome P450 family 19 subfamily A member 1 (CYP19A1) are directly involved in the synthesis of progesterone and estrogen [9,10,11,12]. In addition, several regulatory factors, such as IGF-1, EGF, TGF-β, and SF-1, and transcription factors (CATA-4/6, FOXL2, WT-1, DAX-1, AP-1, and SP-1) [13,14,15] regulate the expression of ovarian steroid synthesis genes as well as hormone secretion by activating multiple molecular signaling pathways. Thus, it is necessary to explore the further regulatory mechanism of steroid synthesis for follicular development and ovulation in chickens. In recent years, many studies have reported that noncoding RNAs, such as miRNAs, lncRNAs and circRNAs, play major roles in the regulation of the reproductive function of laying hens [16,17,18,19,20]. MiRNA is a kind of noncoding small 22 nt RNA that mostly regulates gene expression at the post-transcriptional level. By binding to the miRNA response element (MRE) in the 3′UTR, which is the target of mRNA, miRNAs act as negative modulators of gene expression, inhibit or silence target gene expression, and regulate mRNA and protein expression at the mRNA and protein levels [21,22]. MiRNAs are widely distributed in various tissues and cell types and participate in a variety of biological regulatory processes, playing an important regulatory role in the occurrence and development of diseases, tumors and cancers [23,24,25]. At present, GCs have been the main target cells for the study of ovarian function related to miRNA regulation, particularly in mammals. Many studies have shown that functional miRNAs play an important role in regulating ovarian function, follicular development and atresia, cell proliferation and apoptosis, steroid hormone synthesis and even ovarian cancer [26,27,28,29]. In mammals, miR-383, miR-323-3p, miR-320a, miR-130a-3p, miR-1246, miR-31 and miR-20b influence steroid hormone synthesis in granulosa cells [30,31,32,33,34,35], and miR-214-3p, miR-324-3p and miR-335-5p promote granulosa cell proliferation in the ovary [36,37,38]. Unfortunately, in poultry, the study of functional miRNAs in ovarian development and function of laying hens still lags behind. Only a few studies have proven that miR-26a-5p, miR-1b-3p and miR-23b-3p play an important role in the regulation of follicular development and steroid synthesis in chickens [39,40,41]. In our previous study, we predicted that gga-miR-449b-5p might be involved in the regulation of proliferation and steroid synthesis in ovaries of hens via transcriptome sequencing analysis of hen ovarian tissue during the four classic physiological periods (15 w, 20 w, 30 w, and 68 w), which represent initial ovarian development, sexual maturation, the peak laying period and the late laying period [42]. In another previous study, we predicted that IGF2BP3 may be its targeted regulatory gene [20]. At present, the reports on this gene are mainly focused on cell development, proliferation and migration [43,44], especially in cancer development and progression [45,46,47], but there are few reports on the reproduction of laying hens. Therefore, in the present study, we explored the regulatory effect of gga-miR-449b-5p on cell proliferation and steroid synthesis and hormone secretion in GCs and explored the relationship between gga-miR-449b-5p and IGF2BP3 in GCs to further explore the role of gga-miR-449b-5p in ovarian function in laying hens.
All studies involving Hy-Line brown laying hens were approved by the regulators for the administration of affairs concerning experimental animals (Revised Edition, 2017). The protocols have been reviewed and approved by the Henan Agricultural University Institutional Animal Care and Use Committee (Permit Number: 19−0068).
Forty healthy Hy-Line brown laying hens were collected at the age of 30 weeks and euthanized by cervical dislocation, and then the whole ovaries of six laying hens were removed. The follicles were divided into the following ten groups: small white follicles with a diameter < 4 mm (SWF), large white follicles with a diameter of 4−6 mm (LWF), small yellow follicles with a diameter of 6–8 mm (SYF), large yellow follicles with a diameter of 9–12 mm (LYF), and preovulatory follicles with a diameter > 12 mm (F6-F1) [48]. The obtained groups of follicles were placed in PBS buffer containing 3% double antibiotics to remove the residual connective tissue and attached blood filaments. The outer membrane layer was peeled off with curved forceps, the follicles were cut in half with scissors and the end was gently shaken with forceps until all the white granulosa layer came out; the remaining layer is the theca layer. After the granulosa layer or theca layer were mixed and divided equally into 6 biological replicates, they were immediately used for gene expression analysis. The small yellow follicles with a diameter of 6−8 mm were removed from the remaining 34 hens and divided into 4 groups: NC group, gga-miR-449b-5p mimic group, NCR group and gga-miR-449b-5p inhibitor group, followed by cell proliferation assay, ELISA assay and western blotting assay.
The granulosa layer of small yellow follicles with a diameter of 6–8 mm was collected from the remaining 34 hens according to the method described above, and washed three times in PBS buffer. All GCs were assembled in 1.5 mL centrifuge tubes, ground into a homogeneous paste by a cell grinding rod, mixed in 15 mL centrifuge tubes and digested in a 37 °C environment with 0.25% trypsin of the same volume for 10 min. After the digestion process was completed, single cells were obtained by 200 µm filtration. The cells were assembled by 1800 rpm centrifugation at room temperature for 5 min. After repeated centrifugation twice, the suspended cells in complete culture medium containing 2.5% fetal bovine serum and 1% double antibiotics were spread in a 12-well plate, which was incubated in a cell incubator at 37 °C and 5% CO2 for 12 h and then the cells were transfected, as previously reported [49].
Total RNA was extracted from GCs and TCs using TRIzol reagent (Novizan, Nanjing, China). The purity and concentration of the RNA was determined by measuring the ratio between the absorbance at 260 nm and 280 nm by a spectrophotometer (Thermo, Waltham, MA, USA). All samples were of acceptable purity (the range of the absorbance ratio from 1.9 to 2.1). cDNA was synthesized by reverse transcription with the HiScrip®®III First Strand cDNA Synthesis Kit (Novizan, Nanjing, China) containing gDNA wiper. MiRNA was reverse transcribed by a HiScrip®®III RT SuperMix for qPCR kit (Novizan, Nanjing, China). The samples were stored frozen at −20 °C and a ChamQ Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China) was used for real-time quantitative polymerase chain reaction (qRT-PCR). The β-actin gene was used as the reference gene for mRNA, and U6 was used as the reference gene for miRNA. The relative quantification of related genes and miRNAs was performed by the 2−∆∆Ct method [50]. The primer sequence information is listed in Table 1.
The mimics and inhibitors of gga-miR-449b-5p and their negative controls (NC and NCR) were synthesized by RiboBio (Guangzhou, China). The MMP2 3′UTR fragment with binding sites was cloned into the psiCHECK-2 dual luciferase reporter vector by PCR amplification. To construct a mutant MMP2 3′UTR vector, we designed mutant primers, and the sequences are shown in Table 1.
Lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA) was used to transfect miRNA mimics, and a ribo FECT CP transfection kit (Guangzhou, China) was used to transfect miRNA inhibitors. The transfection experiment was carried out according to the concentration recommended by the manufacturer when the density of follicular granulosa cells in a 12-well plate was ≥ 70%. The new complete medium was changed after transfection for 4 h.
The GCs were spread in 12-well plates for the EdU assay. GC proliferation was measured using a Cell Proliferation EdU Image Kit (Abbkine, Wuhan, China) after transfection for 24 h. Nuclear staining experiments were performed with 4′,6-diamidino-2-phenylindole (DAPI, Invitrogen, Carlsbad, California USA) after two hours of incubation in the incubator. Finally, images were captured with a fluorescence microscope (Olympus Ts2-FL, Olympus, Shinjuku-ku, Tokyo, Japan). GCs were evenly spread in a 96-well plate, placed in a 37 °C incubator containing 5% CO2 and cultured until they were transfected. The 96-well plates were removed at 12 h, 24 h, 36 h and 48 h. According to the manufacturer’s instructions, 100 µL of the original medium was removed, while 100 µL of complete medium containing 10% CCK-8 reagent (Dojindo, Kumamoto, Japan) was added to the incubator for an additional 2 h. Afterward, samples were collected for enzyme labeling (BioTek, Winooski, VT, USA), and absorbance was detected (OD value) at a wavelength of 450 nm.
GCs were collected 24 h after transfection and washed twice with PBS. DNA was incubated with PI (Solarbio, Beijing, China) staining solution at 4 °C for 30 min. GCs were analyzed by adjusting the excitation wavelength of the flow cytometer (BD Biosciences, San Jose, CA, USA) to Ex = 488 nm and the emission wavelength to Em = 530 nm.
GCs were transfected in 12-well plates for 24 h, and cell supernatants were collected. Concentrations of progesterone (P4), testosterone (T), and estradiol (E2) were determined by the Chicken P4, T, and E2 ELISA Kit (Jiangsu Meimian Industrial Co., Ltd., Jiangsu, China), respectively, according to the manufacturer’s instructions (The sensitivity of ELISA Kits of P4, T, E2 were typically less than 10 pmol/L, 1.0 pg/mL and 0.1 pg/mL; tolerance within batch and tolerance between batches of CV < 10% and no cross-reactivity for all three ELISA kits.).
The proteins from GCs were extracted at 36 h post-transfection with a RIPA lysis buffer (Beyotime, Shanghai, China). Primary antibodies for IGF2BP3 and GAPDH were purchased from Novusbio (Littleton, CO, USA) and Affinity (Cincinnati, OH, USA), respectively, and were incubated with samples overnight at 4 °C. The secondary antibody, HRP-conjugated goat anti-rabbit antibodies provided by Elabscience (Wuhan, China), were incubated at room temperature for 1 h. Finally, the optical density values of the target band were analyzed with the Odyssey FC NIR Protein Processing System (LI-COR, Lincoln, NE, USA).
The DF-1 cell line is the most investigated and widely used chicken cell line, and its culture is the same as that reported by Himly et al.; these cells were used for the dual-luciferase reporter assay [51]. When the DF-1 cell density was ≥ 70%, the gga-miR-449b-5p mimics or NC was cotransfected with IGF2BP3 WT or IGF2BP3 MUT and MMP2 WT or MMP2 MUT for 36 h using Lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA). Firefly and sea kidney luciferase activities were detected by the Dual Luciferase Reporter Gene Assay System Kit (Promega, Madison, WI, USA) according to the manufacturer’s instructions.
All data were statistically analyzed by SPSS package version 22.0 and are presented as the means ± SEMs. A p value < 0.05 indicated a statistically significant difference. GraphPad Prism 7.0 software (GraphPad Software, Inc., San Diego, CA, USA) was used for visualization of all data for statistical purposes.
We investigated the distribution of gga-miR-449b-5p in the TCs and GCs of follicles of different sizes by qRT−PCR. The results showed that the expression level of gga-miR-449b-5p was significantly higher in follicular GCs than in TCs, especially follicles with a diameter of 4–6 mm, 6–8 mm, 9–12 mm and preovulatory follicles with a diameter > 12 mm (F6-F3) (p < 0.01 and p < 0.05). In addition, the highest expression was found in prehierarchical GCs (Figure 1).
We investigated the role of gga-miR-449b-5p in the proliferation of GCs using qRT-PCR, CCK-8 assays, EdU assays and flow cytometry. The results showed that the transfection efficiency of gga-miR-449b-5p was increased approximately 600-fold in GCs by the gga-miR-449b-5p mimic (p < 0.01) and significantly diminished by the gga-miR-449b-5p inhibitor (p < 0.01; Figure 2a). Then, a qRT-PCR assay was used to detect the mRNA expression of the proliferation-related genes CCND1, CCND2, CDK1, CDK2 and CDK6. We found that the gga-miR-449b-5p mimic suppressed the mRNA expression of CCND1 and CCND2 (p < 0.05 and p < 0.05) but upregulated the mRNA expression of CDK2 and CDK6 (p < 0.01; Figure 2b). Next, a CCK-8 analysis was performed to determine the changes in GC viability at 12, 24, 36 and 48 h, and we found that both overexpression of and interference with gga-miR-449b-5p had no significant effect on the viability of GCs (Figure 2c,d). EdU analysis was performed to detect the number of proliferating GCs after transfection of cells with gga-miR-449b-5p mimics and gga-miR-449b-5p inhibitors. We found that neither overexpression of nor interference with gga-miR-449b-5p had a significant effect on the proliferation of GCs (Figure 2e). The same results were found for the flow cytometric assays (Figure 2f,g). These results indicated that gga-miR-449b-5p had no effect on the viability and proliferation of GCs in laying hen follicles.
We determined the role of gga-miR-449b-5p in P4, T, and E2 secretion in chicken granulosa cells using qPCR and ELISAs. The expression of key genes related to steroid synthesis was first detected. The qPCR results showed that the overexpression of gga-miR-449b-5p reduced the mRNA expression of StAR and CYP19A1 (p < 0.01), and interfering with gga-miR-449b-5p had the opposite effect (Figure 3a). The ELISA results showed that the P4 and E2 levels in the GCs after transfection with gga-miR-449b-5p mimic were decreased (p < 0.01 and p < 0.05), while the P4 and E2 levels in the GCs after transfection with gga-miR-449b-5p inhibitor were increased (p < 0.05 and p < 0.01; Figure 3b). These results suggest that gga-miR-449b-5p can regulate the synthesis and secretion of steroids and then affect the ovarian function of laying hens.
We examined several potential targets predicted in previous studies to be associated with the regulatory effects of gga-miR-449b-5p on steroidogenesis, including IGFBP4, PGRMC1, MMP2, IGF2BP3, BMP3 and E2F5. We found that the mRNA expression of MMP2 and IGF2BP3 decreased markedly after overexpression of gga-miR-449b-5p (p < 0.05 and p < 0.01; Figure 4a). To verify which was the direct target gene of gga-miR-449b-5p, we used a dual-luciferase reporter assay. The results showed that there was no targeting relationship between MMP2 and gga-miR-449-5p (Figure 4b). Notably, the gga-miR-449b-5p mimic significantly decreased the activity of WT IGF2BP3 (p < 0.01), but no significant changes were noted for the MUT, which indicated that IGF2BP3 was directly targeted by gga-miR-449b-5p (Figure 4c).
To test the validity of the putative target, we transfected gga-miR-449b-5p mimic or NC and inhibitor or NCR into chicken GCs. The results showed that compared with the gga-miR-449b-5p inhibitor NCR, the gga-miR-449b-5p inhibitor significantly increased the protein expression of IGF2BP3 (p < 0.05), while compared with the gga-miR-449b-5p mimic NC, the gga-miR-449b-5p mimic significantly inhibited the protein expression of IGF2BP3 (p < 0.01). These results further suggested that gga-miR-449b-5p plays a regulatory role by targeting IGF2BP3 (Figure 5).
The development of ovarian follicles is the basis of female animal reproduction. As the most basic functional unit of the ovary, the granulosa layer of poultry follicles is closely linked to the development and selection of dominant follicles. The proliferation, apoptosis and steroid synthesis of follicular granulosa cells are not only affected by nutritional and environmental factors but also regulated by miRNAs [52]. The miR-449b-5p has been a known regulatory function in human reproduction-related diseases, such as breast cancer, endometrial cancer and cervical cancer. Jiang et al. found that miR-449b-5p may inhibit the growth and invasion of breast cancer cells by inhibiting the CREPT/Wnt/β-catenin axis [53]. Zhao et al. reported that miR-449b-5p inhibited the proliferation of endometrial cancer cells by targeting MDM4 [54]. Another report found that overexpression of miR-449b-5p in cervical cancer cell lines significantly inhibits cell proliferation [55]. All the above results show that miR-449b-5p has a potentially important influence on regulation of cell proliferation, but its role in ovarian granulosa cells needs to be further explored. Therefore, we speculate that gga-miR-449b-5p has a similar role in GCs. CCND1, CCND2, CDK1, CDK2 and CDK6 were reported to be marker genes for cell proliferation, which was found in GCs [56,57]. In this study, we examined the role of gga-miR-449b-5p in GC proliferation by marker gene-related proliferation, CCK-8, flow cytometry and EdU experiments. Surprisingly, we found that the proliferation of GCs was not affected by gga-miR-449b-5p mimic or inhibitor transfection, indicating that the function of gga-miR-449b-5p in GCs is different from that of the above studies, and this difference can be attributed to the differences between species and cell models. As gga-miR-449b-5p was confirmed to be enriched in the pathway related to steroid synthesis, we explored the specific role of gga-miR-449b-5p in steroid synthesis in GCs. P4, androgen and E2 are the main steroids that play a crucial role in the regulation of female fertility [58]. Previous reports identified an androgen receptor in GCs [59]. GCs are believed to be mediated by follicle stimulating hormone and synthesize P4 under the action of StAR, CYP11A1 and 3β-HSD [60,61]. In addition, P4 is a precursor of estradiol synthesis in TCs, which is stimulated by luteinizing hormone and catalyzed by CYP19A1. Thus, the synthesis of steroids in TCs needs to be carried out with the participation of GCs to regulate the synthesis and secretion of steroids [62,63,64,65,66]. Therefore, in this experiment, we determined P4, T and E2 secretion by ELISAs as well as the expression of StAR, CYP11A1, 3β-HSD, and CYP19A1 by qPCR. The results showed that gga-miR-449b-5p inhibited the expression of the steroid synthesis-related genes StAR, 3β-HSD and CYP19A1 and the production of P4 and E2. This result is consistent with the previous results concerning the validation of miRNA function in steroid the synthesis of GCs [35,37,43]. Several studies have shown that the insulin-like growth factor-2 mRNA-binding protein family is involved in mammalian follicular development and steroid secretion [67,68,69]. IGF2BP3 is an important member of this family [70]. Current studies have shown that IGF2BP3 ensures the early embryonic development of zebrafish by maintaining the stability of maternal RNA [71]. The expression of IGF2BP3 in medaka is also closely associated with oocyte development [72]. These results indicate that IGF2BP3 may play a role in the development of animal ovaries. We further investigated several potential target genes of gga-miR-449b-5p in this study. Interestingly, it was found that overexpression of gga-miR-449b-5p could significantly reduce the expression of MMP2 and IGF2BP3. Furthermore, through double luciferase reporter gene detection, we demonstrated that gga-miR-449b-5p was able to target IGF2BP3. Furthermore, IGF2BP3 gene and protein levels decreased after gga-miR-449b-5p mimic transfection, and vice versa. These data suggest that gga-miR-449b-5p regulates steroid synthesis in GCs by targeting IGF2BP3.
gga-miR-449b-5p inhibits the secretion of P4 and E2 in GCs by targeting the IGF2BP3 gene and inhibiting its expression. Our results may provide scientific insights into the regulatory mechanism of miRNAs in follicular development in the future. | true | true | true |
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PMC9559784 | Zainab H. D. AL-Tamimi,Abdulsamie H. Alta’ee,Ahmed H. Jasim | Effect of Toll-Like Receptor 7 Gene Polymorphism and ABO Blood Groups on the Severity of COVID-19 Patients | 01-09-2022 | TLR-7,ABO,COVID-19,rs179008,Genetic Polymorphism | Background: The most current threat to global health is the continuous spread of a respiratory disease known as COVID-19 Disease 2019 in recent years. COVID-19 was recognized in December 2019. It was quickly determined that a novel COVID-19 virus, which is structurally linked to the virus that causes the severe acute respiratory syndrome, was to cause (SARS). Objective: The aim of this study is to investigate the presence of effect between the rs179008 (A/T) SNP polymorphism in TLR7 gene and blood group on the severity of COVID-19. Methods: The study included 90 patients divided into three groups mild, moderate, severe, and experimental research work was conducted during the period of sample collection extended from November 2021 to February, PCR-RFLP technique was used to determine SNP rs179008 polymorphism in TLR7 in the blood. Results: A present study found non-significant differences between patient groups for TLR7 rs179008 (A, T) allele were (p=0.79152) for mild to moderate and severe, (p=0.84872) for mild and moderate and (p=0.58741) for mild and severe. When comparison (AA, AT, TT) genotypes in three groups found a significant difference between mild and moderate groups (p=0.036) for the AA genotype. Found (A blood group) more frequency than other groups but observes no significant difference between patients’ group. Conclusion: We conclude that the (AA) genotype for TLR7 rs179008 polymorphism was a risk factor and effect on severity of COVID-19 infection, so (AA) can consider an independent risk factor for development of COVID-19. | Effect of Toll-Like Receptor 7 Gene Polymorphism and ABO Blood Groups on the Severity of COVID-19 Patients
The most current threat to global health is the continuous spread of a respiratory disease known as COVID-19 Disease 2019 in recent years. COVID-19 was recognized in December 2019. It was quickly determined that a novel COVID-19 virus, which is structurally linked to the virus that causes the severe acute respiratory syndrome, was to cause (SARS).
The aim of this study is to investigate the presence of effect between the rs179008 (A/T) SNP polymorphism in TLR7 gene and blood group on the severity of COVID-19.
The study included 90 patients divided into three groups mild, moderate, severe, and experimental research work was conducted during the period of sample collection extended from November 2021 to February, PCR-RFLP technique was used to determine SNP rs179008 polymorphism in TLR7 in the blood.
A present study found non-significant differences between patient groups for TLR7 rs179008 (A, T) allele were (p=0.79152) for mild to moderate and severe, (p=0.84872) for mild and moderate and (p=0.58741) for mild and severe. When comparison (AA, AT, TT) genotypes in three groups found a significant difference between mild and moderate groups (p=0.036) for the AA genotype. Found (A blood group) more frequency than other groups but observes no significant difference between patients’ group.
We conclude that the (AA) genotype for TLR7 rs179008 polymorphism was a risk factor and effect on severity of COVID-19 infection, so (AA) can consider an independent risk factor for development of COVID-19.
Coronavirus disease 2019 (COVID-19) is the third plague of this century, and it has been designated as the sixth international health issue. The World Health Organization has declared a global health emergency in 2020 (1, 2). The International Committee on Virus Taxonomy of Viruses named it severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (3). In 2019 December, A group of individuals with pneumonia of indefinite etiology was discovered in Wuhan, Hubei Province, China (4). The China CDC (the Chinese Center for Disease Control and Prevention) detected a new coronavirus from lower respiratory tract samples of pneumonia patients that will be collected on January 7, 2020, and released the genomic sequence on 11 January 2020. In less than a few months after the unknown pathogen was discovered, it had infected at least 114 countries, killing nearly 4,000 people (5). It’s the seventh coronavirus to infect humans; the other four (229E, NL63, OC43, and HKU1) cause very moderate cold symptoms. SARS-CoV, MERS-CoV, and SARS-CoV-2, on the other hand, can cause life-threatening symptoms and even death (6). This is a worldwide emergency that requires the joint determinations of all humanity s to prevent it (7). The most well-known viruses are divided into groups based on their phylogenies with viruses that have previously infected the same host, as well as their genotype (8), it was Spherical or pleomorphic particles ranging in length from 80 to 160 nm the presence of single-stranded (positive-sense) RNA coupled with a nucleoprotein was found in a capsid containing matrix protein (9).SARS-CoV-2 has four major structural proteins: membrane (M) glycoprotein, spike (S) glycoprotein, small envelope (E) glycoprotein and nucleocapsid (N) protein, as well as a number of auxiliary proteins (10). This viral can enter to human body through the receptors ACE2 type I integral membrane protein that has mono carboxypeptidase activity which are found in many organs such as the heart, lungs, kidneys, and gastrointestinal system, thus facilitating virus entry into target cells. Attachment of the S glycoprotein that is form homotrimers protruding from the virus surface to the receptor ACE2 in the host cell, is the first step in Covid-19 entering the host cell such as in type II pneumocystis in the lungs (11). The most commonly reported symptoms are fever, cough and shortness of breath (12). Cough (with or without sputum), fatigue, discomfort, weakness, arthralgia or myalgia, chest tightness, extreme mucus creation with expectoration, hemoptysis, and dyspnea are some of the symptoms that might occur (13, 14). Gastrointestinal symptoms such as vomiting, diarrhea and abdominal pain are observed in some patients with COVID-19 (15). Toll Like Receptor (TLR7) is PRRs located on intracellular organelles (16, 17). which produce antiviral immunity by recognizing single-stranded RNA (ss-RNA) from viruses and the consequent activation of pro-inflammatory pathways (18, 19). TLR7’s ability to inhibit virus replication has been established in MERS-CoV (20). As viral ssRNA binds to TLR7/8 upon entrance into the cell, increasing activation and antiviral immunity (21). TLR7 activation causes the adaptor molecule MyD88 to be recruited, subsequent in the release of pro-inflammatory cytokines and chemokines (22). IFNs of type I (IFN-alpha and IFN-beta) and III (IFN-alpha and IFN-beta) (IFN-lambda) (23).
The aim of this study is to investigate the presence of effect between the rs179008 (A/T) SNP polymorphism in TLR7 gene and blood group on the severity of COVID-19.
This study was done at the laboratory of Chemistry and Biochemistry Department, College of Medicine University of Babylon. This study was designed as cross-sectional study, involved a total of 90 patients divided into three groups according to severity by physician mild, moderate and severe groups, all sample collection from November 2021 to February, Samples were collected from Baquba Teaching hospital and Muqdadiya General Hospital, Diyala Province, Iraq.
Drawn five milliliters blood from venous and put into Sodium Citrate for D-dimer use and 2ml into EDTA tube for CBC, Blood group, genotype and other blood placed into gel tube then Centrifuge at (3000 X g) 10 min for separation serum, Blood for ABO blood group, genotype by PCR-RFLP by using Zh08 amplification primer including forward 5’ GTTGCAAAAGAGAGGCAGCAA 3’, and reverse 3’CTGTGCAGTCCACGATCACA5’, then procedure pcr according to the manufacturing instructions.
First, a glass side was prepared and marked with three circles after cleaning the slide and then Anti-A, Anti-B and Anti-D in the first, second and third circle respectively were added with the help of a dropper. By use pipette, three drops of the antigen were added on anti A, B, and D in glass slid. With the use of a toothpick, the blood sample was gently mixed and the outcome was observed after a minute.
The statistical program for social sciences (SPSS) version 23 and Microsoft Office Excel 2010 were used to collect, summarize, analyze, and present the data. The Hardy-Weinberg equation was used for performed the genotype analysis in COVID-19 patients were found depending on the probability at p > 0.05 (24).
Table 1 showed the mean of age between the COVID-19 patients and severity of disease, where the age ranges from (1-85 years), 63 (70%) as females and 27(30%) as males. In addition, the we found 21 cases for mild symptoms at percentage (23.3%), 26 cases for moderate symptoms at (28.9%), and 43 cases for severe symptoms at (47.8%).
Table 2 showed the distribution of COVID-19 patients according to the ABO blood group, where the highly percentage of patients was in A+ at 34.4% (31 out of 90 for patients), while the lower percentage was in B-& O-at 2.2% (2 out of 90 patients). Table 3 showed the association between COVID-19 patients and ABO blood group according to the severity of disease ,where the highly number of patients was in A+ at 34.4% (31 out of 90 for patients) including ( 4,9,18) for mild, moderate and severe symptoms respectively, while the lower number of patients was in B-at 2.2% (2 out of 90 patients) including (2,0,0) for mild, moderate and severe symptoms respectively and O-at 2.2% (2 out of 90 patients), including (1,0,1) for mild, moderate and severe symptoms respectively. Table 4 showed the association between COVID-19 patients and severity of disease according to the types of genotype, where the highly number of patients was in AA type at 60 out of 90 cases, while the lower number of patients was in TT at 6 out of 90 cases. Table 5 showed the association between COVID-19 patients with mild symptoms and COVID-19 patients with moderate and severe symptoms according to the Allele Frequency of rs179008, where OR (95% CI) of allele A was at 1.121 (0.480-2.620) for mild and moderate symptoms, while for T allele was at 0.892 (0.382-2.084) for mild and moderate symptoms, the statistical analysis don’t shows any significant differences at p-value 0.05. Table 6 showed the association between COVID-19 patients with mild symptoms and COVID-19 patients with moderate symptoms according to the Allele Frequency of rs179008, where OR (95% CI) of allele A was at 0.909 (0.341-2.421) for mild and moderate symptoms, while for T allele was at 1.100 (0.413-2.929) for mild and moderate symptoms, the statistical analysis don’t shows any significant differences at p-value 0.05. Table 7 showed the association between COVID-19 patients with mild symptoms and COVID-19 patients with severe symptoms according to the Allele Frequency of rs179008, where OR (95% CI) of allele A was at 1.291 (0.512-3.252) for mild and severe symptoms, while for T allele was at 0.775 (0.308-1.951) for mild and severe symptoms, the statistical analysis don’t shows any significant differences at p-value 0.05. Table 8 showed the association between COVID-19 patients with mild symptoms and COVID-19 patients with moderate and severe symptoms according to the (A/T) SNP genotypes, where the co-dominant, dominant, recessive and over dominant models don’t show any significant differences at p-value 0.05. Table 9 showed the association between COVID-19 patients with mild symptoms and COVID-19 patients with moderate according to the (A/T) SNP genotypes, where the recessive and over dominant models shows significant differences at (0.025 and 0.035) respectively. Table 10 showed the association between COVID-19 patients with mild symptoms and COVID-19 patients with severe symptoms according to the (A/T) SNP genotypes, where the co-dominant, dominant, recessive and over dominant models don’t show any significant differences at p-value 0.05.
In this study when comparison between these group was found no significant association between ABO blood group and the severity of COVID-19 patients in statistic. But, according to Table 1 found the patients of (A) and (O) groups more frequency in severe patients. This study corresponds to French and Spanish studies was found not related with increased or decreased risk of COVID-19 infection (25). These data are opposite the previous studies. Which described they found group O in depressing risk of COVID-19 (26). Angiotensin-converting enzyme 2 (ACE2) has been described to be the SARS-CoV receptor, and the receptor binding domain is obtainable on the S proteins of the coronaviruses (27). They wanted to see if ABO antibodies could end the interaction between the SARS-CoV receptor and ACE2 and, as a result, adhesion of S protein and ACE2 can be inhibited by anti-A and anti-B natural antibody, recent study give an explanation for the upper risk for blood group A, may absence of these antibodies The genetic background of social populations can influence the vulnerability and result of infectious diseases. Reports suggested that the variations within the host’s genome play a role in COVID-19 disease progression (28). in this study TLR7 rs179008 polymorphism over dominant (AT) genotype was high significant between mild and moderate groups and play role as protective against COVID-19 disease progression and then was observed a no significant distribution of allele (A, T) for TLR7 gene rs179008 polymorphism between three groups. TLR7 is a key factor in the production of interferon (IFN), which has a direct antiviral effect by inhibiting virus replication., As viral ssRNA binds to TLR7/8 upon entrance into the cell, increasing activation and antiviral immunity (21). TLR7 activation causes the adaptor molecule MyD88 to be recruited, resulting in the release of pro-inflammatory cytokines and chemokines (22), IFNs of type I (IFN-alpha and IFN-beta) and III (IFN-alpha and IFN-beta) (IFN-lambda) (23). It has been shown to aid in viral clearance and reduction of replication. The current study should be replicated in populations from other parts of Iraq with a larger sample size, More research is needed to better understand the significance of the TLR7 rs179008A/T polymorphism in vulnerability to disease development in COVID-19 infection.
We conclude that the (AA) genotype for TLR7 rs179008 polymorphism was a risk factor and effect on severity of COVID-19 infection, so (AA) can consider as independent risk factor for development of COVID-19. | true | true | true |
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PMC9559825 | Liqing Zhao,Suqiu Huang,Wei Wei,Bingyao Zhang,Wenxiang Shi,Yongzhou Liang,Rang Xu,Yurong Wu | Novel compound heterozygous CCDC40 mutations in a familial case of primary ciliary dyskinesia | 29-09-2022 | primary ciliary dyskinesia,CCDC40,situs inversus,annular pancreas,pathogenic mutation | Primary ciliary dyskinesia (PCD) is a rare genetic disorder characterized by motile ciliary dysfunction and impaired ultrastructure. Despite numerous studies, the genetic basis for about 30% of PCD cases remains to be elucidated. Here, we present the identification and functional analysis of two novel mutations in the gene encoding coiled-coil domain-containing protein 40 (CCDC40), which are found in a familial case of PCD. These novel CCDC40 mutations, NM_017950.4: c.2236-2delA and c.2042_2046delTCACA, NP_060420.2: p.(Ile681fs), were identified by whole-exome sequencing (WES). Sanger sequencing was then performed to confirm the WES results and determine the CCDC40 gene sequences of the proband’s parents. The c.2042_2046delTCACA mutation disrupts the reading frame of the protein and is therefore predicted to produce a non-functional protein. Using a minigene assay with the pcDNA3.1(+) plasmid, we further investigated the potential pathogenic effects of the c.2236-2delA mutation and found that this mutation leads to formation of a truncated protein via splicing disruption. Thus, in summary, we identified two mutations of the CCDC40 gene that can be considered pathogenic compound heterozygous mutations in a case of familial PCD, thereby expanding the known mutational spectrum of the CCDC40 gene in this disease. | Novel compound heterozygous CCDC40 mutations in a familial case of primary ciliary dyskinesia
Primary ciliary dyskinesia (PCD) is a rare genetic disorder characterized by motile ciliary dysfunction and impaired ultrastructure. Despite numerous studies, the genetic basis for about 30% of PCD cases remains to be elucidated. Here, we present the identification and functional analysis of two novel mutations in the gene encoding coiled-coil domain-containing protein 40 (CCDC40), which are found in a familial case of PCD. These novel CCDC40 mutations, NM_017950.4: c.2236-2delA and c.2042_2046delTCACA, NP_060420.2: p.(Ile681fs), were identified by whole-exome sequencing (WES). Sanger sequencing was then performed to confirm the WES results and determine the CCDC40 gene sequences of the proband’s parents. The c.2042_2046delTCACA mutation disrupts the reading frame of the protein and is therefore predicted to produce a non-functional protein. Using a minigene assay with the pcDNA3.1(+) plasmid, we further investigated the potential pathogenic effects of the c.2236-2delA mutation and found that this mutation leads to formation of a truncated protein via splicing disruption. Thus, in summary, we identified two mutations of the CCDC40 gene that can be considered pathogenic compound heterozygous mutations in a case of familial PCD, thereby expanding the known mutational spectrum of the CCDC40 gene in this disease.
Primary ciliary dyskinesia (PCD) (OMIM#244400) is a rare genetic disorder affecting between 1:15,000 and 1:30,000 individuals worldwide (1, 2). Most PCD cases are inherited in an autosomal recessive manner, although rare cases have been reported to show X-linked inheritance (2, 3). The disease is characterized by impaired function of motile cilia (4), and clinical manifestations include chronic or recurrent respiratory tract infections, situs inversus (SI), conductive hearing impairment, and infertility (5). In addition, dextrocardia with SI, involving a total mirror-image arrangement of all thoracic and abdominal viscera, occurs in approximately 50% of PCD cases, and these were shown to be diagnosed earlier than cases with normal organ position (6). To date, a series of monogenic mutations in over 40 causative genes that contribute to the abnormal structure and function of motile cilia in PCD has been reported (7). The guidelines agree that either a biallelic pathogenic mutation or hemizygous X-linked mutation in a known PCD gene is sufficient to confirm a diagnosis (8, 9). PCD causative genes have been shown to affect ciliary protein function and transport, as well as docking of ciliary structures. In particular, most affected individuals exhibit mutations in genes that encode dynein arm components, such as dynein axonemal heavy chain (DNAH)5, DNAH11, dynein axonemal intermediate chain (DNAI)1, DNAI2, and thioredoxin domain-containing (TXNDC)3 (7). Coiled-coil domain-containing protein (CCDC) 39 and CCDC40, the 96-nm ruler proteins, are responsible for the correct establishment of 96-nm repeats along the ciliary axoneme (7). CCDC40 is also thought to be essential for the docking of inner dynein arms (IDAs) and plays a vital role in left–right axis specification (10). However, despite numerous genetic findings, the genetic basis for about 30% of PCD cases remains unknown, suggesting the existence of other causative genes and mutations. In this study, we report the genetic analysis of a newborn who was prenatally diagnosed with dextrocardia, total SI, and duodenal obstruction. The proband also exhibited neonatal respiratory distress at term birth. Diagnosis of PCD was confirmed according to guidelines of the American Thoracic Society (9), and exome analysis of the proband identified novel heterozygous mutations, NM_017950.4: c.2236-2delA and c.2042_2046delTCACA, NP_060420.2: p.(Ile681fs), in the CCDC40 gene. These two novel CCDC40 mutations were inherited from the proband’s mother and father, respectively, as confirmed by Sanger sequencing. Using a series of bioinformatic analyses and the minigene assay, we further verified the pathogenicity of the mutated sites. Thus, to the best of our knowledge, our study is the first to report a pathogenic role for these heterozygous CCDC40 gene mutations in PCD.
A Chinese family, including the proband, was analyzed in this study (Figure 1A). The proband was transferred to the neonatal intensive care unit (NICU) immediately after birth due to prenatal suspected gastrointestinal tract anomalies and SI in the third trimester. A series of examinations were performed after birth, including chest radiography, echocardiography, chest computed tomography scan, and gastrointestinal contrast (Figure 1). This study was conducted in compliance with the Declaration of Helsinki and was approved by the Ethics Committee of Xinhua Hospital (Approval no. XHEC-QT-2021-042); written informed consent was obtained from both parents.
Genomic DNA (gDNA) was isolated from 2-ml peripheral blood samples obtained from each family member using the QIAamp DNA Mini Kit, according to the manufacturer’s instructions (QIAGEN, Hilden, Germany). Purified gDNA from the proband was analyzed by whole-exome sequencing (WES), using a commercial sequencing services company (Shanghai Biotechnology Co., Ltd., Shanghai, China). Exome capture was performed using the SureSelect Human All Exon V6 system (Agilent Technologies, Santa Clara, CA, USA), according to the manufacturer’s instructions. Exome sequencing libraries were then subjected to quality control testing and analyzed by 2 × 150 bp paired-end sequencing on the HiSeq X Ten platform (Illumina, San Diego, CA, USA). FASTQ files were aligned to the human reference genome (hg19/GRCh37). Based on the quality of the reads, the fragments were analyzed with different tools (11), and the detected variants were exported in a Microsoft Excel file.
To confirm WES results in the proband and determine the CCDC40 gene sequences of the proband’s parents, we performed bidirectional Sanger sequencing, using an ABI 3730 capillary sequencing instrument (Applied Biosystems, Foster City, CA, USA). Primer sequences are listed in Table 1.
We used multiple bioinformatics programs, including the Human Splicing Finder (HSF) tool and MutationTaster, to predict possible impacts of the detected CCDC40 variants.
We used the minigene assay to assess the pathogenicity of the c.2236-2delA mutation and determine the splicing capacity of the wild-type (WT) and mutant sequence (12). Because the c.2236-2delA mutation is in intron13, we amplified 2,962-bp gDNA fragments that include exon13, intron13, exon14, intron14, and exon15 from the PCD patient and a control patient (primer sequences are listed in Table 1). To construct CCDC40 expression plasmids, the WT and mutant PCR products were inserted into the pcDNA3.1(+) vector (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) by the GENEWIZ company, using the Seamless Cloning Kit (Hanbio, China). The WT construct was named WT-E131415-pcDNA3.1, and the mutant construct was named MUT-E131415-pcDNA3.1. After plasmid amplification in DH5α Escherichia coli and plasmid purification (Omega Bio-Tek, Norcross, GA, USA), the sequences and correct orientations of all plasmid constructs were validated by Sanger sequencing, as described above.
Human embryonic kidney 293T cells were maintained in Dulbecco’s Modified Eagle Medium (DMEM) with high glucose (HyClone, Logan, UT, USA) and 10% fetal bovine serum (FBS; Gibco, Thermo Fisher Scientific). Cells were incubated at 37°C in a humidified atmosphere with 5% CO2 and plated onto 6-well plates for 18 h before transfection at a confluence of 60–70%. WT and mutant CCDC40 plasmids were transfected into 293T cells using FuGene HD Transfection Reagent (Promega, Madison, WI, USA), according to the manufacturer’s protocol.
Total RNA was extracted from transfected 293T cells using TRIzol Reagent (Invitrogen, Thermo Fisher Scientific), and RT-PCR was performed with the PrimeScript RT Reagent Kit (TaKaRa Bio, Kusatsu, Shiga Prefecture, Japan). Primers for PCR amplification are listed in Table 1.
The proband (G1P1), a female infant, is the first child of non-consanguineous and healthy parents. She was born at 39-weeks’ gestation to a 28-year-old mother and a 27-year-old father, and her family history is unremarkable. Postnatal transthoracic echocardiography revealed a diagnosis of mirror-image dextrocardia, interrupted inferior vena cava (IVC), secondary atrial septal defect (ASD), and a patent foramen ovale (PFO). Chest radiograph (Figure 1B) and computed tomography scan further indicated bronchopneumonia and total SI (Figure 1C), and gastrointestinal contrast confirmed a diagnosis of duodenal obstruction (Figure 1D). Lastly, the patient received a diagnosis of annular pancreas based on results of surgery performed on the second day after birth.
To identify possible pathogenic mutations, we performed WES analysis of a gDNA sample from the proband, yielding approximately 6 Gb data and producing 205,579,454 total reads. From this analysis, we obtained a coverage of 1x, 20x, and 50x across 99.38, 93.93, and 85.23%, respectively, of the captured target area. We first filtered the WES data by (1) including only variants located in exonic or splicing regions, (2) excluding synonymous variants, and (3) excluding variants with a minor allele frequency (MAF) > 0.001. Next, based on the observed clinical phenotypes and autosomal recessive inheritance patterns, we identified two mutations of the CCDC40 gene, c.2236-2delA and c.2042_2046delTCACA p.(Ile681fs), that may function as pathogenic compound heterozygous mutations in PCD. We then performed Sanger sequencing, which confirmed the presence of these variants in the proband and revealed that the frameshift mutation c.2042_2046delTCACA was inherited from the mother, whereas the c.2236-2delA mutation was inherited from the father (Figure 2A). Copy number variation (CNV) analysis was also performed on WES data, and no abnormal CNV was detected.
We next predicted the pathogenicity of the frameshift mutation c.2042_2046delTCACA (p.Ile681fs) and the splicing mutation c.2236-2delA in CCDC40 (Figure 2B) using two online analysis tools: MutationTaster and HSF. MutationTaster classified the c.2042_2046delTCACA mutation as “Disease-causing,” based on the prediction that it causes a frameshift and creates a premature stop codon p.(Ile681fs), leading to translation of a truncated protein without the N-terminal 390 amino acids. Results of HSF analysis further showed that the c.2236-2delA mutation likely affects splicing by altering the WT acceptor splice site, with the variation (%) of Position Weight Matrices relative to the WT site (–30.27) indicating that this site is dysfunctional in mutant mRNA. Thus, our results strongly suggest that both mutations in the CCDC40 gene are pathogenic. Furthermore, these variants are novel, as neither has been reported in the 1,000 Genomes Project database, the Exome Aggregation Consortium (ExAC) database, or the Human Gene Mutation Database (HGMD).
Lastly, we performed a minigene assay with the pcDNA3.1(+) plasmid to investigate the potential pathogenic effect of the c.2236-2delA mutation. To this end, RNA was extracted from 293T cells transfected with WT-E131415-pcDNA3.1 or MUT-E131415-pcDNA3.1 (Figure 3A), and after reverse transcription (RT) and amplification, the spliced sequences were examined using Sanger sequencing. Our results revealed that the WT construct produces a whole 630-bp band, which results from normal splicing between exon13 and exon15 (Figure 3B). However, the mutant produces a band of 416 bp, resulting from exon14 skipping between exon13 and exon15 (Figure 3B) and leading to a frameshift in the transcript. These results therefore indicate that the c.2236-2delA mutation results in production a truncated protein by disrupting splicing.
In the present study, we performed genetic analysis of a newborn PCD patient presenting with neonatal respiratory distress, secondary ASD, SI with dextrocardia, and annular pancreas. WES revealed two novel mutations, c.2236-2delA and c.2042_2046del TCACA, p.(Ile681fs), in the CCDC40 gene. These two mutations carried by the proband were inherited from the father and mother, respectively, which generated compound heterozygosity in the patient. Diagnosis of PCD is often delayed due to the non-specific symptoms and lack of early diagnostic methods. Studies have shown that different ciliary phenotypes in PCD patients result from a variety of mutations in cilia-related genes, and genotype–phenotype relationships underlying this disease are becoming more apparent (13). Genetic testing is therefore useful to confirm the genotype of probable PCD cases and is an important component of PCD diagnosis based on to current guidelines (8, 9), with a PCD genetic testing panel currently in development. In particular, genetic analysis is critical for early diagnosis, determination of proper disease-management strategies, and family genetic counseling for PCD cases (7, 8). CCDC40 belongs to a group of evolutionarily conserved coiled-coil domain-containing proteins that, together with CCDC39, is known as a 96-nm ruler protein, due its essential role in ensuring the correct establishment of 96-nm repeats along the ciliary axoneme (7). CCDC40 also appears to be required for axonemal recruitment of CCDC39 (10). The CCDC40 protein, which contains 1,142 residues and eight predicted coiled coils, is specifically expressed in the embryonic node and is essential for the formation and maintenance of cilia (14) (Figure 2B). The coiled-coil motif is a common structural domain in eukaryotic and prokaryotic proteins and can act as an adapter between molecules (14). CCDC40 also contains a conserved BRE1 domain of unknown function, as well as two large Structural Maintenance of Chromosomes (SMC) conserved domains, which are found in several ciliary proteins and likely play a role in microtubule-based ciliary transport processes (15) (Figure 2B). A number of mutations in CCDC40 have been identified as novel candidates for gene testing in PCD patients, with these mutations estimated to cause approximately 4–8% of PCD cases (16). Previous studies in animal models have suggested that mutations in CCDC40 disrupt cilia function via the loss of IDAs, which is accompanied by variably expressed disorganization of the 9 + 2 microtubule arrangement (15). These CCDC40-affected cilia often show loss of waveform motion and become completely immotile (15). Here, we found that the c.2236-2delA CCDC40 gene variant is predicted to affect the acceptor splice site, and results of our minigene assay confirm this mutation causes exon skipping, which results in production of abnormal CCDC40 mRNA with an altered reading frame. The other variant, c.2042_2046delTCACA, directly shifts the reading frame and introduces a stop codon, thereby putatively leading to production of a truncated, non-functional protein. Notably, both of these variants result in complete loss of the second SMC domain in the CCDC40 protein (Figure 2B), which may explain the observed PCD phenotype in the proband. PCD patients with CCDC40 mutations or those displaying associated ultrastructural defects (inner dynein arm/central apparatus/microtubular defects) have been reported to show worse lung disease and poorer growth compared to those with outer dynein arm defects (defined by ultrastructure and mutations in associated genes) (4). In addition, the long-term prognosis of CCDC39- or CCDC40-affected cases is worse than for other PCD patients, with similar findings reported for individuals with cystic fibrosis, as well (4). In both instances, recurrent respiratory tract infections in patients with dysfunctional cilia may lead to irreversible lung damage. Early diagnosis is therefore important to select an appropriate disease-management strategy for preventing the onset of this damage. Approximately half of all PCD patients exhibit SI, also referred to as Kartagener syndrome (KTS) (17), and this trait appears to result, in part, from random determination. However, one previous study found that PCD patients with SI show more complex genetic heterogeneity than unaffected individuals (18), and the disease mechanisms affecting nodal cilia function are also important for determination of left–right asymmetry during embryogenesis. Of note, CCDC40 in particular, was shown to be expressed in the embryonic node and midline tissues in a mouse model of PCD (10). Thus, the observed phenotype of total SI with mirror-image dextrocardia in the proband is consistent with these genetic findings. Annular pancreas, another phenotype present in the proband for our study, is a rare congenital gastrointestinal anomaly characterized by a ring of pancreatic tissue surrounding the descending portion of the duodenum. It is thought to originate from incomplete rotation of the ventral pancreatic bud, and many reports have indicated a genetic basis for this anomaly (19). However, to the best of our knowledge, our study is the first showing annular pancreas associated with PCD, and thus, the genetic connection underlying this feature requires further investigation.
In conclusion, we identified two compound heterozygous mutations in the CCDC40 gene of a newborn baby with PCD, one affecting the acceptor splice site and one causing a direct frameshift, both of which are reported for the first time in this study. These results provide new insight into the genetic basis of PCD and will be critical for obtaining a definitive diagnosis, determining a follow-up disease-management strategy, and providing comprehensive genetic counseling for this family.
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary material.
The studies involving human participants were reviewed and approved by the Ethics Committee of Xinhua Hospital. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.
YW, RX, and LZ: study concept and research design. LZ, BZ, and WS: patient’s clinical data. SH, WW, and YL: sequencing and mutation validation. LZ, SH, and YW: writing of the manuscript. All authors have read and agreed to the published version of the manuscript. | true | true | true |
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PMC9560479 | Mi Ra Chang,Patrick R. Griffin | RORβ modulates a gene program that is protective against articular cartilage damage | 13-10-2022 | Osteoarthritis (OA) is the most prevalent chronic joint disease which increases in frequency with age eventually impacting most people over the age of 65. OA is the leading cause of disability and impaired mobility, yet the pathogenesis of OA remains unclear. Treatments have focused mainly on pain relief and reducing joint swelling. Currently there are no effective treatments to slow the progression of the disease and to prevent irreversible loss of cartilage. Here we demonstrate that stable expression of RORβ in cultured cells results in alteration of a gene program that is supportive of chondrogenesis and is protective against development of OA. Specifically, we determined that RORβ alters the ratio of expression of the FGF receptors FGFR1 (associated with cartilage destruction) and FGFR3 (associated with cartilage protection). Additionally, ERK1/2-MAPK signaling was suppressed and AKT signaling was enhanced. These results suggest a critical role for RORβ in chondrogenesis and suggest that identification of mechanisms that control the expression of RORβ in chondrocytes could lead to the development of disease modifying therapies for the treatment of OA. | RORβ modulates a gene program that is protective against articular cartilage damage
Osteoarthritis (OA) is the most prevalent chronic joint disease which increases in frequency with age eventually impacting most people over the age of 65. OA is the leading cause of disability and impaired mobility, yet the pathogenesis of OA remains unclear. Treatments have focused mainly on pain relief and reducing joint swelling. Currently there are no effective treatments to slow the progression of the disease and to prevent irreversible loss of cartilage. Here we demonstrate that stable expression of RORβ in cultured cells results in alteration of a gene program that is supportive of chondrogenesis and is protective against development of OA. Specifically, we determined that RORβ alters the ratio of expression of the FGF receptors FGFR1 (associated with cartilage destruction) and FGFR3 (associated with cartilage protection). Additionally, ERK1/2-MAPK signaling was suppressed and AKT signaling was enhanced. These results suggest a critical role for RORβ in chondrogenesis and suggest that identification of mechanisms that control the expression of RORβ in chondrocytes could lead to the development of disease modifying therapies for the treatment of OA.
Osteoarthritis (OA) is the most prevalent chronic degenerative joint disease where the risk of disease increases in with age and obesity [1–3]. OA occurs more commonly later in life, after years of mechanical wear and tear on cartilage, a tissue that lines and cushions joints. Most therapies target pain relief and currently there are no effective treatments to slow the progression of the disease. Disease progression eventually results in irreversible loss of cartilage and when articular cartilage is significantly degraded or completely lost, joint replacement surgery is the only option [4]. Although the correlation between aging and the development of OA is not completely understood, it is becoming clear that age-related changes in the musculoskeletal system, combined with mechanical injury and genetic factors all contribute to the pathogenesis of OA [5, 6]. Thus, uncovering the molecular mechanism of joint degeneration requires analysis of cartilage metabolism, chondrocyte senescence, and inflammation [7]. Such studies should lead to the identification of therapeutic targets for treating and preventing OA. Chondrocytes are critical to maintenance of articular cartilage where loss of chondrocytes leads to cartilage damage and this damage is often irreversible. Chondrocyte progenitor cells would be an ideal experimental model for the proposed studies, but markers for such cells are still unclear, and the expression level of several candidate markers such as Notch1 and SOX9 are not consistent on superficial zone (SZ), middle zone (MZ), and deep zone (DZ) of normal tissue and OA tissue [8]. Therefore, in the studies presented here we utilized MG63 cells to overcome these issues. MG63 cells are derived from an established sarcoma cell line and is an osteoblastic model to study bone cell viability, adhesion, and proliferation. Importantly, these cells express the mesenchymal stem cell markers Notch1 and SOX9 and are a well characterized osteoblast-like cell line which can drive development of OA. It has been shown that controlled fibroblast growth factor (FGF) signaling is essential for the balance of articular cartilage metabolism, as evidenced by the fact that aberrant FGF signaling contributes to progression of OA [9]. FGFR1 signaling triggers upregulation of pro-inflammatory mediators, matrix metalloproteinases (MMPs), and alters anabolic activities of articular cartilage by inhibition of extracellular matrix (ECM) production and autophagy. Whereas FGFR3 signaling is cartilage protective mainly through the inhibition of pro-inflammatory mediators and hypertrophic differentiation, as well as reduced MMP expression. For this reason, FGFR1 antagonists and FGFR3 agonists are being pursued as potential therapeutic strategies for OA [10–12]. Nuclear receptors (NRs) represent a druggable superfamily of ligand-dependent transcription factors. The NR1F subfamily of NRs contains the retinoic acid receptor-related orphan receptors (RORs), which have homology to both the retinoic acid receptors (RARs) and the retinoid X receptors (RXRs) [13]. The ROR subfamily includes three major isoforms, RORα, RORβ, and RORγ. The physiological functions of RORα and RORγ have been well characterized and they have been shown to play roles in regulation of metabolism and inflammation while RORβ (NR1F2) has been significantly less well studied. RORβ is expressed in regions of the CNS that are involved in processing of sensory information and components of the mammalian clock, the suprachiasmatic nuclei, the retina, and the pineal gland. RORβ has been shown to play a critical role for the proliferation and differentiation of retinal cells in addition to the maintenance of circadian rhythms [14–16]. The clock gene BMAL1 (brain and muscle Arnt-like protein 1), a target gene of the RORs, was reported that contributed to the maintenance of cartilage homeostasis [17, 18]. Recently, it was shown that RORβ plays a role in osteogenesis by impacting Runx2 target gene expression. Levels of RORβ inversely correlated with osteogenic potential suggesting that suppression of RORβ may drive osteoblastic mineralization. It was shown that RORβ and a subset of RORβ-regulated genes were increased in bone biopsies from post-menopausal women compared to pre-menopausal women suggesting a role for RORβ in human age-related bone loss [19]. Additionally, it was shown that the miR-219a-5p regulates RORβ during osteoblast differentiation and in age-related bone loss [20]. While RORβ-/- mice display bone abnormalities, it was shown that deletion of RORβ was osteoprotective [21]. The main goal of this study was to determine if overexpressing RORβ in an osteoblast-like cell would inhibit the osteoblast phenotype while inducing a chondrogenic phenotype. Here we demonstrate that stable expression of the nuclear receptor RORβ in cultured cells results in alteration of a gene program that is supportive of chondrogenesis and protective against development of OA. Specifically, RORβ balances the expression of genes implicated in cartilage homeostasis such as altering FGFR signaling towards that favorable for cartilage stability. While it remains unclear how RORβ regulates the balance of FGFR1/3 expression and downstream signaling, the results presented here suggest RORβ is an important transcription factor involved in the control of a gene program that could prevent articular cartilage damage. Understanding the mechanism of RORβ control of this gene program could lead to the identification of novel therapeutics or drug targets for the prevention and/or treatment of OA.
Full length wild type human RORβ (NM_006914.3) was subcloned into the pLPCX retroviral vector (Clontech) using XhoI and NotI restriction enzymes (NEB) with forward primer 5’- CGCGCTCGAGATGCGAGCACAAATTGAAGTGATAC-‘3 and reverse primer 5’-GCGGCGGCCGCTCATTTGCAGCCGGTGGCAC-‘3. PCR product was obtained with Maxime PCR Premix (i-pfu) (Intron Biotechnologies). pLPCX vector was digested and then dephosphorylated before ligation using the Rapid DNA Dephos & Ligation Kit (Roche). Ampicillin resistance clones were verified using a 5’ sequencing primer 5’-AGCTGGTTTAGTGAACCGTCAGATC-3’ and 3’ sequencing primer 5’-ACCTACAGGTGGGGTCTTTCATTCCC-3’. Selected clone was linearized with AseI (NEB) restriction digestion and dephosphorylated with Antarctic Phosphatase (NEB) prior usage in transfection. Human osteoblast-like MG-63 cells (ATCC CRL-1427TM) were maintained in EMEM (Eagle’s Minimum Essential Medium, ATCC) with 10% heat-inactivated fetal bovine serum (Invitrogen). Linearized hRORβ/pLPCX plasmid was transfected using lipid mediated transfection method (MG-63 transfection kit, Altogen Biosystems). 0.5 ug/ml of Puromycin was added into complete media for selection of stable expressing hRORβ/pLPCX in MG-63 cells. A clone expression high levels of RORβ and a mock-vector clone were used for the following experiments.
Total RNA was extracted using a Qiagen Kit-74106. Total RNA was quantified using a Qubit 2.0 Fluorometer (Invitrogen, Carlsbad, CA) and run on an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA) for quality assessment. RNA samples of good quality with RNA integrity number (RIN) > 8.0 were further processed. A RNase-free working environment was maintained, and RNase-free tips, Eppendorf tubes, and plates were utilized for the subsequent steps. Messenger RNA was selectively isolated from total RNA (300 ng input) using poly-T oligos attached to magnetic beads and converted to sequence-ready libraries using the TruSeq stranded mRNA sample prep protocol (cat. #: RS-122-2101, Illumina, San Diego, CA). The final libraries were validated on the bioanalyzer DNA chips, and qPCR was quantified using primers that recognize the Illumina adaptors. The libraries were then pooled at equimolar ratios, quantified using qPCR, and loaded onto the NextSeq 500 flow cell at 1.8 pM final concentration. They were sequenced using the high-output, paired-end, 75-bp chemistry. Demultiplexed and quality filtered raw reads (fastq) generated from the NextSeq 500 were trimmed (adaptor sequences) using Flexbar 2.4 and aligned to the mouse reference database (mm9) using TopHat version 2.0.9 (Trapnell, et al.). HTseq-count version 0.6.1 was used to generate gene counts and differential gene expression analysis was performed using Deseq2 (Anders and Huber). We then identified genes that were significantly downregulated or upregulated (adjusted P < 0.05) in each comparison. The RNA-seq data is deposited in https://www.ncbi.nlm.nih.gov/geo/ GSE208277.
Protein was purified using RIPA lysis and extraction buffer (ThermoFisher Scientific) from MG-63 clones. HaltTM Protease and phosphatase inhibitor cocktail (100X, ThermoFisher Scientific) were added into lysis buffer. To normalize the amount of cell lysate run on SDS-PAGE, BCA (Thermo Fisher Scientific) assay was used. Anti-ROR beta antibody (rabbit monoclonal EPR15552, abcam), anti-phospho ERK1/2 (D13.14.4E, CST), anti-ERK1/2 (L34F12, CST), anti-phospho AKT (D9E, CST), anti-AKT (40D4, CST), and anti-beta Actin (8H10D10, CST) antibodies were used for primary antibodies. IRDye 680RD and IRDye800CW were used for secondary antibodies. A LI-COR Odyssey system was used for fluorescence imaging. Anti- aggrecan Ab (6-B-4, abcam) was used for primary antibody and FITC-anti mouse Ab was used for secondary antibody. Cell sorting was performed using LSRII (BD Bioscience).
Total RNA was extracted from RORβ OE/MG63 cells using RNeasy Plus Micro Kit (Qiagen), and the RNA was reverse transcribed using the ABI reverse transcription kit (Applied Biosystems/Thermo Fisher Scientific, Waltham MA). Quantitative PCR was performed with a 7900HT Fast Real Time PCR System (Applied Biosystems) using SYBR green (Roche). A list of primers used for these studies is shown in S1 Table. To measure the effect of IL1β stimulation, 2 nM ILβ (recombinant human IL-1β/IL-1F2, R&D system) was added to WT and RORB OE cells. After 24hr, total RNA was isolated and analyzed by qRT-PCR.
To determine if overexpressing RORβ in an osteoblast-like cell line would inhibit the osteoblast phenotype while inducing a chondrogenic phenotype MG63 cells were transfected with a pLPCX vector harboring the puromycin-resistance gene and human RORβ cDNA. The transfected cells were selected with puromycin and the expression of RORβ was analyzed by western blotting using an anti-human RORβ specific rabbit EPR1552 mAb with fluorescence imaging using a LI-COR system (Fig 1A). Anti-beta actin (8H10D10) was used as a protein loading control. Relative mRNA expression of hRORβ was determined for clones that survived selection (Fig 1B). One clone demonstrating high expression of RORβ was selected for all subsequent studies. The expression level of RORβ in this clone was confirmed monthly. A control cell line was generated by transfection of MG63 cells with the pLPCX vector devoid of RORβ and selection with puromycin to generate the wild-type (WT) clone. The WT clone line was used as a control for all studies presented.
To investigate the biological function of RORβ in MG63 cells, RORβ OE-MG63 cells (cells overexpressing RORβ) and mock vector transfected MG63 cells (WT clone) were analyzed by mRNAseq. Three independent biological replicates were processed and analyzed. Principle component analysis results and a heatmap of the sample to sample distance are shown in Fig 2A and 2B. To investigate molecular pathways altered by RORβ expression, we analyzed log2 fold change of mRNA sequencing data using QIAGEN ingenuity pathway analysis (IPA) software with a P-value cutoff of 0.05. As shown in Fig 2C, cells overexpressing RORβ showed alteration in genes involved in signaling pathways associated with OA when compared with WT cells. As further detailed below, the expression profiling results suggest that RORβ may play a protective role in chondrocytes to prevent development of OA.
Aging and chronic inflammation are associated with increase in several critical genes associated with the induction of OA. Matrix metalloproteinases (MMPs) including ADAM metallopeptidase with thrombospondin type 1 motif 4 (ADAMTS4) and MMP3 and the proinflammatory cytokine IL6 are well characterized pathogenic genes for OA. Interestingly, increased expression of RORβ in MG63 cells suppressed the expression of these genes (Fig 3A) and we demonstrate that the cartilage damaging factor MMP3 was also reduced at the protein level (Fig 3B). These results suggest that RORβ may play an inhibitory role to prevent cartilage damage by suppression of chondrocyte degradation by blocking chondrocyte catabolic pathways.
Articular cartilage is composed of collagens, proteoglycans, and non-collagenous proteins. Extracellular matrix proteoglycans and collagens play a critical role in the maintenance of articular cartilage structure by regulating chondrocyte proliferation and promoting cartilage repair [22]. Induction of OA is initiated by mechanical forces and inflammatory events that destabilize the normal coupling of synthesis and degradation of extracellular matrix proteins in both articular cartilage and subchondral bone. In the study presented here, we observed that the expression of the core structural genes in articular cartilage, aggrecan (ACAN) and collagen type II alpha (COL2A1), were increased by overexpressing RORβ in MG63 cells (Fig 3C). Additionally, we demonstrate that ACAN protein level was also increased when compared to the WT clone (Fig 3D). The levels of ACAN protein in RORβ OE MG63 cells was similar to that observed in TC28a2 cells, which are normal chondrocyte cells. Thus, RORβ inhibits the production of MMPs and increases the expression of extracellular matrix proteins, both of which would be protective to articular cartilage degradation.
Fibroblast growth factor (FGF) signaling has a role in growth and homeostasis of joint related cells, including articular chondrocytes, synovial cells, and osteogenic cells and aberrant FGF signaling contributes to the progression of OA [23]. Genetic inhibition of FGFR1 in knee cartilage attenuates cartilage degradation by the RAF-MEK-ERK and PKCd-p38 pathways [24] and conditional deletion of FGFR3 in mice aggravated DMM-induced cartilage degeneration [25]. In addition, FGF18 attenuates cartilage degradation through FGFR3/PI3K-AKT signaling [26]. As shown in Fig 4A, stable expression of RORβ reduced the ratio of FGFR1/FGFR3 towards a protective profile. This alteration of FGFR signaling correlates with changes in phosphorylation of ERK1 (decreased) and AKT (increased) as expected (Fig 4B).
IL-1β is an essential mediator of acute joint inflammation induced by physical injuries and it plays a critical role in cartilage degradation. Induction of IL-1β increases the expression of catabolic matrix enzymes such as MMPs and ADAMTS, as well as the pro-inflammatory cytokine IL-6 which ultimately leads to cartilage matrix degradation [27–29]. Here we demonstrate that stable expression of RORβ suppressed IL-1β induced expression of IL6, MMP3 and ADAMTS4. Additionally, expression of RORβ downregulates expression of MMP3 and ADAMTS4 as compared to WT control cells (Fig 5).
Development of OA impairs the biomechanical properties of articular cartilage eventually leading to irreversible loss of cartilage resulting in debilitating joint pain and swelling. Owing to the limited regenerative capacity of articular cartilage, advanced surgical techniques have been usually required for repair of damaged cartilage [30, 31]. Risk factors for the development of OA include age, obesity, physical injury, and low-grade systemic inflammation where pro-inflammatory mediators such as IL-6 and TNFα can exacerbate cartilage erosion [32, 33]. While the pathogenesis of OA remains unclear, hypertrophic chondrocyte differentiation, reduced proliferation, dysregulated apoptosis, combined with the loss of collagen, proteoglycans and cartilage integrity are associated with the development of OA [3]. An important observation in patients with OA is the upregulation of FGFR1 expression which appears to accelerate matrix degradation by inducing the expression of RUNX2 /ELK1 and consequent downregulation of FGFR3 in articular cartilage. Furthermore, pharmacological inhibition of FGFR1 attenuates progression of disease in a mouse model of OA [10] and FGFR3 deficiency in myeloid cells enhances CXCRL12 dependent chemotaxis via CXCR7 (CXC-chemokine receptor 7), thereby leading to the exacerbation of joint destruction [34]. In this study we demonstrate that the nuclear receptor RORβ balances FGFR1/R3 signaling towards that favorable for cartilage stability by suppressing FGFR1 expression and amplifying that of FGFR3. While it remains unclear how RORβ regulates the balance of FGFR1/3 expression, the results presented here suggest RORβ is an important transcription factor controlling a gene program that is protective against articular cartilage damage. Future studies focused on understanding the mechanism of RORβ’s control of FGFR1/3 modulation in chondrocytes and murine models of OA could lead to the identification of novel therapeutics and drug targets for the prevention and or treatment of OA.
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PMC9560808 | Fu Gui,Xinyi Yu,Yemeng Wu,Chao Wu,Yulan Zhang | Mechanism of LncHOTAIR Regulating Proliferation, Apoptosis, and Autophagy of Lymphoma Cells through hsa-miR-6511b-5p/ATG7 Axis | 06-10-2022 | Objective To explore the role of LncHOTAIR in apoptosis and autophagy in lymphoma. Methods The interaction between LncHOTAIR and miR-6511b-5p, as well as between miR-6511b-5p and ATG7, was verified by a dual luciferase assay. LncHOTAIR overexpression lentivirus was transducted and siATG7s were transfected into Raji and BJAB lymphoma cells, and the efficiency was verified by qPCR. Lymphocyte proliferation was detected by the cell counting kit-8 (CCK8) test, and autophagy was detected by transmission electron microscopy. The protein expressions of ULK1, Beclin1, ATG7, LC3, Bax, cleaved-caspase 3, and Bcl-2 were detected using Western blots. Results There was a targeting relationship between LncHOTAIR and miR-6511b-5p and between miR-6511b-5p and ATG7. LncHOTAIR overexpression promoted the proliferation and autophagy of Raji and BJAB cells, significantly upregulated ATG7, Beclin1, ULK1, Bcl-2, and LC3-II/LC3-I levels, and downregulated Bax and cleaved-caspase3 levels. siATG7 significantly inhibited the proliferation and autophagy of Raji and BJAB cells and promoted their apoptosis. Conclusion LncHOTAIR/hsa-miR-6511b-5p/ATG7 could regulate the proliferation, apoptosis, and autophagy of Raji and BJAB lymphoma cells. | Mechanism of LncHOTAIR Regulating Proliferation, Apoptosis, and Autophagy of Lymphoma Cells through hsa-miR-6511b-5p/ATG7 Axis
To explore the role of LncHOTAIR in apoptosis and autophagy in lymphoma.
The interaction between LncHOTAIR and miR-6511b-5p, as well as between miR-6511b-5p and ATG7, was verified by a dual luciferase assay. LncHOTAIR overexpression lentivirus was transducted and siATG7s were transfected into Raji and BJAB lymphoma cells, and the efficiency was verified by qPCR. Lymphocyte proliferation was detected by the cell counting kit-8 (CCK8) test, and autophagy was detected by transmission electron microscopy. The protein expressions of ULK1, Beclin1, ATG7, LC3, Bax, cleaved-caspase 3, and Bcl-2 were detected using Western blots.
There was a targeting relationship between LncHOTAIR and miR-6511b-5p and between miR-6511b-5p and ATG7. LncHOTAIR overexpression promoted the proliferation and autophagy of Raji and BJAB cells, significantly upregulated ATG7, Beclin1, ULK1, Bcl-2, and LC3-II/LC3-I levels, and downregulated Bax and cleaved-caspase3 levels. siATG7 significantly inhibited the proliferation and autophagy of Raji and BJAB cells and promoted their apoptosis.
LncHOTAIR/hsa-miR-6511b-5p/ATG7 could regulate the proliferation, apoptosis, and autophagy of Raji and BJAB lymphoma cells.
Lymphoma is a systemic malignant tumor that originates from the lymphohematopoietic system, accounting for 3%–4% of all malignant tumors. Most lymphomas originate from B cells, whereas other lymphomas are derived from T cells or natural killer (NK) cells [1]. Burkitt lymphoma (BL) belongs to B-cell lymphoma, which leads to poor prognosis due to unclear early symptoms and a lack of effective treatment [2, 3]. Therefore, it is key to explore and identify new biomarkers for early detection and effective treatment. Long noncoding RNA (e.g., LncRNA) is defined as longer than 200 nucleotides, and many lncRNAs are abnormally expressed in different diseases, especially cancer. The imbalance of lncRNA mainly promotes cancer progression by promoting the malignant biological behavior of tumor cells (such as proliferation, invasion, or metastasis). LncRNA can be used as tumor markers to provide a basis for early diagnosis of cancer because some lncRNA have abnormal expression in various types of human tumors. LncHOTAIR is abnormally expressed in solid tumors, acute leukemia, and lymphoma, and is closely related to tumor proliferation, apoptosis, and migration [4, 5]. Autophagy plays a role in “tumor inhibition” in the occurrence, development, and malignant evolution of various cancers, including gastric cancer, glioma, and pancreatic cancer [6]. ATG7 is an E1-likeubiquitin-activating enzyme, and it is needed during autophagy as well as cytoplasmic-to-vacuolar transportation. However, no study has confirmed the regulatory relationship between LncHOTAIR and autophagy. Therefore, to explore the regulatory mechanism between LncHOTAIR and autophagy in BL cells, we predicted that hsa-miR-6511b-5p may be involved in the regulation between LncHOTAIR and ATG7 using bioinformatics. We explored the molecular mechanisms of LncHOTAIR and ATG7 regulating proliferation, apoptosis, and autophagy in Raji and BJAB cells, which provided a theoretical basis for understanding how autophagy is involved in the pathogenesis of BL lymphoma.
The Raji and BJAB cells (cultured in RPMI1640 + 10% FBS) and 293T cells (cultured in DMEM + 10% FBS) were obtained from ATCC and cultured at 37°C with 5% CO2.
miR-6511b-5p′s interaction with LncHOTAIR and ATG7 were tested using pRL-SV40 containing LncHOTAIR and ATG7 3′-UTR luciferase reporter gene plasmids as a previously publication [7]. Sea kidney luciferase was used for standardization. miR-6511b-5P mimic sequences CUGCAGGCAGAAGUGGGGCUGACA,UGUCAGCCCCACUUCUGCCUGCAG and NC sequences UCACAACCUCCUAGAAAGAGUAGA,UCUACUCUUUCUAGGAGGUUGUGA.
Total RNA was extracted from cells using the RNeasy kit (Qiagen) and reverse transcribed into cDNA according to the kit's instructions. The rt-PCR was performed on an ABI StepOne Plus system using SYBR Green qPCR Master Mix (Thermo Fisher Scientific, USA). The reaction was set at 95°C for 10 min for activation, then 95°C for 5 s, and 60°C for 40 s, with 40 cycles. β-Actin or U6 were employed as internal controls, and the amount of mRNA was calculated by the 2−ΔΔCT method. The primer sequences were summarized in Table 1.
The logarithmic growth phase cells were harvested from plates by trypsin digestion, added into plates (1 × 104 cells per well of 96-well) for overnight incubation, then 10 μl of cell counting kit-8 (CCK8) solution, which was purchased from Beyotime (Shanghai, China), was added, followed by a 4 h incubation [8]. The OD450 was measured with a SmartReader 96 Microplate Absorbance Reader (Benchmark Scientific, USA; n = 6 per group).
The cells were collected and washed with ice-coldphosphate-buffered saline (PBS), followed by apoptosis detection by the AnnexinV-FITC Analysis Kit on a NovoCyte™ flow cytometry according to the instructions.
The cells were collected, washed with PBS, fixed with 70% ethanol at 4°C, followed by ribonuclease treatment, and 200 μl of 50 μg/ml of propidium iodide (PI) were added. After 30 minutes of incubation in the dark, samples were loaded for flow cytometry analysis [9].
The samples were fixed and dehydrated, embedded with acetone embedding solution, and solidified in an oven. The blocks were cut into 70 nm slices with an ultramicrotome. The slices were observed after 7.3% uranium acetate-lead citrate double staining under JEOL JEM-1230 (80 KV) TEM.
RIPA buffer was used for cell lysis. Lysates were centrifuged at 4°C (10000 rpm) for 10 min, and a BCA Protein Assay Kit (ThermoFisher, USA) was used to measure concentrations of the supernatant. Protein lysates were mixed with loading buffer, denatured at 95°C for 10 minutes, and separated (50 μg/lane) by electrophoresis in SDS-PAGE. Then, proteins were transferred to a PVDF membrane, which was washed and blocked using blocking buffer, followed by primary antibody incubation at 4°C overnight, rinsed, and the secondary antibody incubation for 1 h at room temperature, then immunoblotted by an enhanced chemiluminescence kit (Perkin-Elmer Inc.), and finally the Quantity One software was used for quantification.
The LncHOTAIR overexpression and control lentivirus were prepared by [7] and were transduced as previously described [10]. The transfection was conducted with the Lipofectamine 3000 kit (Thermo Fisher Scientific) in a control group, an siATG7 NC group, and an siATG7 group. The siRNA sequences are shown in Table 2.
The data were analyzed by SPSS 20.0 (IBM, Armonk, NY, USA). One-way ANOVA was used to calculate the differences among groups. A 2-sidedP < 0.05 was used to determine statistical significance.
LncHOTAIR WT bound with miR-6511b-5p mimic and significantly reduced luciferase activity (Figure 1(a)), ATG7 WT bound with miR-6511b-5p mimic and also significantly reduced luciferase activity (Figure 1(b)). These showed that LncHOTAIR and miR-6511b-5p, and miR-6511b-5p and ATG7 had a targeting relationship, respectively.
In Figure 2, in Raji and BAJB cells, the level of LncHOTAIR increased significantly after transduction with the LncHOTAIR overexpression lentivirus vector compared with those in the control group and empty NC group (P < 0.05), which suggested that LncHOTAIR overexpression lentivirus transduction was successful.
As shown in Figure 3, LncHOTAIR overexpression significantly promoted the proliferation of Raji and BJAB cells compared to that of the control group and NC group (P < 0.05).
The autophagy of Raji and BAJB cells was observed by TEM (Figure 4). Compared with the control group and NC group, the autophagy bodies significantly increased in the LncHOTAIR overexpression group. These results suggested that LncHOTAIR overexpression promoted autophagy in Raji and BAJB cells.
The LncHOTAIR overexpression significantly increased the levels of autophagy related proteins ATG7, Beclin1, LC3-II/LC3-I, ULK1 and the antiapoptotic protein Bcl-2 in Raji and BAJB cells, and the levels of proapoptotic proteins were significantly decreased, such as Bax and cleaved-caspase3 (Figure 5).
The expression level of ATG7 in the siATG7-1, siATG7-2 and siATG7-3 groups decreased significantly in Raji and BAJB cells compared with that of the control group and NC group (P < 0.05), especially in the siATG7-1 group (Figure 6). Therefore, siATG7-1 was selected as the interference vector of ATG7 in subsequent experiments.
ATG7 significantly decreased the viability of Raji and BAJB cells (Figure 7, P < 0.05).
In Raji and BAJB cells, siATG7 significantly promoted cell apoptosis. It blocked BJAB and Raji cells in G0/G1 phase, which indicates that siATG7 could affect G0/G1 phase and then affect apoptosis (Figure 8).
The autophagy of Raji and BAJB cells was observed by TEM after siATG7 treatment (Figure 9). The autophagy bodies significantly decreased in the siATG7 group. These results suggested that siATG7 inhibited the autophagy of Raji and BAJB cells.
The siATG7 significantly inhibited autophagy-related proteins and antiapoptotic proteins in Raji and BAJB cells, and significantly increased proapoptotic proteins (Figure 10).
Lymphoma is a malignant tumor that is primarily located in lymph nodes or extranodal lymphoid tissue. Its incidence rate is increasing and seriously threatens human health. In B-cell lymphoma, the content of BIC RNA/miR-155 increased significantly, and it was different among patients, suggesting that miR-155 may be transcribed and regulated by BIC RNA [11]. LncHOTAIR was upregulated in diffuse large B-cell lymphoma (DLBCL). Its expression level was significantly correlated with tumor characteristics. Knockdown of LncHOTAIR in vitro may lead to tumor cell growth inhibition, cell cycle arrest, and apoptosis through the PI3K/AKT/NF-κB pathway [12]. LncHOTAIR expression in DLBCL may induce H3K27me3 through EZH2-related PRC2 activation [13]. In this study, LncHOTAIR overexpression could significantly promote the proliferation of Raji and BAJB cells, which is consistent with Yan et al.'s results [12]. Bax promotes apoptosis, whereas Bcl-2 inhibits apoptosis [14]. When Bax expression increases, a large number of Bax homodimers are formed, which induces the release of Cyt-C into the cytoplasm and activates caspase-9. Then, caspase-9 digests caspase-3 zymogen and activates caspase-3, promotes the cleavage of caspase-3, starts a caspase cascade reaction, and induces apoptosis [15]. In colorectal cancer (CRC), siLncHOTAIR could significantly bring down Bcl-2 and bring up Bax and cleaved-caspase 3 protein expression [7], which was confirmed in our study in Raji and BAJB lymphoma cells. Autophagy, also known as a special type of programmed cell death, participates in many pathological processes as well as biological growth and development. LncHOTAIR and ATG7 were upregulated and autophagy was significantly increased during liver injury. However, after LncHOTAIR expression was knocked down, autophagy induced by hydrogen peroxide in isolated hepatocytes was attenuated, and LncHOTAIR regulated autophagy in liver injury [16]. This study predicted that hsa-miR-6511b-5p may be involved in the regulation of LncHOTAIR and ATG7 using the bioinformatic databases of TargetScan and Starbase, and proved that hsa-miR-6511b-5p had target sites for LncHOTAIR and ATG7 by dual luciferase reporter gene assay. Overexpression of LncHOTAIR could significantly upregulate ATG7 and increase the number of autophagy bodies in Raji and BAJB cells. Autophagy is related to nutritional status, energy status, oxidative stress, ischemia, and hypoxia. It is regulated by multiple mechanisms, such as the ULK1 pathway, Beclin1 pathway, p53 pathway, AMP-activated protein kinase AMPK pathway, and so on. The Beclin1 pathway is the downstream regulatory signal of ULK1. ULK1 complex can phosphorylate Beclin1-Ser14 and Vps34Ser249, promote Beclin1-Vps34 complex formation, and thus promote the occurrence of autophagy [17]. LC3 is the earliest marker for autophagy, whose precursor excises the carboxyl terminal to generate LC3I, followed by covalent binding with phospholipids on the autophagy body membrane to form LC3II [18]. In this study, LncHOTAIR overexpression significantly promoted the expression levels of proteins related to autophagy, such as LC3-II/LC3-I, Beclin-1, and ULK1, which was consistent with the previous results [12, 16]. ATG7 is closely related to abnormal proliferation and drug resistance of a variety of tumors [19–24]. ATG7 deficiency completely inhibited the occurrence and development of mouse intestinal epithelial cell tumors and promoted the body's antitumor immune response [25]. In the mouse model, knockout of the ATG7 gene significantly reduced the tumorigenicity of tumor cells and promoted the transformation of lung cancer cells into benign tumors [26]. In this study, siATG7 significantly inhibited Raji and BAJB lymphoma cell proliferation. In bladder cancer, ATG7 played a role in cell invasion, and ATG7-specific therapy had certain development potential [27]. ATG7 can also promote angiogenesis in the brain [28], regulate the activity of caspase-9, and regulate the process of apoptosis [29]. In SH-SY5Y cells, knockdown of ATG7 significantly decreased Bcl-2 while increasing Bax and Caspase-3, which proved that ATG7-mediated autophagy could not only promote cell proliferation but also inhibit cell apoptosis [30]. In this study, siATG7 significantly downregulated Bcl-2 and upregulated Bax and caspase3. The knockdown of the ATG7 gene could inhibit the conversion from LC3-I to LC3-II [30], which was consistent with the results of this study.
In conclusion, this study found that the proliferation, apoptosis, and autophagy of Raji and BJAB lymphoma cells induced by the LncHOTAIR overexpression may be realized by autophagy-related protein ATG7. In BL lymphoma cells, ATG7 may promote abnormal cell proliferation and inhibit apoptosis by mediating autophagy. | true | true | true |
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PMC9560823 | Xiaolu Song,Yirui Chen,Ye Peng,Xiaogang Wang,Sujie Zheng,Fangfang Shi,Jianping Lan | LncRNA-PAX8-AS1 Silencing Decreases Cell Viability, Enhances Apoptosis, and Suppresses Doxorubicin Resistance in Myeloid Leukemia via the miR-378g/ERBB2 Axis | 06-10-2022 | Objective Considering the role of lncRNAs reported as regulators in acute myeloid leukemia (AML) progression, the current research aims to investigate the role of PAX8-AS1 in chemo-resistant AML. Methods Human AML cells HL60 and human doxorubicin (ADM)-resistant AML cells (HL60/ADM cells) were used to establish in vitro models of chemo-sensitive AML and refractory/recurrent AML, respectively. CCK-8 assay and flow cytometry were used to determine cell resistance to ADM, viability, and apoptosis. PAX8-AS1, miR-378g, and ERBB2 expressions in the models and/or AML patients were quantified via qRT-PCR or Western blot. The miRNA/mRNA axis targeted by PAX8-AS1 was analyzed using Starbase, TargetScan, or GEO and validated through a dual-luciferase reporter assay. The expressions of Bcl-2, Bax, and C Caspase-3 in cells were quantitated by Western blot. Results The highly expressed PAX8-AS1 was observed in AML patients and HL60 cells, which was more evident in refractory/recurrent AML patients and HL60/ADM cells. Compared with that in ADM-treated parental HL60 cells, the viability of ADM-treated HL60/ADM cells remained strong. PAX8-AS1 overexpression increased viability and Bcl-2 expression, while diminishing apoptosis, Bax, and C Caspase-3 expressions in HL60 cells. However, the abovementioned aspects were oppositely impacted by PAX8-AS1 silencing in HL60/ADM cells. PAX8-AS1 directly targeted miR-378g, whose expression pattern is opposite to that of PAX8-AS1 in AML. MiR-378g upregulation abrogated the effects of PAX8-AS1 overexpression on HL60 cells. MiR-378g downregulation offset PAX8-AS1 silencing-induced effects on HL60/ADM cells. Moreover, ERBB2 was recognized as the target of miR-378g, with a higher expression in HL60/ADM cells than in HL60 cells. Conclusion PAX8-AS1 silencing decreases cell viability, enhances apoptosis, and suppresses ADM resistance in AML via regulating the miR-378g/ERBB2 axis. | LncRNA-PAX8-AS1 Silencing Decreases Cell Viability, Enhances Apoptosis, and Suppresses Doxorubicin Resistance in Myeloid Leukemia via the miR-378g/ERBB2 Axis
Considering the role of lncRNAs reported as regulators in acute myeloid leukemia (AML) progression, the current research aims to investigate the role of PAX8-AS1 in chemo-resistant AML.
Human AML cells HL60 and human doxorubicin (ADM)-resistant AML cells (HL60/ADM cells) were used to establish in vitro models of chemo-sensitive AML and refractory/recurrent AML, respectively. CCK-8 assay and flow cytometry were used to determine cell resistance to ADM, viability, and apoptosis. PAX8-AS1, miR-378g, and ERBB2 expressions in the models and/or AML patients were quantified via qRT-PCR or Western blot. The miRNA/mRNA axis targeted by PAX8-AS1 was analyzed using Starbase, TargetScan, or GEO and validated through a dual-luciferase reporter assay. The expressions of Bcl-2, Bax, and C Caspase-3 in cells were quantitated by Western blot.
The highly expressed PAX8-AS1 was observed in AML patients and HL60 cells, which was more evident in refractory/recurrent AML patients and HL60/ADM cells. Compared with that in ADM-treated parental HL60 cells, the viability of ADM-treated HL60/ADM cells remained strong. PAX8-AS1 overexpression increased viability and Bcl-2 expression, while diminishing apoptosis, Bax, and C Caspase-3 expressions in HL60 cells. However, the abovementioned aspects were oppositely impacted by PAX8-AS1 silencing in HL60/ADM cells. PAX8-AS1 directly targeted miR-378g, whose expression pattern is opposite to that of PAX8-AS1 in AML. MiR-378g upregulation abrogated the effects of PAX8-AS1 overexpression on HL60 cells. MiR-378g downregulation offset PAX8-AS1 silencing-induced effects on HL60/ADM cells. Moreover, ERBB2 was recognized as the target of miR-378g, with a higher expression in HL60/ADM cells than in HL60 cells.
PAX8-AS1 silencing decreases cell viability, enhances apoptosis, and suppresses ADM resistance in AML via regulating the miR-378g/ERBB2 axis.
Acute myeloid leukemia (AML) is characterized by clinical and biological heterogeneity and poor prognosis and is the most common subtype of acute leukemia in adults [1]. Uncontrolled proliferation and impaired differentiation of clonal mass of myeloid stem cells are considered to be highly related to the pathogenesis of AML [2] and can lead to a rapid onset of deadly infections, bleeding, or organ infiltration [3]. Currently, chemotherapy has emerged as the main therapeutic option for AML when compared to molecularly targeted drugs and allogeneic hematopoietic stem cell transplantation [4]. However, chemotherapy has a propensity to fail owing to the acquired resistance of leukemia cells to chemotherapeutic agents [4]. The development of multidrug resistance (MDR) involves multiple mechanisms [5], which are ATP-binding cassette (ABC) overexpression-induced drug efflux pumps that reduce intracellular drug concentrations [6], FLT3 mutation [7], DNA repair abnormalities [8], apoptosis tolerance [5], and bone marrow microenvironment changes [9]. Doxorubicin (ADM) is a first-line chemotherapeutic drug used in AML [10] and has been recorded to mediate caspase activation and apoptotic DNA fragmentation to induce death of AML cells [11]. Resistance to ADM involves upregulation of proteins from the ABC superfamily to cause efflux of the drug in AML cells [12], which remains a significant obstacle to the successful treatment of AML. Notably, an existing study has revealed that altered expressions of long noncoding RNAs (lncRNAs) are implicated in the ADM resistance of patients diagnosed with relapsed/refractory AML [13]. LncRNAs, a class of transcripts produced in mammals and other eukaryotes, are constituted by over 200 nucleotides without an open reading frame, possessing great functional diversity [14]. Considerable lncRNAs have been recognized to be biologically significant in many human diseases including malignant tumors [15, 16]. Aberrant expressions of lncRNAs can cause repercussions on cancer cell proliferation and apoptosis, thus altering drug resistance to eventually affect cancer progression [17, 18]. A report has shown that poor outcomes for AML patients are attributed to resistance to treatment [4]. Therefore, targeting lncRNAs with an intention to antagonize treatment resistance may be a promising approach to improve the result of AML patients. The lncRNA risk score system built for predicting survival of children with AML has uncovered that PAX8 antisense RNA 1 (PAX8-AS1) in combination with MYB-AS1 can serve as effective predictor of AML prognosis [19]. PAX8-AS1, an lncRNA located in the upstream region of the paired box 8 (PAX8) gene, modulates the expression of PAX8 gene [20], which is found to upregulate the Wilms' tumor gene 1 (WT1), an oncogene for AML [20, 21]. Previous data have also indicated that the polymorphisms of PAX8-AS1 are related to an increased risk of childhood AML [22]. These discoveries underlined that PAX8-AS1 may contribute to AML development and progression. In addition, since lncRNAs can modulate ADM resistance [13], which is critically related to the poor outcomes of AML patients [4], and PAX8-AS1 expression can reflect the poor prognosis of AML childhood, we hypothesized that PAX8-AS1 may be possibly implicated in ADM-resistant AML, thus impacting the prognosis of ADM-resistant patients. Accordingly, we investigated the specific molecules that might have an association with the poor prognosis of AML patients from the perspective of PAX8-AS1. Furthermore, a well-known mechanism, through which lncRNAs can modulate cell biological behaviors, is the consequence of the process in which lncRNAs sponge microRNA (miRNA) to indirectly regulate gene expression [23]. Therein, miRNAs are those small noncoding RNAs, a great number of which are also found to be dysregulated along with their target genes in AML [24, 25]. Wang et al. have proposed that PAX8-AS1, whose overexpression leads to the development of gynecological cancers, may exert an oncogenic effect through constructing a PAX8-AS1-hsa-miR-4461-TNIK network in uterine corpus endometrial carcinoma (UCEC) [26]. Bioinformatic analyses conducted in the current study preliminarily predicted that miR-378g is a miRNA directly targeted by PAX8-AS1. A previous study has confirmed that miR-378g promotes the osteogenic differentiation of bone marrow mesenchymal stem cells after escaping from the inhibition caused by HOTAIR [27]. HOTAIR confers ADM resistance in AML [13]. Meanwhile, miR-378g has been also perceived as a suppressor in many types of cancers [28–30]. Taken together, we conjectured that miR-378g may participate in the ADM resistance of AML by inhibiting malignant progression. This study seeks to propose a novel PAX8-AS1/miR-378g axis-induced lncRNA-miRNA-mRNA regulatory network and investigate the role of this network in the proliferation and apoptosis of ADM-resistant AML cells, so as to provide feasible therapeutic targets for refractory/recurrent AML.
The study has obtained ethic approval from the Ethics Committee of Zhejiang Provincial People's Hospital (approval number: 2021QT323). All the participants enrolled in our research agreed that their tissues would be used for clinical research, and signed the written informed consent.
Bone marrow samples were collected from chemo-sensitive AML patients (n = 23; male: 13, female: 10; 21∼58 years old), refractory/recurrent AML patients (n = 22; male: 10, female: 12; 20∼62 years old), and healthy volunteers (n = 45; male: 25, female: 20; 18∼56 years old), all of whom were enrolled at Zhejiang Provincial People's Hospital in 2020. Inclusion criteria: the patients with refractory/recurrent AML were insensitive to chemotherapy and were pathologically confirmed according to the published criteria [31]. Exclusion criteria: patients with myelodysplastic syndrome, previously known as malignancy; and patients with hepatic and renal insufficiency. After aspiration, the bone marrow samples were instantly preserved at −80°C.
Human AML cell line HL60 and human doxorubicin (ADM)-resistant AML cell line HL60/ADM were obtained as gifts from the Institute of Hematology Affiliated with Chinese Academy of Medical Sciences (Tianjin, China). All the cells were cultured in Dulbecco's modified Eagle's medium (DMEM, A4192101, ThermoFisher, Waltham, Massachusetts, USA) blended with 10% bovine calf serum (BCS, F8687, Sigma‒Aldrich, St. Louis, Missouri, USA) at 37°C with 5% CO2. ADM (D1515) was procured from Sigma‒Aldrich (USA). HL60 or HL60/ADM cells were treated with DMEM containing ADM with gradually increasing concentrations (0, 0.01, 0.03, 0.07, 0.15, 0.3, 0.6, 1.2 and 2.4 µg/mL) at 37°C with 5% CO2 for 24 hours (h) before cell viability determination.
PAX8-AS1 overexpression plasmid was structured using pcDNA3.1 vector (V79520, ThermoFisher, USA). Small interfering RNA targeting PAX8-AS1 (si-PAX8-AS1, sense: 5′-AGTTAAACAAGTTCTTTTCGG-3′, antisense: 5′-GAAAAGAACTTGTTTAACTAA-3′) was synthesized by RIBOBIO (Guangzhou, China). MiR-378g mimic/inhibitor (miR10018937-1-5/miR20018937-1-5) and mimic/inhibitor control (miR1N0000001-1-5/miR2N0000001-1-5) were also purchased from RIBOBIO (China). With the help of Lipofectamine 3000 transfection reagent (L3000015, ThermoFisher, USA), parental HL60 cells were transfected with PAX8-AS1 overexpression plasmid or miR-378g mimic alone or in combination, while HL60/ADM cells were transfected with si-PAX8-AS1 or miR-378g inhibitor alone or in combination. Specifically, HL60 or HL60/ADM cells (3 × 104) were seeded to achieve 90% confluence. Opti-MEM (31985062, ThermoFisher, USA) was used to dilute Lipofectamine 3000 transfection reagent, PAX8-AS1 overexpression plasmid, si-PAX8-AS1, and miR-378g mimic/inhibitor. P3000 reagent was added into gene solutions except for the diluted si-PAX8-AS1. Subsequently, the gene solutions were mixed with the diluted lipofectamine 3000 transfection reagent and incubated at room temperature for 10 minutes (min). Later, the incubated solution, which appeared as the gene-lipid complex, was incubated with the cells at 37°C for 48 h.
CCK-8 reagent (20140419, Beyotime, Beijing, China) was employed to assess the sensitivity of transfected HL60 or HL60/ADM cells to ADM. HL60 and HL60/ADM cells, which were either transfected with or without PAX8-AS1 overexpression plasmid or si-PAX8-AS1 were diluted to 1 × 104 cells/mL and inoculated in 96-well plates (265300, ThermoFisher, USA). The cell solution was sequentially incubated at 37°C overnight to adhere to the wall and treated with ADM at the indicated concentrations for 24 h. CCK-8 reagent was diluted by DMEM at the ratio of 10 : 1. The HL60 or HL60/ADM cells in each well were added with 100 µL of the diluted CCK-8 reagent and incubated at 37°C for 2 h. A spectrophotometer (GENESYS 140/150, ThermoFisher, USA) was used to read the absorbance at 450 nm.
The apoptosis of HL60 or HL60/ADM cells was evaluated via Annexin V-FITC apoptosis detection kit (C1062S, Beyotime, China). Following the transfection as described above or the treatment with ADM at indicated concentration for 24 h, HL60 or HL60/ADM cells (5 × 105) were rinsed with phosphate buffer saline (PBS, P5493, Sigma‒Aldrich, USA), detached using trypsin (T1426, Sigma‒Aldrich, USA) and centrifuged at 1,000 × g for 5 min. Again, the HL60 or HL60/ADM cells were resuspended in PBS and centrifuged at 1,000 × g for 5 min. Subsequently, the HL60 or HL60/ADM cells were resuspended in 195 µL Annexin V-FITC solution, mixed with 5 µL Annexin V-FITC solution, and stained with 10 μL of PI, followed by incubation at 20°C for 20 min without light. CytoFLEX flow cytometer and CytExpert software (ver. 2.2.0.97), both of which were available from Beckman Coulter (Brea, CA, USA) were used to analyze and quantify cell apoptosis.
The Venn diagrams were adopted to screen out the targets of miR-378g from a range of mRNAs, which include AML-associated differentially expressed mRNAs obtained through the analysis of GPL19956 from GSE142700 in the GEO database and include potential miR-378g-targeted mRNAs predicted through Starbase and TargetScan. Then, Starbase (https://www.lncrnablog.com/tag/starbase-v2-0/) and TargetScan (https://www.targetscan.org/mamm_31/) were applied to perform the sequence alignment between PAX8-AS1 and miR-378g and between miR-378g and erb-b2 receptor tyrosine kinase 2 (ERBB2), respectively.
The sequences of wild-type PAX8-AS1 (5′-CACGGGCCCAGCATCCGAGA-3′)/mutant PAX8-AS1 (5′-CACGGGACCAGCAGCCCAGA-3′) and sequences of wild-type ERBB2 (5′-CCTCCTCCTGCCTTCAGCCCAGC-3′)/mutant ERBB2 (5′-CCTCCTCCTGCCTTCATACCCGC-3′) were separately cloned onto pmirGLO vectors (pmirGLO, E1330, Promega, Madison, Wisconsin, USA) to construct the corresponding reporter plasmids. HL60 cells and HL60/ADM cells (3 × 104 cells/well in 96-well plates) were seeded to achieve 70% confluence and were cotransfected with the reporter plasmids and miR-378g mimic/inhibitor or mimic control/inhibitor control using Lipofectamine 3000 transfection reagent for 6 h. 48 hours after the cotransfection, the change of the luciferase activity of the HL60 cells was measured using the dual-luciferase reporter assay system (E1910, Promega, USA). Briefly, following the lysis by Lysis Buffer (16189, ThermoFisher, USA), HL60 cells were added with Luciferase Assay Reagent II and Stop & GLo Reagent to determine the reaction intensities of firefly luciferase and Renilla luciferase in the dark. The ratio of the two reaction intensities was calculated to indicate the expressions of the target genes.
Bone marrow samples were homogenized by a homogenizer (TissueLyser-96, Thunder Sci, Shanghai, China). The total RNA and total miRNA from HL60 cells, HL60/ADM cells, and homogenate of bone marrow samples were extracted using TRIzol lysis buffer (15596018, ThermoFisher, USA) and RNAiso for Small RNA kits (9753Q, TaKaRa, Liaoning, China), respectively. The lysates of RNA or miRNA were added with 200 μL chloroform (48520-U, Sigma‒Aldrich, USA) and centrifuged at 12,000 × g for 15 min at 4°C. 500 μL isopropanol (W292907, Sigma‒Aldrich, USA) was added into the upper water phase, followed by centrifugation at 12,000 × g for 10 min at 4°C. Then, the precipitate of RNA or miRNA was obtained and washed with 1 mL 75% ethanol (32205, Sigma‒Aldrich, USA). After being centrifuged (10,000 × g) at 4°C for 5 min, the precipitate was dissolved in 50 μL nonRNase water (10977023, Sigma‒Aldrich, USA). The purified RNA or miRNA was reversely transcribed into cDNA using RevertAid First Strand cDNA Synthesis Kits (K1621, ThermoFisher, USA). PCR was conducted on a real-time PCR machine (Applied Biosystems, Foster City, CA, USA) and TB Green Premix Ex Taq II (Tli RNaseH Plus) (RR820Q, TAKARA, China), with the indicated conditions as follows: activation (95°C for 10 min) and 40 cycles of denaturation (95°C for 15 seconds (s)), annealing (60°C for 30 s), and extension (60°C for 1 min). The sequences of primers used were listed in Table 1. The relative gene expressions were determined by the 2−ΔΔCT method. The experiment was carried out in triplicate.
The total proteins from HL60 and HL60/ADM cells with or without transfection were extracted using RIPA Buffer (89900, ThermoFisher, USA), following which the concentration of protein sample was quantitated by a BCA kit (A53227, ThermoFisher, USA). 30 μg protein and 4 μL marker (PR1910, Solarbio, Beijing, China) were separately loaded, electrophoresed using 12% SDS-PAGE gel (P0053A, Beyotime, China) for 1 h, and then transferred onto polyvinylidene difluoride (PVDF) membranes (P2438, Sigma‒Aldrich, USA). The membranes were blocked by 5% skimmed milk in Tris-buffered saline with 1% Tween 20 (TBST, TA-125-TT, ThermoFisher, USA) at room temperature for 1 h, and incubated with the following primary antibodies (Abcam, Cambridge, MA, USA) at 4°C overnight, including those against Bcl-2 (ab59348, 26 kDa, 1 : 1000), Bax (ab32503, 21 kDa, 1 : 1000), C Caspase-3 (ab2302, 17 kDa, 1 : 500), ERBB2 (ab237715, 180 kDa, 1 : 1000) and housekeeping control GAPDH (ab8245, 36 kDa, 1 : 10000). Next, the membranes were washed with TBST and cultured with the secondary antibody goat antimouse IgG (A32723, 1 : 1000, ThermorFisher, USA) or goat antirabbit IgG (A32731, 1 : 1000, ThermorFisher, USA) at room temperature for 2 h. The proteins were detected with the help of an enhanced chemiluminescence reagent (WP20005, ThermoFisher, USA) on an imaging System (iBright CL1500A, ThermoFisher, USA). The grey values of the protein bands were quantified using ImageJ (v. 1.52s, National Institutes of Health, Bethesda, MA, USA).
All the results were analyzed using SPSS (v. 12.0, SPSS, Chicago, Illinois, USA), and data from three independent trials were presented as mean ± standard deviation. Comparison of gene expression changes among healthy volunteers, refractory/recurrent patients, and chemo-sensitive patients was performed by independent t-test. Differences between two groups were evaluated by Student's t-test, and those among multiple groups were analyzed using One-Way ANOVA followed by Turkey's posthoc test. All the experiments were repeated in independent triplicate. Statistical significance was defined as two-sided P < 0.05.
Based on the analyses via qRT-PCR, it was evident that PAX8-AS1 expression level was pronouncedly upregulated in AML patients, in comparison with that in the healthy volunteers (P < 0.001, Figure 1(a)), and such upregulation was more notably in refractory/recurrent AML patients than in chemo-sensitive AML patients (P < 0.001, Figure 1(b)). Next, the CCK-8 assay was conducted to determine the sensitivity of AML cells to ADM. As depicted in Figure 1(b), the viability of ADM-resistant HL60 (HL60/ADM) cells was stronger than that of HL60 cells after the treatment of ADM at concentrations of 0.3, 0.6, 1.2, and 2.4 μg/mL (P < 0.05). Then, PAX8-AS1 expression level in HL60/ADM cells and HL60 cells was quantified via qRT-PCR. The relevant results suggested that PAX8-AS1 expression was upregulated in HL60/ADM cells compared to that in parental HL60 cells (P < 0.001, Figure 1(c)). These discoveries collectively demonstrated that the resistance to ADM is associated with a high expression level of PAX8-AS1.
PAX8-AS1 was overexpressed or silenced in HL60/ADM cells and HL60 cells via transfection. After being transfected with PAX8-AS1 overexpression plasmid, HL60 cells exhibited an increased expression level of PAX8-AS1 in comparison with NC-transfected HL60 cells (P < 0.001, Figure 2(a)), and si-PAX8-AS1 transfection induced a decreased expression level of PAX8-AS1 in HL60/ADM cells, relative to siNC transfection (P < 0.001, Figure 2(b)). Then, the CCK-8 assay indicated that PAX8-AS1 upregulation increased the viability of HL60 cells treated with ADM (0.6, 1.2, and 2.4 μg/mL) (P < 0.001, Figure 2(c)), while PAX8-AS1 downregulation decreased the viability of HL60/ADM cells treated with ADM (0.3, 0.6, 1.2 and 2.4 μg/mL) (P < 0.01. Figure 2(d)). Subsequently, the flow cytometry analysis proved that the apoptosis of HL60 cells was inhibited after the overexpression of PAX8-AS1, compared to that of NC-transfected cells (P < 0.001, Figures 2(e) and 2(f)), but the apoptosis of HL60/ADM cells was promoted by PAX8-AS1 silencing, compared to that of siNC-transfected cells (P < 0.001, Figures 2(g) and 2(h)). To further verify the relation between PAX8-AS1 expression and apoptosis, the expressions of apoptosis-related factors were analyzed by Western blot, the result of which revealed that PAX8-AS1 overexpression raised Bcl-2 protein expression while lowering the protein expressions of Bax and C Caspase-3 in HL60 cells (P < 0.01, Figures 3(a) and 3(b)). PAX8-AS1 silencing, however, dwindled Bcl-2 protein expression, but elevated protein expressions of Bax and C Caspase-3 in HL60/ADM cells (P < 0.001, Figures 3(c) and 3(d)). These discoveries reflected that the resistance of AML cells to ADM was attributed to increased viability and inhibited apoptosis caused by PAX8-AS1 overexpression.
Starbase-based analyses identified that PAX8-AS1 had binding sites complementary to miR-378g, which was additionally confirmed by dual-luciferase reporter assay (Figure 4(a)). It was shown that the transfection of miR-378g mimics suppressed the luciferase activity of HL60 cells containing wild-type PAX8-AS1, compared to transfection of mimic control (P < 0.001, Figure 4(b)), whereas the luciferase activity of wild-type PAX8-AS1 was enhanced in HL60/ADM cells after the transfection of miR-378g inhibitor (P < 0.001, Figure 4(c)). Next, miR-378g expression was analyzed in healthy volunteers, chemo-sensitive AML patients, and refractory/recurrent AML patients as well as in HL60 cells and HL60/ADM cells. The relevant analyses via qRT-PCR revealed that miR-378g expression was lower in AML patients than in healthy volunteers (P < 0.001, Figure 4(d)), and miR-378g expression was much lower in refractory/recurrent AML patients and HL60/ADM cells than in chemo-sensitive AML patients and HL60 cells, respectively (P < 0.001, Figures 4(d) and 4(e)). These findings manifested that the resistance of AML patients and AML cells to ADM involves miR-378g downregulation caused by PAX8-AS1 upregulation.
As the abovementioned results confirmed a high PAX8-AS1 expression-related ADM resistance and demonstrated the direct interaction between PAX8-AS1 and miR-378g in AML. Subsequently, miR-378g mimic and inhibitor were used to investigate the role of miR-378g in PAX8-AS1-mediated antiADM-resistant activity in AML cells. Through qRT-PCR analysis, we found that when compared to the NC + MC groups, the expression of miR-378g was decreased in PAX8-AS1 + MC group, while it was increased in the NC + M group (P < 0.001, Figure 5(a)). As expected, miR-378g expression was higher in PAX8-AS1 + M group than that in PAX8-AS1 + MC group, but it was lower than that in NC + M group (P < 0.001, Figure 5(a)). Besides, in HL60/ADM cells, siNC + I group displayed downregulation of miR-378g level but si-PAX8-AS1 + IC group displayed upregulation of miR-378g expression when compared to the siNC + IC groups (P < 0.001, Figure 5(b)), while miR-378g expression was lower in si-PAX8-AS1 + I group than that in si-PAX8-AS1+IC group, but it was higher than that in siNC + I group (P < 0.001, Figure 5(b)). Moreover, the analysis of flow cytometry revealed that PAX8-AS1 overexpression significantly inhibited apoptosis of HL60 cells, but upregulation of miR-378g promoted the apoptosis and partially reversed the suppressive effect of PAX8-AS1 overexpression on the apoptosis of HL60 cells (P < 0.001, Figures 5(c) and 5(e)). Meanwhile, in HL60/ADM cells, silencing of PAX8-AS1 promoted the apoptosis of HL60/ADM cells, but downregulation of miR-378g inhibited the apoptosis and partially reversed the promotive effect of PAX8-AS1 silencing on the apoptosis of HL60/ADM cells (P < 0.001, Figures 5(d) and 5(f)). Furthermore, the expression changes of apoptosis-related factors were analyzed in response to miR-378g mimic/inhibitor. Western blot analyses demonstrated that in contrast to NC + MC group, NC + M group exhibited downregulation of Bcl-2 protein expression, and upregulation of Bax and C Caspase-3 protein expressions, PAX8-AS1+MC group exhibited the upregulated Bcl-2 protein expression yet the downregulated Bax and C Caspase-3 protein expressions (P < 0.001, Figure 6(a)). However, Bcl-2 protein expression was elevated yet Bax and C Caspase-3 protein expressions dwindled in PAX8-AS1 + M group, as compared to those in the NC + M group (P < 0.001, Figure 6(a)). In addition, in HL60/ADM cells, the protein expression level of Bcl-2 was augmented and those of Bax and C Caspase-3 were lessened in siNC + I groups, relative to those in the siNC + IC group (P < 0.001, Figure 6(b)). The protein expression level of Bcl-2 was decreased and those of Bax and C Caspase-3 were increased in si-PAX8-AS1 + IC groups, relative to those in the siNC + IC group (P < 0.001, Figure 6(b)). Bcl-2 protein expression was lowered but Bax and C Caspase-3 expressions were augmented in si-PAX8-AS1 + I group, when compared to those in the siNC + I group (P < 0.001, Figure 6(b)). These discoveries mirrored that the resistance of AML cells to ADM might be attributed to the inhibited apoptosis caused by PAX8-AS1 overexpression-induced miR-378g downregulation.
AML-associated differentially expressed mRNAs were obtained based on the analysis of the GPL19956 dataset from the GSE142700 database in the GEO, which was followed by the selection of mRNAs up-regulated with a fold change absolute value greater than 1. These selected mRNAs are defined as set 1 (Figure 7(a)). Meanwhile, Starbase and TargetScan were used to predict potential miR-378g-targeted mRNAs, which are defined as set 2 and 3. The intersection of the three sets presented fourteen overlapping mRNAs, among which the mRNAs with the five highest scores in TargetScan were selected as subjects (EPOR, CDC25B, GNG12, NOTCH2 and ERBB2) for qRT-PCR analysis (Figure 7(a)). The results of qRT-PCR unveiled that ERBB2 expression was downregulated (or upregulated) the most among the abovementioned five mRNAs after HL60 cells (or HL60/ADM cells) were transfected with miR-378g mimic (or inhibitor) (P < 0.001, Figures 7(b) and 7(c)). Later, the binding sites complementary to ERBB2 on miR-378g were shown through TargetScan-based analysis (Figure 7(d)). Furthermore, validation via dual-luciferase reporter assay displayed that the luciferase activity of HL60 cells containing wild-type ERBB2 was suppressed by transfection with miR-378g mimic (P < 0.001, Figure 7(e)), and the luciferase activity of HL60/AMD cells containing wild-type ERBB2 was promoted by the transfection of miR-378g inhibitor (P < 0.001, Figure 7(f)). Next, ERBB2 expression was analyzed in HL60 cells and HL60/ADM cells. QRT-PCR and Western bot analyses both revealed that HL60/ADM cells exhibited a higher ERBB2 level than HL60 cells (P < 0.001, Figures 7(g) and 7(h)). These data corroborated that the resistance of AML cells to ADM involves activation of the PAX8-AS1-miR-378g-ERBB2 regulatory network.
Poor response to intensive chemotherapy renders AML patients with a particularly gloomy outlook [32]. This poor response is strongly developed mainly due to ABC-induced drug efflux [2] in secondary AML which harbors characteristics such as upregulation of antiapoptotic proteins and MDR proteins [33–36]. Resistance to ADM, which arises from upregulation of the ABC superfamily proteins, results in less accumulation of ADM in AML cells [12], thereby impeding anticancer activities in AML. Therefore, the identification of novel therapeutic targets for ADM resistance is of great importance to decrease chemoresistance and recurrence rate. Accumulating pieces of evidence have documented that lncRNAs are key players in cellular processes including apoptosis through interacting with miRNA/mRNA axis in AML [37, 38]. A prior study has revealed that these lncRNA-mediated regulatory networks are correlated with the development of drug resistance in AML [39]. Our study discovered that lncRNA-PAX8-AS1 participated in the ADM resistance of AML cells via the miR-378g/ERBB2 axis by regulating cell viability and apoptosis. The expression profile screening and bioinformatics analysis have identified dysregulated lncRNAs, some of which can be used to predict clinical outcomes, exist in ADM-resistant cells [40], and strengthen the relation between lncRNAs and ADM resistance in AML. ADM resistance indicates a poor prognosis of refractory/recurrent AML patients [10, 41], and can be aggravated by AML-associated oncogenic genes, such as HOTAIR [13, 42]. PAX8-AS1 regulates PAX8 [20], which is a physiological regulator that causes upregulation of certain oncogenic genes in AML [43]. PAX8-AS1, which has been previously found to be highly expressed in UCEC, plays an oncogenic role in gynecological cancers [26]. Similar to the expression of PAX8-AS1 in UCEC, PAX8-AS1 was discovered in this study to be higher expressed in AML patients compared to that in healthy volunteers, signifying that PAX8-AS1 may function as an oncogene in AML. Meanwhile, PAX8-AS1 overexpression is related to the poor recurrence-free survival (RFS) in UCEC [26] and thyroid cancer [44], suggesting that PAX8-AS1 contributes to disease recurrence in these cancers. Similarly, PAX8-AS1 is an lncRNA whose polymorphisms are risk factors for childhood AML [22]. Based on the findings above, we surmised that PAX8-AS1 exerts an oncogenic effect and confers ADM resistance in AML. In our study, PAX8-AS1 expression was detected to be higher in AML patients. Based on further comparison, we found that the upregulation level of PAX8-AS1 was more pronounced in refractory/recurrent AML patients than in chemo-sensitive AML patients. Following that, the in vitro experiment was conducted with HL60/ADM cells. We found that HL60/ADM cells displayed stronger viability after ADM treatment, which was in accord with the differences between the performances of ADM-resistant THP-1(THP-1/ADM) cells and THP-1 cells subsequent to the ADM treatment [45]. This discovery indicates that HL60/ADM cells are qualified to establish an in vitro drug-resistant AML model. Moreover, as compared to HL60 cells, HL60/ADM cells exhibited highly expressed PAX8-AS1, suggesting a positive relationship between high PAX8-AS1 expression and ADM resistance to AML cells. Yu's study has disclosed that PAX8-AS1 activation reduces cell viability in breast cancer [46]. Contrary to the result caused by PAX8-AS1 activation in Yu's study, our study showed that overexpressed PAX8-AS1 boosted the viability of ADM-treated HL60 cells. More importantly, we detected that PAX8-AS1 silencing led to decreased viability of HL60/ADM cells. Our findings demonstrated that PAX8-AS1 positively regulates AML cell viability to promote ADM resistance in AML. ADM resistance mainly causes apoptosis failure in cytostatic treatment of haemoblastosis, leading to chemoresistance in AML [47]. Zhou's study recorded that PAX8-AS1 positively correlates with the apoptosis of papillary thyroid carcinoma cells [48]. In some way, our results contradict Zhou's finding by demonstrating that PAX8-AS1 overexpression inhibited apoptosis of HL60 cells. Also, we discovered that PAX8-AS1 silencing enhanced apoptosis of HL60/ADM cells. Collectively, our results indicated that PAX8-AS1 expression negatively regulated apoptosis to induce ADM resistance in AML. Meanwhile, chemoresistance-associated apoptosis inhibition is driven by upregulated level of antiapoptotic protein, Bcl-2 [49, 50]. Bcl-2 upregulation impedes the eradication of AML cells during ADM treatment [51]. Besides, Bax activation is also an initial step in apoptosis induction [52], and is found to be released to trigger apoptosis induced by the synergy of ADM plus panobinostat in acute leukemia cells [53]. Upregulation of C Caspase-3, which is essential to initiate and execute the apoptotic process [54], is detected to attenuate ADM resistance in HL60 cells [55]. In our study, the inhibited apoptosis caused by PAX8-AS1 overexpression in HL60 cells was accompanied by the higher expression of Bcl-2 and the lower expressions of Bax and C Caspase-3, and the promoted apoptosis resulted from PAX8-AS1 silencing in HL60/ADM cells was concurrent with the downregulation of Bcl-2 levels and upregulation of Bax and C Caspase-3, which indicated that PAX8-AS1 could affect the result of AML patients through apoptotic mechanism-mediated drug resistance. LncRNAs can impact the drug resistance-related biological processes of AML cells through modulating miRNAs [39]. In our study, we predicted that miR-378g could be a target of PAX8-AS1, which was later validated via dual-luciferase reporter assay. Existing research has revealed that miR-378g is lowly expressed in various kinds of cancers, such as ovarian cancer [30], oral squamous cell carcinoma [29], colon cancer [56], and nasopharyngeal carcinoma (NPC) [57]. Furthermore, miR-378g is discovered to be related to the activation of apoptosis-related signaling pathways in stage II colon cancer [56], and enhanced radiosensitivity of NPC cells [57]. However, the impact of miR-378g on AML remained unknown. Our current study unraveled that miR-378g expression was downregulated in AML patients, and this downregulation was more evident in refractory/recurrent AML patients and HL/60/ADM cells than in chemo-sensitive AML patients and parental HL/60 cells, respectively. Besides, consistent with the proapoptotic role of miR-378g revealed in a previous cancer study [57], our study found that miR-378g was positively related to apoptosis as well as apoptosis-related protein expression changes in both parental HL/60 cells and HL/60/ADM cells, and counteracted the inhibiting effect of PAX8-AS1 on apoptosis of these cells. Furthermore, to figure out the PAX8-AS1-induced lncRNA-miRNA-mRNA regulatory network in drug-resistant AML, three databases including GEO, Starbase, and TargetScan were utilized to predict the target(s) of miR-378g. After validation via dual-luciferase reporter assay, our study proved that ERBB2 was directly targeted by miR-378g. Mutations of ERBB2 as an oncogene are an event with a high incidence rate in numerous tumor types such as the bladder (9.4%), small bowel (7.1%), ampullar (6.5%), and skin nonmelanoma (6.1%) [58]. During chemotherapy against AML, mubritinib, an ERBB2 inhibitor, fulfills a potent antileukemic effect [59]. Our study uncovered a significantly higher ERBB2 expression level in HL/60/ADM cells than in parental HL/60 cells, implicating that inhibiting ERBB2 can be a valid approach to antagonize ADM resistance in AML. However, resistance to mubritinib is still developed in those AML patients bearing highly expressed homeodomain-containing transcription factor HOXA9 and other HOX-network genes [59]. Therefore, our study suggested that ERBB2 inhibition resulting from the binding of ERBB2 to miR-378g may alleviate refractory/recurrent AML in patients without highly expressed HOX-network genes. Furthermore, the study should put more effort to define the effective range within which ERBB2 inhibition can generate an antileukemic effect and find solutions to drug resistance caused by aberrant HOX-network gene expressions in AML. In conclusion, this study discovers the upregulated PAX8-AS1 and the downregulated miR-378g in both in vivo and in vitro samples of ADM-resistant AML when compared to those in chemo-sensitive AML. Besides, this study also demonstrates that PAX8-AS1 expression is negatively associated with cell apoptosis but positively associated with viability in ADM-resistant AML cells via targeting the miR-378g/ERBB2 axis. Collectively, our current study provides a potential regulatory network-based target for antagonizing chemoresistance in AML. | true | true | true |
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PMC9560888 | 36239875 | Ruiting Li,Qin Wang,Kaiqin She,Fang Lu,Yang Yang | CRISPR/Cas systems usher in a new era of disease treatment and diagnosis | 14-10-2022 | CRISPR,Base editing,Prime editing,Gene therapy,Molecular diagnosis | The discovery and development of the CRISPR/Cas system is a milestone in precise medicine. CRISPR/Cas nucleases, base-editing (BE) and prime-editing (PE) are three genome editing technologies derived from CRISPR/Cas. In recent years, CRISPR-based genome editing technologies have created immense therapeutic potential with safe and efficient viral or non-viral delivery systems. Significant progress has been made in applying genome editing strategies to modify T cells and hematopoietic stem cells (HSCs) ex vivo and to treat a wide variety of diseases and disorders in vivo. Nevertheless, the clinical translation of this unique technology still faces many challenges, especially targeting, safety and delivery issues, which require further improvement and optimization. In addition, with the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), CRISPR-based molecular diagnosis has attracted extensive attention. Growing from the specific set of molecular biological discoveries to several active clinical trials, CRISPR/Cas systems offer the opportunity to create a cost-effective, portable and point-of-care diagnosis through nucleic acid screening of diseases. In this review, we describe the development, mechanisms and delivery systems of CRISPR-based genome editing and focus on clinical and preclinical studies of therapeutic CRISPR genome editing in disease treatment as well as its application prospects in therapeutics and molecular detection. | CRISPR/Cas systems usher in a new era of disease treatment and diagnosis
The discovery and development of the CRISPR/Cas system is a milestone in precise medicine. CRISPR/Cas nucleases, base-editing (BE) and prime-editing (PE) are three genome editing technologies derived from CRISPR/Cas. In recent years, CRISPR-based genome editing technologies have created immense therapeutic potential with safe and efficient viral or non-viral delivery systems. Significant progress has been made in applying genome editing strategies to modify T cells and hematopoietic stem cells (HSCs) ex vivo and to treat a wide variety of diseases and disorders in vivo. Nevertheless, the clinical translation of this unique technology still faces many challenges, especially targeting, safety and delivery issues, which require further improvement and optimization. In addition, with the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), CRISPR-based molecular diagnosis has attracted extensive attention. Growing from the specific set of molecular biological discoveries to several active clinical trials, CRISPR/Cas systems offer the opportunity to create a cost-effective, portable and point-of-care diagnosis through nucleic acid screening of diseases. In this review, we describe the development, mechanisms and delivery systems of CRISPR-based genome editing and focus on clinical and preclinical studies of therapeutic CRISPR genome editing in disease treatment as well as its application prospects in therapeutics and molecular detection.
Gene therapy is an approach whereby an “exogenous good gene” is transferred into cells to replace a defective gene in those who suffer from genetic defects [1]. Gene therapy has made remarkable progress in recent years, showing promising clinical results [2]. However, current gene replacement therapy is effective for a part of but precludes utility for other diseases [3, 4]. Genome editing, in contrast, can correct defective DNA in its original location. Therefore, genome editing based on programmable nucleases overcoming the imprecision of current gene therapy is likely to become the next-generation gene therapy technology. At present, there are four major classes of engineered nucleases: meganucleases [5, 6], zinc finger nucleases (ZFNs) [7–9], transcription activator–like effector nucleases (TALENs) [10, 11] and the CRISPR/Cas system [12–14]. Meganucleases, ZFNs and TALENs achieve specific DNA binding via protein-DNA interactions, whereas CRISPR/Cas9 uses simple base-pairing rules between an engineered guide RNA (gRNA) and the target DNA site. CRISPR/Cas9 targets genomic sequences containing protospacer adjacent motifs (PAMs) and complementary to guide RNAs (gRNAs), and generates DSBs [14]. Then, it is taken to the form of either error-prone sequence disruption by non-homologous end joining (NHEJ) or sequence replacement by homology-directed repair (HDR) at the DSB sites to achieve targeted gene disruption, replacement, and modification [15]. CRISPR/Cas9 has been widely used in the research field as well as in disease treatment [16–20]. In recent years, CRISPR/Cas9 has quickly progressed to the clinical stage for the treatment of blood disorders such as β-thalassemia and sickle cell disease, cancer such as metastatic gastrointestinal cancers and metastatic non-small cell lung cancer, eye diseases such as Leber congenital amaurosis (LCA), etc. To achieve the disease mutation correction and avoid the uncontrolled indel outcomes generated by DSBs, DNA base-editing (BE) and prime-editing (PE) have been developed based on Cas proteins. BEs are capable of C·G to T·A or A·T to G·C conversions by the usage of a catalytically impaired Cas protein to direct an adenine or cytidine deaminase to modify the target window of single-stranded DNA [21]. PEs, the latest addition to the CRISPR genome-engineering toolkit, are composed of a reverse transcriptase (RT) fused to the Cas9 nickase and enable replacement or insertion of any desired sequence based on the information encoded in the co-delivered prime editor guide RNA (pegRNA) [22]. Moreover, PE can mediate not only all 12 base-to-base conversions, but also small insertion and deletion mutations as well [22]. Base editors have been proven to correct the largest single class of human disease-causing mutations, transition mutations, which account for 30% of known disease alleles. While prime editors are more multifunctional, they are capable of installing any base-to-base change inserting up to 44 base pairs and deleting up to 80 base pairs. It suggests that, excluding changes involving aneuploidy, chromosomal rearrangement, sizable duplications, insertions, or deletions, prime editors can, in theory, fix > 89% of known human disease-causing mutations [22–24]. Since its emergence in 2012, CRISPR-based genome editing technology has created immense therapeutic potential. For ex vivo research, the modification of T cells and hematopoietic stem cells (HSCs) to treat hematologic disorders [25], viral infections [26] and some refractory cancers [27] are mainly discussed. Since the first autologous CAR therapies targeting CD19 were approved for the treatment of B-cell lymphoma and leukemia in 2019 [28], an increasing number of ex vivo studies have come to clinical trials; for example, CTX001 and CRISPR_SCD001 drug products based on modifying HSCs by CRISPR have been created to cure severe sickle cell disease and are currently in phase 3 clinical trials [29]. Meanwhile, in in vivo studies, the genome editing technology has also been applied to treat a wide variety of diseases and disorders, mainly liver metabolic disorders [30], ocular disorders [31, 32], and neuromuscular disorders [33, 34], some of which have already been in clinical trials, for example, the CRISPR/Cas9-based EDIT-101 drug product for the treatment of LCA10 [32], the EBT-101 drug product for the treatment of HIV-1 infected adults [26], and the NTLA-2001 drug product for the treatment of hereditary transthyretin amyloidosis [35]. Additionally, due to its capacity for precise gene targeting, the CRISPR system has recently attracted increasing attention as a diagnostic tool. C2c2 (also known as Cas13a), Cas12a and Cas9 are currently widely used in DNA or RNA detection [36]. This diagnostic tool is faster and more sensitive for diagnosing various viruses including SARS-CoV-2 [37], Zika virus [38], human papilloma virus (HPV) [39], Dengue virus [40], Japanese encephalitis virus (JEV) [41], and African swine fever virus [42]. Moreover, the high specificity of this diagnostic tool can also help to discriminate various virus strains [38]. In addition to disease treatment and diagnosis, CRISPR has also been found to hold great potential in synthetic gene circuits, which achieve cell programming programs in a reliable and user-defined manner and detect and could be used to treat multiple tumors [43, 44]. Here, we review the mechanisms, prospects, therapeutic applications, and molecular diagnostic applications of CRISPR genome editing as well as the challenges of the novel technology.
CRISPR-Cas RNA-guided nucleases are derived from an adaptive immune system that developed in bacteria to protect them from plasmids and viruses that were invading their environment. Nakata and colleagues identified a cluster of 29 bp repeats downstream of the iap gene located in Escherichia coli (E. coli), found in more than 40% of bacterial species, representing a unique form of clustered repeats in 1987 [45]. Jansen and Mojica referred to these sequences as CRISPR according to their characteristic structure in 2002 [46]. Associated with these repeats are a number of Cas proteins and were classified into three types (types I–III). For types I and III CRISPR, multiple Cas proteins are involved in the recognition and destruction of target genes. The type II system utilizes fewer Cas proteins and works by the function of the single guide RNA (sgRNA) and the single Cas9 endonuclease complex; therefore, it is much simpler to engineer [47–50]. The sgRNA is the combination of the crRNA (CASCADE complex for type I; Cmr or Csm RAMP complexes for type III) and the tracrRNA (transactivating CRISPR RNA) [51]. The Cas9 protein of the Type II CRISPR system is the most widely used for genome engineering due to its precision, and the sgRNA complex interrogates DNA in cells randomly by recognizing the PAM sequence (NGG), a short motif adjacent to the target sequence. Then, the Cas9 protein unwinds the DNA, and the Cas9-associated sgRNA hybridizes with the exposed DNA strand (the protospacer), generating DSBs [50] (Fig. 1a). These breaks are then repaired by the host cell through NHEJ or HDR mechanisms. NHEJ is an efficient but error-prone mechanism that is prevalent and results in small insertions and deletions (indels) at DSB sites. While, HDR is a relatively well-established mechanism with high accuracy during DNA sequence repair [52]. The CRISPR/Cas system represents an efficient genome editing tool after uncontrolled integration into the host genome. Many genome editing methods based on the CRISPR/Cas system for the treatment of diseases have come to clinical trials, and scientists have also developed the CRISPR as an effective tool to detect targeted DNA and RNA. However, the generation of DSBs during the process is still a problem, and more optimized repair mechanisms need to be constructed. Both BE and PE are the newest evolution of CRISPR/Cas-based technologies that correct point mutations in cellular DNA directly without generating DSBs.
DNA BEs comprise a Cas enzyme for binding the targeted DNA sequence and a single-stranded DNA modifying enzyme for altering the targeted nucleotide. Two classes of DNA base-editors have been described thus far: cytosine base-editors (CBEs) convert C·G to T·A [53] and adenine base-editors (ABEs) convert A·T to G·C [54]. Thus, CBEs and ABEs can mediate all four transition mutations of base pairs. In recent years, DNA BEs have also been engineered continually to expand the range of application [55, 56], and a strategy combining CBEs and ABEs has been established to create a dual base-editor system in human cells [57, 58]. To date, CRISPR-guided DNA base editors are widely used for many applications, especially for repairing point mutations [30, 59, 60].
Komor et al. engineered the first-generation cytosine base-editor (CBE1) rAPOBEC1-XTEN-dCas9 by fusing an APOBEC1 cytidine deaminase to dead SpCas9(dCas9) in 2016 [21]. APOBEC1 accepts single-stranded DNA (ssDNA) as a substrate but is incapable of acting on dsDNA, whereas dCas9 contains Asp10Ala and His840Ala mutations that inactivate its nuclease activity. XTEN is a 16 amino acid linker. CBE1 mediates the direct conversion of cytidine to uridine even when located in different sequence motifs and efficiently results in a C·G to T·A transition in vitro (Fig. 1b). The deamination efficiency in vitro is 25–40%; however, in human cells, it decreases to 0.8–7.7% [21]. To inhibit the conversion and improve base-editing efficiency, a uracil DNA glycosylase inhibitor (UGI) was fused to the C-terminus of BE1 to generate a second-generation cytosine base-editor (CBE2), rAPOBEC1-XTEN-dCas9-UGI. UGI is a small protein from bacteriophages that inhibits BER [61], and BE2 increases base editing efficiency in both bacterial and mammalian cells [53]. Subsequently, the third-generation base editor (BE3) rAPOBEC1-XTEN-nCas9-UGI was designed by turning dCas9 to Cas9 nickase (nCas9). Editing efficiency increases threefold by CBE2 and sixfold further by CBE3, while the indel frequencies of CBE2 and CBE3 are 0.1% and 1.1%, respectively, much lower than indels induced by DSBs [53]. Moreover, Kim et al. used Cas9 variants with different PAM specificities to develop a series of deaminase mutants with varying editing window widths to optimize CBEs in 2017 [62]. To constantly increase the therapeutic applications of gene editing, further optimization of CBEs was still performed [63–67].
There are six kinds of pathogenic point mutations in living systems with different frequencies, among which the cytosine deamination rate is close to half, resulting in the C·G to T·A mutation [68–70]. Therefore, a new class of ABEs is required to expand the convert range of CBEs from installing C·G to T·A mutation to convert the A·T base pair back into a G·C base pair (Fig. 1c). ABEs operate a similar mechanism to CBEs; similar to cytosine, adenine alters its base pairing preferences by deaminating the exocyclic amine it contains and then yields inosine. Inosine located in the third position of the tRNA anticodon prefers to pair with A, U, or C in mRNA during translation, but it prefers to match with G when the polymerase active site exists [71]. The major block is that unlike cytosine deaminase, adenosine deaminase acting on ssDNA does not exist in nature. RNA adenosine deaminase is utilized to act on DNA, installed in APOBEC1 of BE3, but no efficiency of adenine base editing was detected [54]. Gaudelli et al. overcame this problem by evolving a tRNA adenosine deaminase of E. coli (ecTadA) to manipulate DNA. To obtain the directed evolution and aiming TadA mutants, an antibiotic resistance complementation approach was employed. E. coli cells were equipped with TadA mutants and defective antibiotic resistance genes, and the mutant TadA-dCa9 fusion had to correct a deoxyadenosine to a deoxyinosine to realize growth in the presence of antibiotics. The mutant gene of bacteria encoding TadA-dCas9 fusions (TadA*-dCas9) capable of repairing mutant resistance was isolated and then used to develop the first-generation ABEs [54]. The editing rates through simple TadA*-Cas9 nickase fusions are quite low; thus, a single polypeptide chain involving a wild-type noncatalytic TadA monomer, an evolved TadA* monomer and a Cas9 nickase (TadA-TadA*-Cas9 nickase) was designed to optimize ABEs. Moreover, Seventh-generation ABEs were successfully converted from target A-T to G-C (50%) in human cells by extensive protein engineering and controlled evolution [54]. Compared to CBEs, ABEs enable precise conversion of a target A·T to G·C in DNA and yield a much cleaner product (typically ≥ 99.9%) with almost no indels (typically ≤ 0.1%) [54, 72, 73]. Nevertheless, ABEs almost can only match SpCas9, which is different from the broad compatibility of CBEs [74]. To ameliorate this problem, the deaminase component of ABE7.10 was evolved by Richter et al. in 2020 using phage-assisted noncontinuous and continuous evolution (PANCE and PACE)-engineered ABE8e, which increased the function of ABEs and provided higher editing efficiencies when combined with a variety of Cas9 or Cas12 homologs [75]. CBEs and ABEs mediate targeted single-nucleotide conversions without requiring DSBs, minimizing undesired consequences of editing such as indels, large deletions, translocations or other chromosomal abnormalities. On this basis, researchers have focused on developing BEs into a novel therapeutic strategy and have applied BEs to the treatment of some diseases in mice and nonhuman primates [30, 76–85], which we summarized in the last part of this review.
CBEs and ABEs can install the four transition mutations (C·G to T·A, A·T to G·C) without DSBs in many cells and organisms, but fail to perform the other eight transversion mutations, such as C·G to G·C, C·G to A·T, A·T to T·A and A·T to C·G [22], which may cause some molecular diseases [86–88]. In 2019, Anzalone et al. described the invention of PE, a gene editing technique that can mediate targeted indels and all 12 base-to-base conversions in mammalian cells, without the need for donor DNA templates or double-strand breaks [22]. PE is composed of an RT fused to Cas9 nickase and a pegRNA. The pegRNA plays a major role in the PE system. On the one hand, by containing the complementary sequence to the target sites that drive nCas9 to its target sequence, it is able to specify the DNA target. On the other hand, it contains an additional sequence enabling to spell the desired sequence changes and bring new genetic information to replace target DNA nucleotides (Fig. 1d). The 5’ end of the pegRNA binds to the primer binding site (PBS) region at the 3′ end of the target DNA strand, exposing the noncomplimentary strand and forming a primer-template complex, while the 3’ end of the pegRNA encodes the desired edit. Upon binding to the target, Cas9 nicks the PAM-containing unbound DNA strand and then primes reverse transcription with the extension in the pegRNA as a template to modify the target region. The reverse transcription template contains the desired DNA sequence changes and the homologous region of the target site to facilitate DNA repair. Subsequently, the edited DNA is newly synthesized with an original DNA sequence containing the 5′ flap without being edited. The 5′ flap is excised, and the 3′ flap is incorporated into the target site by cellular DNA repair processes, generating one edited and one unedited strand of heteroduplex DNA (Fig. 1d). Finally, an additional nick promoted by a simple sgRNA cuts off the unedited strand, resulting in full editing of the dsDNA [89]. Three major versions of the PE system have been developed thus far. PE1 used a wild-type moloney murine leukemia virus (M-MLV) RT fused to a Cas9 nickase and pegRNA, with a maximum editing efficiency of 0.7–5.5%. To optimize PE1, an engineered pentamutant M-MLV RT was used to substitute the wild-type M-MLV RT and created PE2, which increased the editing efficiency approximately threefold. PE3 nicked the unedited strand with an additional sgRNA and enabled 20–50% editing efficiency with 1–10% indels in human HEK293T cells [89, 90]. PEs enable precise targeted indels, and all 12 kinds of point mutations without DSBs or donor DNA templates, result in lower off-target activity, fewer byproducts, and higher editing efficiency. Prime editing is an enormous milestone in the development of gene editing and has an immense potential in clinical applications.
Efficient and safe gene delivery to target cells and tissues in the human body is one of the most crucial factors and processive challenges for successful therapeutic CRISPR genome editing. First, components including nucleases, the CRISPR/Cas9 systems and the gRNAs need to be delivered efficiently. In addition, the efficiency of homologous recombination, the duration and magnitude of nuclease expression are critical. Moreover, DNA-related cytotoxicity must be low. The present delivery systems of gene editing are classified as viral delivery systems and non-viral delivery systems [91]. There are three major classes of viral delivery systems: adenoviral vector, adeno-associated viral vector (AAV) and lentiviral vector [92] (Fig. 2). Viral gene therapy is an attractive but controversial method in transgenic vectors. It has built successful gene therapy approaches with high delivery efficiencies in multiple disease models in vivo, while the limitation of its capacity is still a problem [93]. Non-viral vectors are divided into naked DNA, particle-based and chemical-based vectors [94], and many non-viral gene therapy systems based on liposomes, polymers and nanoparticles have already come into clinical trials [95].
Adenoviral vectors, AAV and lentiviral vectors are three major classes of viral delivery systems (Fig. 2). Adenoviruses, a group of DNA viruses with double-stranded genomes between 34 and 43 kb, use alternative splicing to encode genes in both sense and antisense directions [96] (Fig. 2). Being an unintegrated virus, it can cause infected differentiated and non-dividing cells to create a significant amount of recombinant virus. Natural adenoviruses have the tendency to transduce pulmonary epithelial cells; thus, human adenoviruses were first used to treat cystic fibrosis [97]. To extend the ability of adenovirus, certain essential viral genes were deleted and replaced with therapeutic elements that express exogenous therapeutic genes, and then the engineered adenovirus vectors used for gene therapy, vaccines, and cancer therapy were obtained [98]. Adenovirus vectors are currently the most commonly employed vectors for cancer gene therapy, for instance, the use of adenoviruses targeting the SERPINA1 gene in hepatocytes to rescue the pathological liver phenotype in a mouse model of α1-antitrypsin deficiency [99]. AAV is a small and nonpathogenic parvovirus composed of a 4.7 kb ssDNA genome within a nonenveloped icosahedral capsid. The wild-type AAV belongs to the Parvoviridae family and is not able to automatically replicate unless the adenovirus exists [100]. AAV can infect mammals but remains inactive without integrating into the genome of the host and thus has no genotoxic effect. Furthermore, although a small portion of humans are AAV seropositive, AAV capsids have a lower systemic inflammatory response than adenoviruses [101, 102]. The genome of AAV contains three open reading frames (ORFs) (rep, cap, aap) flanked by ITRs. In recombinant AAV vectors, A therapeutic transgene linked to promoter and polyadenylation sequences is placed between the viral ITRs in place of rep and cap (Fig. 2). The AAV variants are abundant; there are 11 natural serotypes and more than 100 variants of engineered AAV with diverse amino acid sequences and gene delivery properties [103]. AAV was first adapted as a mammalian DNA cloning vector almost 40 years ago [104] and benefited from the non-genotoxicity and low immunogenicity. AAV has gradually been considered as the most promising method for gene therapy delivery systems. Glybera, the first gene therapy product approved in Europe for patients with lipoprotein lipase deficiency in 2012, was based on an AAV gene delivery system [105–107]. In recent years, various AAV vector-mediated gene therapies have produced clinical benefits, for example, the treatment of various eye diseases [108, 109] and spinal muscular atrophy [100, 110], as well as some rare diseases, including hemophilia and Duchenne muscular dystrophy [111–113]. In fact, further modification is also required to optimize the capacity, transduction efficiency, and immune response of AAV to facilitate the success of AAV gene therapy. Lentiviruses are a subclass of retroviruses based on HIV and other nonhuman lentiviruses, which are single-stranded RNA (ssRNA) viruses and can integrate viral DNA into the genome of targeted cells. Replication of retroviruses has a deontic step: RNA copies into DNA and then integrates into the genome of the host cell. Two copies of positive-strand RNA with three genes are packaged by lentiviruses: gag (encoding structural proteins), pol (encoding RT, integrase, and protease enzymes that are packaged with the RNA strands inside the virus), and env (encoding envelope proteins that coat the virus), while accessory protein genes are flanked by the long terminal repeat (LTR) that also functions as a promoter sequence (Fig. 2). As vectors, lentiviral vectors (LVs) are capable of delivering transgenes up to 8 kb in size and transducing dividing as well as non-dividing cells such as neurons, hematopoietic stem cells and T cells. LVs represent a major vector for the treatment of monogenic diseases and adoptive cell therapy trials where gene delivery is required [114]. For genetic components of LVs, the therapeutic transgene is inserted between the viral LTRs, and the three genes gag, pol, and env are the essential elements of the production of LVs [115]. Retroviruses were the only practicable method to modify patients’ genes before the discovery of CRISPR-Cas systems [101]. In the early 1990s, the first clinical trial of gene therapy for genetic diseases was started using retroviral-mediated transfer of the adenosine deaminase gene into T cells to cure the severe combined immunodeficiency caused by the lack of adenosine-deaminase [116, 117]. Naldini et al. created an in vivo lentiviral gene delivery system and achieved stable transduction of nondividing cells through LVs in 1996 [118]. Currently, LVs are widely used in laboratory and clinical gene therapy applications [119–121], especially most used for ex vivo gene transduction, due to their capacity to integrate transgenes into the genome of the host cell and to infect both proliferating and nondividing cells [122], with relatively large packaging capacity and low immunogenicity [123].
Using a viral delivery system to deliver therapeutic components is the most widely used approach thus far. However, it also brings some risks including increasing the frequency of off-target editing [124] and relatively increasing the possibility of oncogenesis caused by the integration of viral vectors into the genome of targeted cells [92]. Compared to viral delivery systems, non-viral delivery systems have less gene delivery efficiency, but have lower immune responses, less insertional mutagenesis, greater capacity and lower costs [94, 95, 125]. As is known, the non-viral vectors are divided into naked DNA, particle-based and chemical-based vectors [94]. Due to the advantages of the non-viral delivery system, a large number of research efforts and advancements have brought nanoparticle-based, lipid-based and polyplexes-based non-viral gene delivery vectors into the clinic [95]. Liposomes are spherical delivery systems with hydrophilic polar head groups and hydrophobic tails that are effective at encasing both water-soluble and water-insoluble substances within their hydrophilic core and lipid membrane, respectively [126]. Lipid nanoparticles (LNPs) were explored in 1999 using stabilized plasmid lipid particles through a detergent dialysis method [127], which are quite different from classical liposomes, especially LNPs that do not display a lipid bilayer surrounding the aqueous core [128]. In 2018, Onpattro, the production of LNPs for the treatment of amyloidosis was approved in the US and EU, which confirmed its ability to deliver nucleic acid drugs [129]. A delivery system containing cationic polymers has been approved, which has the advantages of formulating smaller uniform particle sizes and improving transfection efficiency [130]. Recently, a novel non-viral delivery system named engineered virus-like particle (eVLPs) vector was created by David Liu's group [131]. The VLP vector is composed of infectious viral proteins but lacks viral genetic material, and has been engineered to efficiently deliver therapeutic protein RNPs including BEs and Cas9 nuclease, in vivo. The efficient packaging and delivery of RNPs overcome the problems of cargo packaging, release, and localization. Moreover, compared with the longer time that DNA is present in target cells, the existence of RNP is quite short, which reduces the frequencies of off-target editing.
CRISPR-based genome editing is able to precisely modify any genomic sequence, and this feature creates immense therapeutic potential. Next, we focus on the ongoing clinical strategies using both ex vivo and in vivo strategies for major categories of disease treatment by therapeutic CRISPR gene editing (Fig. 3).
The strategy of altering genes in autologous cells ex vivo is the most straightforward application of gene editing (Table 1). In this process, somatic cells are isolated first, modified by gene editing tools, and finally delivered back to the patients’ organs (Fig. 3).
Gene therapy of autologous hematopoietic stem cells (HSCs) with integrating vectors has the potential to cure many inherited disorders, especially diseases of the blood system and immune deficiencies. The first clinical application of HSC gene therapy was applied to the most severe immunological defects called primary immunodeficiencies (PIDs). PIDs are a large group of diseases, and four of the most extensively studied PIDs are X-linked severe combined immunodeficiency (SCID-X), adenosine deaminase deficiency (ADA-SCID), Wiskott-Aldrich syndrome (WAS), and chronic granulomatous disease (CGD). The hematopoietic system of PIDs is intrinsic, making them the ideal target for allogeneic hematopoietic stem cell transplantation (alloHSCT) [132]. With the discovery of retroviruses, the first HSC gene therapy trials for SCID-X1 and ADA-SCID were conducted [133–136]. Then, the CRISPR/Cas9 system was used to repair mutations in the CYBB gene of CD34+ HSCs from patients with the immunodeficiency disorder CGD [137, 138]. In addition, with the help of AAV, the CRISPR/Cas9 system also achieved homologous recombination of the β-globin gene in HSCs to cure red blood cell disorders [139]. In recent years, CRISPR/Cas9-based CRISPR_SCD001 and GPH101 drug products have been undergoing clinical trials (ClinicalTrials.gov Identifier: NCT04774536, CT04819841). They are CRISPR/Cas9 edited red blood cells designed for a single infusion of differentiated CD34 + hematopoietic stem cells (HSPCs) modified by the sickle allele in patients with severe sickle cell disease (SCD), and are currently evaluating HSCT safety and efficacy.
Another advanced ex vivo gene editing strategy is the modification of T cells, especially the treatment of primary HIV infection by knocking out the CCR5 coreceptor. In an earlier study, researchers knocked out the CCR5 gene of T cells via ZFNs and then engrafted the corrected T cells into HIV-infected mice, successfully decreasing viral loads and increasing CD4+ T cell numbers [140]. In addition to ZFNs, similar gene-editing strategies to knock out CCR5 with TALENs [141, 142], CRISPR/Cas9 [26, 142, 143], and meganucleases [144] have been developed recently. In 2020, three patients with refractory cancer participated in the first-in-human phase 1 clinical trial testing the viability and safety of multiplex CRISPR/Cas9 editing to generate T cells, and patients performed to improve antitumor immunity within the modified T cells persisted for up to 9 months (ClinicalTrials.gov Identifier: NCT03399448) [145]. Furthermore, ex vivo T cells modified to express chimeric antigen receptors (CAR-T) and recombinant T-cell receptors (rTCRαβ) are feasible for cancer immunotherapy [146]. In 2019, the first autologous CAR product targeting CD19 obtained approval for marketing to treat B-cell-derived lymphoma and leukemia [28]. However, a subset of patients who accepted CD19-directed CAR-T-cell therapy for the treatment of relapsed or refractory B-cell malignancies suffered the relapse due to the loss of CD19 in tumor cells or were unable to receive this highly active therapy because of failed expansion. Moreover, infantile cancer patients have a small blood volume, and it is a challenge to manufacture an effective therapeutic product for them. Personalized autologous T cell manufacturing is the inherent characteristic of autologous CAR-T cell therapy, resulting in the difficulty of industrialization of autologous CAR-T cell therapy. One of the improved methods is using dual specificity CD19 and CD20 or CD22 CAR-T cells to recognize and kill CD19-negative malignant cells by recognizing CD20 or CD22 and then achieve immunotherapy for relapsed or refractory leukemia and lymphoma (ClinicalTrials.gov Identifier: NCT03398967). Another optimized method is to combine the CAR-T and CRISPR mRNA electroporation to disrupt endogenous TCR and B2M genes simultaneously by LVs. This method generates universal CD19-specific CAR-T cells (UCART019) derived from one or more healthy unrelated donors without graft-versus-host-disease (GVHD) and minimizes their immunogenicity; currently, it is in progress of a phase 2 clinical trial (ClinicalTrials.gov Identifier: NCT03166878). Additionally, the NTLA-5001 as a T-cell receptor engineered T (TCR-T) cells directed drug based on CRISPR/Cas9 was also assessed in a clinical trial to investigate the safety and efficacy in subjects with acute myeloid leukemia (ClinicalTrials.gov Identifier: NCT05066165). To date, there have been various clinical trials using CRISPR systems to modify human T cells and have a great chance of curing many refractory diseases. For example, CRISPR/Cas9 mediated PD-1 knockout T cells from autologous origin for advanced Epstein-Barr virus (EBV)-associated malignancies (ClinicalTrials.gov Identifier: NCT03044743), genetically engineered T cell therapy for solid tumors in the setting of novel checkpoint inhibition to treat metastatic gastrointestinal cancers (ClinicalTrials.gov Identifier: NCT04426669), the BD111 drug product for the treatment of refractory viral keratitis (ClinicalTrials.gov Identifier: NCT04560790) and so on. COVID-19 is a worldwide pandemic. It has been reported that in patients infected with SARS-CoV-2, the PD-1 and Tim-3 expression on the surface of T cells was increased significantly, which was directly related to the disease's severity and was also increased in other viral infections. Using CRISPR/Cas9 to knock out PD-1 and ACE2 to modify human T cells and achieve the induction of long-term immunity in COVID-19 patients is a potential and effective method to cure the infectious disease. In this clinical trial, exhausted virus-reactive CD8+ memory T cells will be collected and both the programmed cell death protein 1(PDCD1) gene and ACE2 gene will be knocked out by CRISPR/Cas9 in the laboratory. Then the lymphocytes will be selected and expanded ex vivo, and reinfused into patients (ClinicalTrials.gov Identifier: NCT04990557). In addition to gene editing of T cells, some other clinical trials are also underway utilizing CRISPR/Cas9 with AAV vectors or LVs as the delivery system to modify B cells for the treatment of refractory B cell malignancies (ClinicalTrials.gov Identifier: NCT04035434, NCT04557436) (Table 1).
Gene editing in vivo is a large-extended strategy for targeted gene correction in tissues, as cell transplantation presents obstacles under certain conditions. To achieve gene editing in vivo, the effective delivery of gene-editing nucleases and donor vectors to target tissues, low off-target frequencies, and low genotoxic effects are all required (Fig. 3). Initially, highly effective nuclease-mediated gene editing in vivo was demonstrated in a study, that delivered ZFNs and a factor IX cDNA to the liver of a promoter-free animal model of hemophilia B by AAV vector [147]. Later, an increasing number of in vivo gene editing studies with various therapeutic strategies for multiple diseases were conducted, especially CRISPR-based genome editing. Here, therapeutic in vivo gene editing is discussed by the classification of tissues with representative diseases (Table 2).
Many different types of liver diseases have the potential to be treated by gene correction, including metabolic liver diseases, viral hepatitis and hepatocellular carcinoma (HCC). Metabolic liver diseases mainly include clotting disorders (hemophilia A and hemophilia B), hereditary tyrosinemia, lysosomal storage disorders (Fabry disease, Gaucher disease, Pompe disease, von Gierke disease), and ornithine transcarbamylase deficiency (OTCD) (Table 2). Among them, hemophilia is caused by factor VIII (FVIII) or factor IX (FIX) mutations in the clotting factor genes, which disrupt the clotting pathway. Metabolic liver diseases are among the best candidates for genome editing therapeutic strategies, as many of them are too severe to be treated with drugs and require orthotopic liver transplantations. Gene editing has become a potential method to correct the metabolic liver disease phenotype, some of which have obtained significant effects [148, 149]. Since 2011, nuclease-mediated gene editing in vivo has been used to ameliorate hemophilia B in infants by delivering ZFNs and a factor IX cDNA using AAV vectors [147] and was later demonstrated to be effective in adult mice [150]. In addition to ZFNs, CRISPR/Cas9-mediated gene correction was created and later ameliorated hemophilia in mice [151, 152]. Another metabolic genetic disorder named hereditary tyrosinemia type I (HTI) is caused by a mutation in fumarylacetoacetate hydrolase (FAH), resulting in toxic metabolite accumulation. In 2014, CRISPR/Cas9 was used for the first time to correct the HTI in a mouse model following hydrodynamic tail vein injection of plasmid DNA, which allowed the corrected cells to repopulate the liver successfully [153]. Later, therapeutic strategies based on CRISPR/Cas9 were optimized continuously. In 2016, instead of editing the disease-causing gene, a disease-associated pathway gene named Hpd was deleted using CRISPR/Cas9 and successfully rerouted tyrosine catabolism in some mice [149]. In the same year, using LNP-mediated delivery of Cas9 mRNA with AAV encoding a sgRNA and a repair template to induce the generation of FAH-positive hepatocytes by correcting the causative Fah-splicing mutation also successfully redeemed disease symptoms such as weight loss and liver damage [154]. Later, an improved Cas9n was engineered to reduce the numerous undesired mutations caused by wild-type Cas9, and the Cas9n-mediated genome editing in treating HTI suggested a safer and optimized therapeutic CRISPR genome editing strategy [148]. Recently, BEs were constructed and greatly extended the CRISPR/Cas9 system; the plasmid DNA encoding the ABE and sgRNA corrected an A > G splice-site mutation, and this treatment successfully relieved the symptoms of HTI [84]. Researchers also used BE to correct genetic point mutations by AAV in neonatal phenylketonuria (PKU) mice in 2022 [30, 85]. LNP-based delivery of mRNA encoding ABE and sgRNA targeting PCSK9 has been proven to reduce the blood low-density lipoprotein (LDL) levels efficiently and safely [81]. As a novel gene editing tool, BE has great therapeutic potential. Other liver metabolism diseases including lysosomal storage disorders and OTCD have also been successfully treated in animal models by in vivo gene editing [155, 156] (Table 2). Hepatitis B virus (HBV) is a type of viral hepatitis, and its high infection rate makes it one of the most affected diseases in the world. Vaccines have been the most effective prevention and treatment strategy until now but can only inhibit HBV replication while cannot eliminate the covalently closed circular DNA (cccDNA) of HBV still carried in the hepatocyte nucleus [157, 158]. Therefore, using CRISPR/Cas9 to specifically target and disrupt the cccDNA of HBV has become an attractive and novel strategy to cure chronic hepatitis B [158–161]. In 2014, Lin et al. designed a CRISPR/Cas9 system with HBV-specific gRNAs that significantly decreased the production of HBV core and surface proteins in Huh-7 cells transfected with an HBV expression vector in the mouse model [159]. Furthermore, targeting the ORFs S and X of HBV by CRISPR/Cas9 reduced the serum surface-antigen levels and inactivated HBV in chronically and de novo infected cells to some extent [162, 163]. DNA polymerase κ (POLK), a Y-family DNA polymerase that significantly contributes to the formation of cccDNA during de novo HBV infection, is most active in non-dividing cells. Thus, the expression of POLK in HepG2-NTCP cells can be depleted by siRNA and CRISPR/Cas9 to inhibit the conversion of rcDNA into cccDNA [164]. Recently, after the SaCas9 and S gene targeting gRNA were introduced into HepG2.2.15 cells by single stranded adeno-associated viral vectors (ssAAVs), targeted mutation of HBV DNA was observed, indicating that the inactivation of cccDNA was successful [160]. Hepatitis C virus (HCV) is another kind of widespread chronic hepatitis. A study showed that Francisella novicida Cas9 endonuclease (FnCas9) directed by an engineered gRNA is capable of inhibiting HCV within eukaryotic cells [165]. The ability to precisely mediate gene KO in numerous cell types makes CRISPR/Cas9 a potential technique for the treatment of multiple cancers, such as HCC. CRISPR/Cas9 can precisely target many tumor-associated genes, including the tumor-promoting genes G9a, ASPH, eEF2, NCOA5, CXCR4 and CDK7, and the tumor-suppressing genes p53 and PTEN [166–171]. G9a is an important epigenetic regulator. As a histone methyltransferase, it is associated with the occurrence and development of human hepatocellular carcinoma. The poor prognosis in HCC is indicated by the upregulation of G9a. Inactivation of G9a by RNAi knockdown and CRISPR/Cas9 knockout can suppress the progression of HCC cells in vitro and inhibit HCC tumorigenicity in vivo [166]. ASPH, aspartate β-hydroxylase, an enzyme involved in the malignant transformation process, is overexpressed in HCC tumors. ASPH knockout was achieved by the CRISPR/Cas9 system and decreased HCC growth and progression, suggesting that ASPH enzymatic activity is a novel therapeutic target mediated by CRISPR/Cas9 for HCC [170]. eEF2, eukaryotic elongation factor 2, is a prognostic marker which kinase is a potential therapeutic target in HCC. Compared with non-tumorous tissue, the activity of the regulating eEF2 kinase in tumors is more than four times higher, while proliferation and growth are decreased in CRISPR/Cas9-mediated eEF2 kinase knockout HCC cells [167]. NCOA5, a nuclear receptor coactivator, performs critical roles in the emergence of numerous cancers, and CRISPR/Cas9 deletion of NCOA5 reduces hepatocellular carcinoma cell migration and proliferation by preventing the epithelial-to-mesenchymal transition [168]. CXCR4, CXC chemokine receptor 4, is linked to poor clinical outcomes and a decreased survival rate in HCC. Utilizing the CRISPR/Cas9 system to mediate genome engineering of CXCR4 can decrease the malignancy of hepatocellular carcinoma cells in vitro and in vivo [169]. CDKs, cyclin-dependent kinases, regulate the gene transcription of HCCA, and a CRISPR screen identified CDK7 as a therapeutic target for HCC [171].
Therapeutic CRISPR/Cas genome editing technology has been rapidly developed in treatments of ocular disorders since its discovery in 2012, and now the EDIT-101 drug product based on CRISPR/Cas system with SaCas9 gRNAs has been developed for the treatment of LCA10 [32] (ClinicalTrials.gov Identifier: NCT03872479). The LCA, retinitis pigmentosa (RP), proliferative diabetic retinopathy (PDR), wet age-related macular degeneration (wAMD), corneal dystrophy (CD) and optic nerve (ON) diseases are six classes of ocular disorders that have advantages in gene editing treatments. LCA is a part of the spectrum of early-onset retinal dystrophy (EORD). LCA10 is the most prevalent subtype of LCA, a severe retinal degeneration caused by mutations in the CEP290 gene. Gene therapy clinical trials for treating LCA2 by subretinal injection of AAV encoding the full RPE65 gene have shown great success in terms of both safety and efficiency [172, 173]. However, the large size of the CEP290 gene limits the loading capacity of the full length gene, and the CRISPR/Cas9 system has been developed to optimize the strategy [174]. A therapeutic genome-editing candidate EDIT-101 with SaCas9 gRNAs has also been developed for the treatment of LCA10 [32] (ClinicalTrials.gov Identifier: NCT03872479). In 2019, Boye's group finished the first in vivo CRISPR genome editing in the retina of the nonhuman primate macaque. SaCas9 delivered by AAV5, together with a sgRNA targeting GUCY2D, reduced the expression of retinal guanylate cyclase-1 (retGC1) and improved the retinal function and structure. GUCY2D is the gene encoding retGC1, and mutations in this gene lead to autosomal dominant cone-rod dystrophy (CORD6) and cause LCA1 [175]. CBEs and ABEs can correct point mutations precisely, and the subretinal injection of an LV expressing an ABE and a sgRNA targeting the de novo nonsense mutation in the Rpe65 gene can correct the pathogenic mutation with an efficiency of 29%. The formation of indel and off-target mutations minimally restores RPE65 expression and improves the retina in many aspects in ABE-treated mice [82]. In addition to LCA, RP is another large category of ocular disorders caused by the mutation of the rhodopsin (RHO), NRL, Pde6b or other genes, leading to rod photoreceptor degeneration that invariably causes vision loss. P23H is the most common mutation in the RHO gene. To inactivate the RHO-P23H mutant, an AAV9-based CRISPR/Cas9 delivery strategy was used, and the phenotypes and functions of the retina were successfully improved [31]. In the same year, researchers utilized both SpCas9 variants and truncated sgRNAs to discriminate a single-nucleotide mutation in RHO-P23H mice, and in treated areas of the RHO-P23H retina at 5 weeks of age, the rate of photoreceptor cell degeneration in the outer nuclear layer was significantly delayed [176]. Nevertheless, further optimization is still required because not every mutation in the RHO gene can find a proper CRISPR design; thus, it is necessary to develop a novel gene editing strategy to overcome the genetic heterogeneity in RP resulting from mutations in RHO. An optimized experimental study combining both gene ablation and gene replacement destroys the expression of endogenous RHO gene in a mutation-independent manner via an improved CRISPR-based gene deletion delivered by AAV. The expression of wild-type protein was restored via exogenous cDNA, and the thickness of the outer nuclear layer and the results of electroretinography improved significantly after the subretinal injection of combination ablate-and-replace gene therapy [177]. The NRL gene encodes neural retina-specific leucine zipper protein, which determines the photoreceptor development and is associated with RP. Using AAV-mediated CRISPR/Cas9 delivery to postmitotic photoreceptors to target and disrupt NRL in rods, following the treatment, rods gained partial features of cones and presented with improved survival in the presence of mutations in rod-specific genes, consequently preventing secondary cone degeneration [178, 179]. In another study, instead of disrupting the NRL gene for the transformation of rods to cone-like cells, a CRISPRi technique was adopted to repress NRL gene expression, and downregulation of NRL in the Rd10 mouse photoreceptors was achieved in vivo. The CRISPRi system includes a dCas9 that is fused with a gene repressor protein such as KRAB, the dCas9/repressor complex results in sequence-specific gene repression with the guidance of sgRNA [180]. Mutations in the Pde6b gene also result in RP, and the Pde6b gene regulates intracellular cGMP levels. Researchers used CRISPR/Cas genome editing to untangle the effects of two potentially pathogenic genetic differences [181] and attempted to repair causative mutations in a preclinical model of RP [31, 182]. Ocular angiogenesis is associated with a variety of human diseases, including PDR and AMD, in which vascular endothelial growth factor receptor 2 (VEGFR2) plays an essential role. Using the CRISPR/Cas9 system with AAV to deplete VEGFR2 in vascular endothelial cells (ECs) provided more opportunities to suppress angiogenesis in mouse models of oxygen-induced retinopathy and laser-induced choroid neovascularization [183, 184] (Table 3). Specifically, using AAV9-delivered CjCas9 to target the VEGFA or HIFLA gene in RPE cells can reduce the size of laser-induced choroidal neovascularization, indicating that in vivo CjCas9-based genome editing is useful for the treatment of wAMD [185]. LV-delivered CRISPR is also able to disrupt the VEGFA gene efficiently [186]. Meesmann's epithelial corneal dystrophy (MECD) is an autosomal dominant disease caused by mutations in the KRT12 gene, which leads to the occurrence of a novel PAM. Researchers designed a CRISPR against mutant single-nucleotide polymorphisms (SNPs) within KRT12 and intrastromal injection was used to deliver the plasmids encoding the CRISPR components to the cornea of a humanized MECD mouse model, successfully editing the mutant KRT12 allele without any off-target effects in the wild-type allele [193]. Another corneal dystrophy named transforming growth factorβ-induced (TGFBI) corneal dystrophy is also a model of autosomal dominant disease that is used to evaluate the effectiveness of CRISPR/Cas9 in two allele-specific systems, contrasting guide-specific cleavage with SNP-derived PAM cleavage [194]. These studies evaluated novel approaches for targeting heterozygous SNPs using CRISPR/Cas9. In addition, optic neuropathies are a group of ON diseases that cause irreversible blindness and are characterized by retinal ganglion cell (RGC) death and ON degeneration. Combining the AAV-mSncg promoter with CRISPR/Cas9 gene editing can knockdown pro-degenerative genes in RGCs and effectively provide neuroprotection in optic neuropathies [192].
Neuromuscular disorders mainly include Duchenne muscular dystrophy (DMD), limb girdle muscular dystrophies (LGMD), spinal muscular atrophy, Friedreich’s ataxia, Huntington’s disease, and amyotrophic lateral sclerosis (ALS). Gene editing treatment for DMD is one of the most advanced treatments among them. DMD is caused by mutations in a large gene called the dystrophin gene, which leads to the most common large deletions that shift the downstream gene to go out of frame and render the protein product nonfunctional. Moreover, the dystrophin gene cannot be packaged into size-restricted viral delivery vectors because of the vast coding sequence of the dystrophin gene (14 kb). Recently, many works have incorporated the CRISPR/Cas9 system into viral vectors with tropism for skeletal and cardiac muscle with different approaches to explore the therapeutic strategy of DMD and have significantly enhanced the skeletal muscle functions and cardiac hemodynamics in animal models. For instance, studies have focused on alleviating DMD by deleting single or multiple exons [33, 201–206] and performing point mutation repair [207, 208], respectively. In 2016, to correct DMD by skipping mutant dystrophin exons in postnatal muscle tissue in vivo, researchers used AAV9 to deliver gene-editing components to DMD model mice, and the dystrophin protein expression in cardiac and skeletal muscle was restored to varying degrees [202]. In the same year, CRISPR/Cas9 system was used in a mouse model of DMD to remove the mutated exon 23 from the dystrophin gene. Exon 23 deletion by CRISPR/Cas9 resulted in the expression of the modified dystrophin gene, and the functions and phenotypes of associated proteins and tissues were partially restored [204]. Researchers also produced specific CRISPR/Cas9-HCAdV to target DMD, and CRISPR/Cas9-HCAdV proved to be efficient in delivering the respective CRISPR/Cas9 expression units and introducing the desired DNA DSBs at intended target sites in immortalized and primary cells [201]. The use of single or dual AAV vector delivery of a muscle-specific Cas9 cassette together with sgRNA cassettes fully corrected the mutation in a dystrophin homology region [205]. Later, DMD model mice were treated intravenously with AAV-mediated CRISPR gene editing and evaluated for disease rescue at 18 months. The nominal dystrophin levels in skeletal muscle and cardiac tissue were restored, but histology and hemodynamics were not improved. The gRNA was found to be depleted, suggesting that gRNA vector loss is a unique barrier for systemic AAV-mediated CRISPR gene editing therapy and that the vector dose needs optimization [33]. In 2018, researchers showed that using CjCas9 as a gene-editing tool to correct an out-of-frame Dmd exon in Dmd knockout mice enhanced muscle strength without off-target mutations [203]. SaCas9 was also proven to have the ability to edit the human DMD gene [206]. Furthermore, BE, as a novel method of gene editing, also applies to the treatment of DMD. In 2018, the split ABE gene was delivered by AAV vectors to muscle cells in a mouse model of DMD to correct nonsense mutations in the Dmd gene, demonstrating the therapeutic potential of BEs in adult animals [196]. ALS is an incurable neurodegenerative disease that usually causes selective loss of motor neurons in the cortex, brain stem, and spinal cord. Because of the diverse genetic origin of ALS, at least 20 genes have been shown to be related to ALS, such as the variants of the SOD1, C9orf72, FUS, and TARDBP genes [209]. Superoxide dismutase 1 (SOD1) mutation is one of the most notable causes [210]. To modify the mutant SOD1 gene, the AAV-SaCas9-sgRNA system was tested to modify mutant SOD1 in SOD1G93A transgenic mice and successfully deleted the SOD1 gene. It was reported that the lifespan of SOD1G93A mice was prolonged by 54.6% [34]. Moreover, the mutations in other genes associated with ALS were corrected by the CRISPR/Cas9 system in animal models and patient-derived iPSCs [209]. BEs have held tremendous potential to treat molecular and genetic diseases since the creation. An intein-mediated trans-splicing system that enables the delivery of CBEs consisting of the widely used SpCas9 protein in vivo was engineered. In the G93A-SOD1 mouse model of ALS, intrathecally injected dual AAV particles encoding a split-intein CBE designed to trans-splice and insert a nonsense-coding substitution into a mutant SOD1 gene prolonged survival and noticeably slowed disease development [197]. Studies of other neuromuscular disorders are ongoing as well. For example, myotonic dystrophy type 1(DM1) was treated by CRISPR/Cas system mediated repeat region deletion [211], and muscular dystrophy type 1A (MDC1A) was treated by CRISPR/Cas system-mediated intronic deletion and dCas9 activation in animal models [198, 199] (Table 3).
The number of reported in vivo clinical trials of CRISPR-based therapeutic gene editing are much fewer than ex vivo due to the difficulty of technology and the complexity of the internal environment. In addition to the CRISPR/Cas9-based EDIT-101 drug product for the treatment of LCA10 is in progress of clinical trial phase 2, the treatment of HPV-related cervical intraepithelial neoplasia I, EBT-101 drug product for the treatment of HIV-1 infected adults, NTLA-2001 drug product for the treatment of hereditary transthyretin amyloidosis with polyneuropathy (ATTRv-PN) and with transthyretin amyloidosis-related cardiomyopathy (ATTR-CM) (Table 2) based on TALEN or CRISPR/Cas9 are all on the clinical trials (ClinicalTrials.gov Identifier: NCT03057912, NCT05143307, NCT05144386, NCT04601051). Among them, cervical intraepithelial neoplasia (CIN) and cervical cancer are major causes of persistent HPV infection. E6 and E7 play important roles in HPV-driven carcinogenesis and are appealing therapeutic intervention targets. Previous evidence showed that when HPV16 and HPV18 E6/E7 DNA were disrupted by the designated genome editing tools TALEN and CRISPR/Cas9, the expression of E6/E7 was significantly decreased, inducing cell apoptosis and inhibiting cell line growth. EBT-101 is an HIV-1-specific CRISPR/Cas9 gene editing system delivered by AAV9 for intravenous (IV) administration. Eligible participants received a single IV dose of EBT-101 and were required to attend multiple study visits at irregular intervals for safety monitoring. The duration of the long-term follow-up (LTFU) study will be up to 15 years. Hutchinson-Gilford progeria syndrome (HGPS) is a rare genetic disease caused by single point mutations. The gene that codes for nuclear lamin A, LMNA, usually contains a dominant-negative C-G-to-T-A mutation (c.1824 C > T; p.G608G). This mutation leads to RNA mis-splicing, which results in progerin, a lethal version of lamin A. Progerin is a toxic protein that induces the premature aging. In 2020, the first HGPS monkey model with typical HGPS phenotypes was generated by microinjecting a BE mRNA and gRNA into monkey zygotes that target the LMNA gene with high success rates [212]. ABEs can convert targeted A·T base pairs to G·C base pairs with few byproducts, without the need for donor DNA templates or DSBs. Injecting ABE-expressing AAV9 at postnatal day 14 directly fix the pathogenic HGPS mutation in a mouse model of HGPS in 2021, this increased the mice's vigor and significantly extended their median longevity from 215 to 510 days [76]. A dominantly or recessive inherited form of genetic deafness caused by the point mutation of transmembrane channel-like 1 gene (TMC1). To maintain normal auditory function, TMC1 encodes a protein that forms mechanosensitive ion channels in sensory hair cells of the inner ear. The point mutation of TMC1 leads to complete loss of auditory sensory transduction. To ameliorate hearing loss in a mouse model, researchers engineered a Cas9-gRNA complex delivered by cationic lipids in vivo and found that genome editing agents disrupted the dominant deafness-associated allele in TMC1, reducing progressive hearing loss in 2018 [200]. Later, researchers developed a BE strategy to treat this form of deafness. After testing several optimized CBEs and gRNAs, the most promising CBE derived from an activation-induced cytidine deaminase was chosen and delivered by AAV using a split-intein delivery system, which eventually successfully improved the hearing of the mouse models [83].
Multiple studies have brought tremendous progress in therapeutic genome editing. Nevertheless, the clinical translation of this unique technology still faces many challenges, especially targeting, safety and delivery issues.
The target sites of CRISPR, BEs and PEs are constrained due to the PAM specificity of Cas proteins. To maximize on-target activity while minimizing unwanted editing, directed evolution and engineered variants of SpCas9 are necessary. For example, in 2020, Walton et al. developed a variant named SpG that is able to target an expanded set of NGN PAMs. They further optimized the enzyme, and a near-PAMless SpCas9 variant named SpRY was developed. SpG and SpRY eliminated the NGG PAM requirement [213]. The same year, Shannon et al. reported on the directed evolution of three novel SpCas9 variants that could recognize NRRH, NRTH, and NRCH PAMs (where R is either A or G and H is either A, C, or T), successfully expanding the SpCas9 sequence space that was accessible to PAMs [66]. Hiroshi et al. in 2018 engineered a SpCas9 variant (SpCas9-NG) that can recognize relaxed NG PAMs, extending the recognizable PAM sequence [214]. Kleinstiver et al. in 2015 established two variants of SpCas9 called VQR and VRER, which recognized the novel PAM sequences NGAN/NGNG and NGCG, enhancing the opportunities to utilize SpCas9 in the CRISPR/Cas9 platform [215]. Moreover, researchers also used molecular evolution to modify the NNGRRT PAM specificity of SaCas9 [216–218].
In addition to improve the targeting scope of CRISPR tools, approaches to maximize targeting specificity and minimize the off-target effects of the CRISPR/Cas9 system are unmet needs. It was possible to try to make efforts in these three aspects: reforming Cas9 variants [219–223], modifying sgRNA [224] and improving the delivery platform of CRISPR/Cas9. For example, SpCas9-HF1 [219], eSpCas9 [220], evoCas9 [221], HypaCas9 [222] and Sniper-Cas9 [223] were engineered to reduce non-specific DNA contacts and all of them maintained robust on-target cleavage. In 2019, Kocak et al. demonstrated that adding a hairpin secondary structure to sgRNAs' spacer region (hp-sgRNAs) can boost the specificity over 55-fold when combined with different CRISPR effectors [224]. Moreover, many other methods of modifying sgRNAs to reduce off-target effects exist: selection [225–227], truncation [228, 229] or extension [230] of guide sequences. To improve the delivery platform of CRISPR/Cas9, Sojung et al. showed that delivering purified Cas9 ribonucleoproteins improved the efficiency of genome editing in human cells in 2014 [231]. Suresh et al. demonstrated that the cell-penetrating peptide-mediated delivery of Cas9 protein and gRNA can effectively reduce off-target effects [232]. Compared to CRISPR/Cas9, BEs and PEs allow targeting specificity with fewer indels and fewer off-target effects. Indels caused by CBE and ABE are 1.1% and 0.1%, respectively, as opposed to the substantially greater 4.3% indels caused by Cas9-HDR editing [53, 54]. Additionally, at four main Cas9 off-target loci, PEs averaged 0.6% off-target alterations as opposed to Cas9 + sgRNA, which averaged 32% off-targeting at the same four loci [22]. To further eliminate the off-target effects of BEs, researchers engineered CBE variants that minimized Cas9-independent off-target DNA editing by approximately 10 to 100-fold [233]. While high-fidelity Cas9 was fused to BE2 and BE3 to develop HF-BE2 and HF-BE3, respectively, aiming to limit the Cas9-dependent off-targeting, the HF-BE2 showed several-fold lower off-targeting, and HF-BE3 showed 37-fold lower off-targeting relative to traditional BEs [234]. Co-expression of free UGI with BE3 containing triple UGI [235] and fusion of bacteriophage Gam protein with BE3 and BE4 [236] are the other two efforts to reduce BE off-targeting.
Regarding the off-target effect, whether it can refer to all the conditions of therapeutic genome editing remains unclear since a therapy always targets one site within billions of DNA base pairs, modifies millions of cells, and varies among patients [219, 220]. Second, the human immune reaction and cytotoxicity are also tricky matters, and how the human immune system will respond to the in vivo administration of genome-editing tools and genetically modify cells remains unknown. Viral delivery systems have relatively high efficiency in transgene delivery but are controversial in the latent cytotoxicity they may cause; adenoviral vectors may lead to immune elimination of infected cells [98], and LVs have the risk of potential oncogenesis [115].
Currently, nucleic acid-based diagnostics are the best methods to detect various diseases. The speed and accuracy of disease diagnosis are of vital importance to the prevention and treatment of diseases, especially those caused by infectious viruses. A more recent example is the worldwide pandemic of COVID-19. During the outbreak of COVID-19, the fast and accurate nucleic-acid-based testing is central and essential for controlling the spread of disease, suggesting the need for innovative detection methods with higher sensitivity and specificity. One of the most required elements for disease detection is nucleic-acid-based biomarkers, which are able to amplify trace amounts of DNA or RNA and then pair complementary nucleotides with high specificity. In addition to disease diagnosis, nucleic acid-based biomarkers are also applied for agriculture, food safety and environmental monitoring. Currently, the most common technique for identifying nucleic acid-based biomarkers is quantitative polymerase chain reaction (qPCR), or sequencing combined to RT in the case of RNA. Because of its versatility, robustness, and sensitivity, it is the gold-standard technique for most nucleic acid-based diagnostics of various diseases. To obtain more reliable and reproducible results, numerous processes need to be optimized, include amplicon detection, primer design, DNA or RNA extraction, and data normalization [237]. However, the process of PCR exhibits nonspecific amplification, which reduces the specificity of detection, even though heat cyclers are not needed for isothermal nucleic acid amplification [238]. Some extra readouts such as fluorescent probes, oligo strand-displacement probes, and molecular beacons, may relatively improve the specificity [239–241], but the costs of reagents, laboratory equipment and trained technicians are high [237]. Therefore, a new detection technique needs to be engineered with the advantages of ease of use and cost efficiency of isothermal amplification with the diagnostic accuracy of PCR. The new next-generation detection technique is supposed to be single-nucleotide specific. This is required for the identification of the most dangerous pathogenic bacterial or viral variations and strains as well as the detection of genotyping, cancer, and mutations that confer resistance to antibiotics, antiviral medications, or cancer therapies. CRISPR/Cas is widely known for its use as a gene-editing tool. Because of its high specificity to detect DNA and RNA sequences, CRISPR-based diagnostics are able to fulfill these unmet needs, and various CRISPR systems have been modified for nucleic acid detection in recent years.
The CRISPR/Cas system is a fundamental part of a prokaryotic adaptive immune system in various archaea and bacteria [45]. It targets foreign genomes based on their sequence and subsequently eliminates them through the endonuclease activity of the Cas enzyme. Diverse Cas enzymes exist among different species of archaea and bacteria and are composed of various CRISPR/Cas systems. The crRNA guides Cas proteins to recognize and cleave nucleic acids that are targeted, and they have high specificity to target specific DNA and RNA sequences, which makes CRISPR/Cas systems have the potential to offer cost-effective, portable and point-of-care diagnosis through nucleic acid screening of diseases.
The Cas13 effector is already frequently used to create RNA knockout models, but more recently, it has also been used as a molecular diagnostic tool for accurate and precise RNA detection. The 900–1,300 amino acid CRISPR/Cas type VI (Cas13) family of enzymes is employed to identify ssRNA in the cis conformation and exhibits collateral trans-cleavage activity against ssRNA in vitro [242, 243]. After finishing the study of most of the CRISPR nucleases from microorganisms, Zhang’s group characterized the class 2 type VI CRISPR/Cas effector C2c2 (also known as Cas13a) from the bacterium Leptotrichia shahii and demonstrated its RNA-guided ribonuclease function. These findings broaden the range of CRISPR/Cas systems and suggest that Cas13a can be used to develop new RNA-targeting tools [243]. However, the Cas13a was found to have the ability to cut ssRNA randomly and nonspecifically after completing specific RNA cutting, which means that Cas13a has a strong cytotoxicity and cannot be used as a tool for gene editing, such as Cas9. In the same year, Doudna’s group showed that the unique dual RNase activities of Cas13a enable its two distinct catalytic capabilities, multiplexed processing and loading of gRNAs, which in turn allow for sensitive cellular transcript detection. In the reaction system of molecular detection, a ssRNA with chemical modification is used as the substrate. When Cas13a specifically cleaves the target RNA, it can also cleave the ssRNA substrate. The chemically modified ssRNA will not emit fluorescence until it is cut off, and then transcript detection is achieved [242]. Finding a more rapid, cheap and sensitive way to detect pathogens is the goal scientists are striving for. To achieve this goal, Zhang’s group created a SHERLOCK (Specific High Sensitivity Enzymatic Reporter UnLOCKing) detection platform based on CRISPR/Cas13a (Fig. 4a), and they established a CRISPR-based diagnostic (CRISPR-Dx) by combining the collateral effect of Cas13a with isothermal amplification. First, using a forward primer with the addition of a T7 promoter, recombinase polymerase amplification (RPA) or RT-RPA, respectively, isothermally amplifies DNA or RNA. The Leptotrichia wadeii Cas13a (LwaCas13a) complex and a crRNA containing the target's complementary sequence bind to the targeted sequence after the T7 promoter permits RNA production of the target. Cas13 is activated and cleaves both the on-target RNA and ssRNA reporter molecules by cis cleavage and collateral trans cleavage, respectively. The ssRNA reporter molecule is composed of a fluorophore and quencher binding with a short RNA oligomer, and the fluorophore separates from the quencher to produce fluorescence once the oligomer is cleaved. The entire procedure has been demonstrated to successfully detect certain strains of the Zika and Dengue viruses, discriminate pathogens, genotype human DNA, and detect cell-free tumor DNA mutations. It also offers quick DNA or RNA detection with attomolar sensitivity and single-base mismatch specificity [38]. Version two of SHERLOCK (SHERLOCKv2) introduces an immunochromatographic assay-based lateral-flow readout, using antibody-conjugated gold nanoparticles on a paper strip to detect cleaved reporter molecules. In addition, the SHERLOCKv2 has achieved the quantitative multiplexed sensing of nucleic acids and the target detection at zeptomolar (10–21 M) concentrations [244].
SHERLOCK is a very sensitive and specific tool in the detection of target RNA, but for the detection of target DNA, in vitro transcription of DNA to RNA must be conducted before the SHERLOCK test, which is inconvenient. The Cas12 enzyme is an effective tool to achieve the diagnosis of target dsDNA and ssDNA with the requirement of a PAM site in the target region for dsDNA cleavage and the collateral cleavage of ssDNA [245]. Doudna’s group focused on Cas12a, which like CRISPR/Cas9, has the ability to generate targeted DSBs and has been harnessed for genome editing. They found that Lachnospiraceae bacterium Cas12a (LbCas12a) or Cas12a from other organisms can facilitate RNA-guided DNA binding, which releases indiscriminate ssDNA cleavage activity. Because Cas12a degrades ssDNA molecules completely with the help of a complementary crRNA that enables Cas12a to be guided to dsDNA. Then, the quencher from the fluorophore is separated as a result of target recognition and reporter cleavage, and a fluorescence signal is produced. Moreover, other type V CRISPR/Cas12 enzymes also have the property of target-activated, nonspecific single-stranded deoxyribonuclease (ssDNase) cleavage. With the help of Cas12a, ssDNase was activated with isothermal amplification, a DNA endonuclease-targeted CRISPR trans reporter (DETECTR) was created (Fig. 4a), and with the combination of RPA preamplification, the sensitivity of DETECTR reached attomolar. DETECTR enabled rapid and specific detection of human papillomavirus in patient samples and achieved DNA detection for the first time [39]. Moreover, the CRISPR-based DETECTR assay provides an alternative to the US Centers for Disease Control and Prevention SARS-CoV-2 real-time RT–PCR assay due to its visual and fast characteristics [37]. Subsequently, Wang’s group used a quenched fluorescent ssDNA reporter as the probe and employed PCR for preamplification together with LbCas12a engineered a one-Hour Low-cost Multipurpose highly Efficient System (HOLMES). HOLMES has the ability to quickly detect both target DNA and RNA. In a reaction system that exists in target DNA, the Cas12a/crRNA binary complex and the target DNA form a ternary complex, transcleaving a nontargeted ssDNA reporter and illuminating fluorescence in the system [41]. Then, in order to identify SNPs and various viruses, such as the Japanese encephalitis virus (JEV) better [246], HOLMES was optimized to HOLMESv2 by using loop-mediated isothermal amplification (LAMP) in conjunction with a thermostable Cas12b from Alicyclobacillus acidoterrestris (AacCas12b) in a one-pot reaction [247]. Similarly, the limit of detection (LOD) for HOLMES and HOLMESv2 is roughly 10 aM.
In addition to Cas13a and Cas12a, Cas9 combined with other techniques can also be used for the detection of specific DNA and RNA sequences, which again broadens the field of molecular diagnosis. Guide-directed reconstitution of split proteins by catalytically inactive Cas9 partners [248], Cas9-based destruction of PAM-containing sites [249], and Cas9-induced unwinding of the non-targeted DNA strand as a targeting site for isothermal amplification [250] are three main principles of many different Cas9-based approaches for sensing DNA. In 2016, Collins’s group used a novel CRISPR/Cas9-based module nucleic acid sequence-based amplification (NASBA)-CRISPR cleavage (NASBACC) to detecte clinically relevant concentrations of Zika virus sequences and show selectivity against closely related Dengue virus sequences. Through nucleic acid sequence-based amplification, the amplification of targeted RNA starts with RT to complementary DNA using a sequence-specific primer that appends a trigger sequence (magenta) for the toehold sensor. Then, the RNase H destroys the RNA from the RNA/DNA hybrid, creating the chance for the binding of the primer containing a T7 promoter and producing a complementary second DNA strand. A toehold sensor for the readout and PAM-dependent target detection is attached to nucleic acid sequence-based amplification through RT, and then Cas9 mediates the cleavage in the CRISPR/Cas9-based method (Fig. 4a). When the RNA fragment contains a PAM sequence, Cas9-mediated cleavage produces a truncated RNA that lacks the trigger region for T7 transcription; otherwise, the trigger containing full-length RNA activates the toehold sensor and produces a visible change in color. The technique successfully detected Zika virus (ZIKV) in the low femtomolar range in infected monkey plasma by sensing strain-specific PAM sites [251]. In 2019, Xing’s group developed a novel CRISPR/Cas9-triggered isothermal exponential amplification reaction (CAS-EXPAR) strategy mediated by CRISPR/Cas9 cleavage and nicking endonuclease (NEase)-mediated nucleic acid amplification for site-specific and real-time fluorescent nucleic acid detection [252]. In 2020, Wang’s group improved the efficiency and precision of immune response analytical techniques by introducing the CRISPR/Cas9 system into the lateral flow assay, termed the CRISPR/Cas9-mediated lateral flow nucleic acid assay (CASLFA). CASLFA is able to detect Listeria monocytogenes, genetically modified organisms, and African swine fever virus [253]. In 2021, the FELUDA (FNCAS9 Editor-Linked Uniform Detection Assay) was developed using a catalytically inactive form of Cas9 to identify the targeted mismatches, bind to target DNA, but do not cleave it. The FELUDA was demonstrated to be successfully used for SARS-CoV-2 molecular testing [246]. Compared with CRISPR/Cas9 systems, CRISPR/Cas12 systems and CRISPR/Cas13 systems have the ability to trigger non-specific collateral cleavage on target recognition (Fig. 4b). The cleavage of non-targeted ssDNA by Cas12 and ssRNA by Cas13 are involved in collateral cleavage activity. The collateral cleavage activity provides the detection of nucleic acids by signal amplification and allows for various readouts by the addition of functionalized reporter nucleic acids.
In recent years, the field of the CRISPR diagnosis has expanded rapidly, growing from the specific set of molecular biological discoveries to several active clinical trials (ClinicalTrials.gov identifiers: NCT05143593, NCT04535505, NCT04178382, NCT04074369, NCT04535648), multiple COVID-19 tests and the establishment of several companies (Table 4). CRISPR-based detection methods are combined with pre-existing preamplification and readout technologies to achieve a sensitivity and reproducibility equivalent to and comparable to the current first-rate standard nucleic acid detection methods. However, there are still several limitations that need to be optimized to diagnose the diseases and monitor the progression of pathogens. The dependence on preamplification when detecting targets below the femtomolar range is one of the major limitations of most current CRISPR-based diagnostics, which increases the complexity, cost and reaction time. The potential methods to solve this problem may be the incorporation of non-primer-based signal-amplification strategies or modifications of the Cas enzyme, crRNA or reporter molecule. Moreover, sample preparation is another issue that makes the diagnosis process more complex, as it requires a separate step and special heating devices with an incubation program. With the effort to continuously improve the CRISPR-based diagnostic innovations, this new technology will play an even more important role in molecular diagnosis.
Genome editing has changed the definition of gene and cell therapy and has been a key factor in correcting many molecular and genetic diseases. Compared to the CRISPR/Cas9 system, the BE and PE systems are simpler and more precise, achieving the correction of point mutations in human genetic diseases that account for more than half of all human genetic diseases [90]. Moreover, BEs and PEs can edit the genome without DSBs and are able to edit both dividing and non-dividing cells [272], greatly increasing the efficiency, targeting scope, and purity of the edited products. However, the targeting specificity of genome editing tools needs to be further optimized, and significant safety and delivery issues, such as off-target effects, human immune reactions, cytotoxicity and delivery efficiency, need to be addressed before genome editing can be widely used for treating human diseases. The feature of high specificity to recognize and cleave target specific DNA and RNA sequences, makes CRISPR/Cas systems have the potential to offer cost-effective, portable and point-of-care diagnosis through nucleic acid screening of diseases. With the successful creation of CRISPR-based molecular diagnosis such as SHERLOCK, DETECTR, HOLMES NASBACC and so on, the possibilities for the application of the CRISPR system have been extended. More importantly, as disease detection technologies continuously improve, the CRISPR system will be a large step to resist to various diseases, especially pandemic viruses worldwide. | true | true | true |
PMC9561268 | 36156138 | Anzhi Sheng,Jingyi Yang,Longfei Tang,Lili Niu,Liangfen Cheng,Yujing Zeng,Xu Chen,Juan Zhang,Genxi Li | Hydrazone chemistry-mediated CRISPR/Cas12a system for bacterial analysis | 26-09-2022 | Abstract In this study, a hydrazone chemistry-mediated clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 12a (Cas12a) system has been proposed for the fist time and constructed. In our system, hydrazone chemistry is designed and employed to accelerate the formation of a whole activation strand by taking advantage of the proximity effect induced by complementary base pairing, thus activating the CRISPR/Cas12a system quickly and efficiently. Moreover, the introduction of hydrazone chemistry can improve the specificity of the CRISPR/Cas12a system, allowing it to effectively distinguish single-base mismatches. The established system has been further applied to analyze Pseudomonas aeruginosa by specific recognition of the probe strand with a characteristic fragment in 16S rDNA to release the hydrazine group-modified activation strand. The method shows a wide linear range from 3.8 × 102 colony-forming units (CFU)/ml to 3.8 × 106 CFU/ml, with the lowest detection limit of 24 CFU/ml. Therefore, the introduction of hydrazone chemistry may also broaden the application of the CRISPR/Cas12a system. | Hydrazone chemistry-mediated CRISPR/Cas12a system for bacterial analysis
In this study, a hydrazone chemistry-mediated clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 12a (Cas12a) system has been proposed for the fist time and constructed. In our system, hydrazone chemistry is designed and employed to accelerate the formation of a whole activation strand by taking advantage of the proximity effect induced by complementary base pairing, thus activating the CRISPR/Cas12a system quickly and efficiently. Moreover, the introduction of hydrazone chemistry can improve the specificity of the CRISPR/Cas12a system, allowing it to effectively distinguish single-base mismatches. The established system has been further applied to analyze Pseudomonas aeruginosa by specific recognition of the probe strand with a characteristic fragment in 16S rDNA to release the hydrazine group-modified activation strand. The method shows a wide linear range from 3.8 × 102 colony-forming units (CFU)/ml to 3.8 × 106 CFU/ml, with the lowest detection limit of 24 CFU/ml. Therefore, the introduction of hydrazone chemistry may also broaden the application of the CRISPR/Cas12a system.
Cas12a (CRISPR-associated protein 12a) is a nucleic acid endonuclease from the V-A-type clustered regularly interspaced palindromic repeats (CRISPR) system for genome editing by processing CRISPR RNAs (crRNAs) from arrays using its dedicated RNase functional domain (1,2). It can indiscriminately cleave single-stranded DNA (ssDNA) after activation of intrinsic nuclease activity by recognizing its target site, which has been used for the detection of nucleic acids (3,4). However, there are still many challenges to overcome. The system is unsuitable for distinguishing very similar ssDNA sequences (1,5). Moreover, the interference between similar ssDNA sequences may cross-react for multiple target detection in a single reaction system, which affects the analytical sensitivity and specificity (6). Usually, it may also be difficult to find a protospacer adjacent motif (PAM) sequence matching with Cas12a protein for the direct detection of short target sequences. So, the effector protein and target sequence need to be carefully selected to avoid background signals (7). Hydrazone chemistry has the advantages of rapid reaction, mild reaction conditions and good selectivity (8,9). Since the programmability of a CRISPR/Cas system relies on the interaction of guide RNA and nucleic acid, we envisage that hydrazone chemistry can be introduced into the initiation sequence of the system to activate the CRISPR/Cas12a system more flexibly, which may not only improve the specificity, but may also be widely used in the analysis of different targets (2,10,11). Here, we have constructed a detection platform based on a hydrazone chemistry-mediated CRISPR/Cas12a system. In our system, the activation strand is subtly designed as a hairpin structure, which is elaborately split into two segments separately modified by two hydrazone-linked groups, hydrazine and an aldehyde group. Meanwhile, the probe complementary sequence is carefully designed to release the hydrazine group-modified split segment due to the specific binding of the target sequence to the probe, leading to the formation of the whole activated strand and the activation of the hydrazone chemistry-mediated CRISPR/Cas12a system. Therefore, the introduction of hydrazone chemistry not only improves the specificity of the CRISPR/Cas12a system, but also accelerates the activation process of the CRISPR/Cas12a system. Pseudomonas aeruginosa is a common environmental bacterium that can spread rapidly through animal feces, food and water. The bacterium can cause infectious diseases such as otitis, pneumonia, keratitis, sepsis and endocarditis (12). The traditional detection methods for this bacterium include colony culture and counting, which is routine, accurate and reliable for microbial detection (13,14). However, these methods are always labor-intensive and time-consuming (15), which has greatly limited their application. Therefore, it is urgent to develop a new method to detect P. aeruginosa. In this work, we have proposed a simple and sensitive method for the analysis of P. aeruginosa based on the proposed hydrazone chemistry-mediated CRISPR/Cas12a system, which may have great potential application in the future.
All oligonucleotides (as shown in Supplementary Table S1) were synthesized and purified by Shanghai Sangon Biotechnology Co., Ltd (Shanghai, China), EnGen®LbaCas12a (Cpf1) (M0653T) was purchased from NEB (Beijing, China), RNase inhibitor (K1046) was purchased from APExBIO (Shanghai, China) and diethylpyrocarbonate (DEPC) water was purchased from Shanghai Sangon Biotechnology Co., Ltd. 4-Hydrazinobenzoic acid was obtained from Wokai Biotechnology, Co., Ltd (Beijing, China). All experimental water was obtained through the Milli-Q purification system (R >18 MΩ/cm). All other chemicals are analytical reagent grade.
First, 95 mg of EDC [1-ethyl-3-(3-dimethylaminopropyl)carbodiimide] and 11 mg of NHS (N-hydroxysuccinimide) were dissolved in 1 ml of deionized water to prepare the cross-linking agent, and then 0.5 mM 4-hydrazinobenzoic acid was added to the cross-linking agent for 20 min, followed by the addition of 100 μM TS1-NH2 strand. After sonicating for 30 s, the mixture was kept for 12 h with regular shaking. Finally, the mixture was separated by using a gel column (illustrra MicroSpin G-25 columns) to obtain TS1-NHNH2, which was characterized by Fourier infrared spectroscopy (Bertex 70, Bruker, Germany).
First, the TS2-CHO strand (10 μM) was heated at 95°C for 5 min and then cooled naturally to room temperature. A 4.8 μl of the TS1-NHNH2 strand (0.6 μM) was mixed with 4.8 μl of the TS2-CHO strand (0.6 μM), 8 μl of 10× buffer, 2 μl of RNase inhibitor (40 U), 3.2 μl of Cas12a (200 nM), 1.6 μl of crRNA (200 nM) and 1.6 μl of ssDNA-FAM (200 nM). Finally, DEPC water was added to a final volume of 80 μl. After incubation at 37°C for 15 min, the mixture was heated at 65°C for 10 min to inactivate the enzyme. The fluorescence intensity of the reaction solution was measured by a fluorescence spectrometer (F-7000, Hitachi Ltd, Japan).
A 4.8 μl aliquot of the 16S rDNA probe strand (Probe) (0.6 μM) was mixed with 4.8 μl of the TS1-NHNH2 strand (0.6 μM). After heating at 95°C for 5 min, the mixture was cooled naturally to room temperature. Subsequently, 4.8 μl of the TS2-CHO strand (0.6 μM) was added, followed by the addition of 10 μl of synthetic target DNA at various concentrations. Finally, the mixture was incubated at 37°C for 60 min. The product was characterized through polyacrylamide gel electrophoresis (PAGE).
Again a 4.8 μl aliquot of Probe (0.6 μM) was mixed with 4.8 μl of the TS1-NHNH2 strand (0.6 μM), and the mixture was heated at 95°C for 5 min and cooled naturally to room temperature. Subsequently, 4.8 μl of the TS2-CHO strand (0.6 μM) and 10 μl of P. aeruginosa suspension at various concentrations were added and incubated at 37°C for 60 min, followed by the addition of 8 μl of 10× buffer, 2 μl of RNase inhibitor (40 U), 3.2 μl of Cas12a (200 nM), 1.6 μl of crRNA (200 nM) and 1.6 μl of ssDNA-FAM (200 nM). Finally, DEPC water was added to give a final volume of 80 μl. After incubating at 37°C for 15 min, the mixture was heated at 65°C for 10 min to inactivate the enzyme. The fluorescence intensity of the reaction solution was measured by a fluorescence spectrometer (F-7000, Hitachi Ltd, Japan). The logarithm of odds (LOD) of the assay was calculated using the formula LOD = 3σ/S, where σ is the standard deviation of the unadded sample and S is the slope of the calibration curve.
All strains were obtained from stock cultures in the laboratory of Professor Dr Lili Niu. The concentrations of these strains were determined by McFarland's turbidimetric assay. The specificity of the established method was evaluated using 3.8 × 106 colony-forming units (CFU)/ml of Escherichiacoli 2571, E. coli 25922 and Stapylococcus aureus instead of P. aeruginosa. In addition, different concentrations of P. aeruginosa (3.8 × 103, 3.8 × 105 and 3.8 × 106 CFU/ml) were added to pure water, milk, grapefruit juice and green tea to make the spiked samples. After adjusting the pH value of the spiked samples with NaOH or HCl to 7.0, the amount of P. aeruginosa was analyzed by using the established method, and the relative recoveries were calculated.
A single colony of bacteria was cultured in LB medium for 9 h and examined under a microscope. Subsequently, 50 μl of the solution was taken evenly onto the slide, and successively fixed by flame and 4% paraformaldehyde (PFA) for 10 min, followed by drying naturally. Then the glass slide was immersed in a mixture of 50% alcohol and 50% phosphate-buffered saline (PBS) for 10 min and air-dried. After that, 200 μl of Probe-Cy5 was added and incubated at 55°C for 6 h in hybridization buffer containing 10 mmol/l NaCl, 30% (v/v) formamide, 5 mmol/l Na2EDTA, 0.2% (v/v) Triton X-100 and 50 mmol/l Tris–HCl. After hybridization, the slide was washed twice for 10 min each time with 55°C pre-warmed washing buffer containing 5 mmol/l Tris–HCl, 15 mmol/l NaCl and 0.1% (v/v) Triton X-100. The slices were air-dried naturally and sealed with 80 μl of antifade polyvinylpyrrolidone mounting medium, followed by covering with a coverslip.
Two-tailed Student's t-test was used for evaluating statistical differences between two groups by the GraphPad software (Prism 7), and P <0.05 was statistically significant.
The hydrazone chemistry-mediated CRISPR/Cas12a system is illustrated in Figure 1A. The activated strand is split into two parts, i.e. TS1-NHNH2 and TS2-CHO. Neither TS1-NHNH2 nor TS2-CHO can activate the CRISPR/Cas12a system. With the aid of complementary base pairing, TS1-NHNH2 containing a hydrazide group is easier to react with the aldehyde group of TS2-CHO to form a whole TS1/TS2 strand through a hydrazone bond. Localization of Cas protein mainly depends on the PAM in TS1-NHNH2 (2). After the linkage of the TS1-NHNH2 strand with the TS2-CHO strand, the Cas12a/crRNA complex localizes to the TS1/TS2 strand and cleaves to generate sticky ends far away from its PAM sequence (16). The subsequent activated trans-cleavage activity of the Cas12a/crRNA complex will result in the non-specific cleavage of ssDNA-FAM and fluorescence recovery. The formation of TS1/TS2 through a hydrazone bond was confirmed by infrared spectroscopy. The peaks at 1563 cm−1 and 1266 cm−1 corresponding to the amide II and III bands and another peak at 1642 cm−1 attributed to the stretching vibration of the C=N double bond appear, while the peaks at 1735 cm−1 ascribed to the stretching of the carbonyl group in the saturated aliphatic aldehyde disappears (Supplementary Figure S1A). These results confirm the formation of a hydrazone bond between TS1-NHNH2 and TS2-CHO. Moreover, a new band in L3 can be observed (Supplementary Figure S1B), verifying the successful linkage between TS1-NHNH2 and TS2-CHO. Slight changes in the target sequence can lead to instability of the triple complex of the target DNA–crRNA–Cas effector interfering with the activation response (16,17). We first explored the effect of strand length on CRISPR/Cas12a activation. When the number of bases of TS1 or TS2 changes from 8 nt to 11 nt, no obvious fluorescence peaks can be detected (Figure 1B1, B2), indicating that none of them could activate CRISPR/Cas12a. When the number of bases of TS1 or TS2 increases from 12 nt to 20 nt (18), obvious fluorescence peaks can be detected, indicating the occurrence of partially activated CRISPR/Cas12a (Figure 1B1, B2). Based on these findings, in the following experiment, the full-length TS was split into two segments, namely TS1-NHNH2 and TS2-CHO, each with a length of 10 nt. Subsequently, the effects of the introduction of hydrazone chemistry on the activation of CRISPR/Cas12a were investigated. Compared with that for the full-length TS, the whole TS1/TS2 can give similar values of Kcat, Km and the kcat/Km ratio (Figure 1C1, C2). These results suggest that the introduction of hydrazone chemistry does not affect the activated effect of the whole TS1/TS2 on the CRISPR/Cas12a system and its corresponding trans-cleavage activity. It has been reported that double-stranded activated CRISPR/Cas12a is insensitive to single-base mismatches (19). Along with the optimization of the Cas12a concentration (Supplementary Figure S2), we further investigated the effect of introduction of hydrazone chemistry on the specificity of the CRISPR/Cas12a system. In comparison with that of full-length TS with one mismatched base pair (Figure 1D1), obviously decreased mean fluorescence intensity can be found for the whole TS1/TS2 with one pair of mismatched bases (Figure 1D2). This can be explained by the fact that the mismatched bases influence the occurrence of complementary base pairing between TS1-NHNH2 and TS2-CHO, so as to reduce the proximity effect and hinder the formation of a hydrazone bond. As confirmed by our previous experiment, TS1-NHNH2 or TS2-CHO with a length of 10 nt cannot activate the CRISPR/Cas12a system (Figure 1B1, B2). Therefore, the whole TS1/TS2 with one pair of mismatched bases evidently can influence the extent of the activation of the CRISPR/Cas12a system and its corresponding trans-cleavage efficiency. The introduction of hydrazone chemistry can improve the specificity of the CRISPR/Cas12a system, which can effectively distinguish a single-base mismatch in the target sequence. The degree of mismatch tolerance is highly dependent on the source of the effector protein and the location of the mismatch (18). We have further investigated the influence of the mismatch position on the trans-cleavage activity of the CRISPR/Cas12a system. For a single-base mismatch, different positions (1, 5, 10, 15 and 20 relative to the PAM region) were selected to study their effect on the trans-cleavage activity, and the corresponding results are shown in Supplementary Figure S3. With mismatch at position 1 adjacent to the PAM region, an obvious statistical differences can be found for both full-length TS and whole TS1/TS2. This can be explained by the fact that the PAM region is extremely important for the recognition and activation of the CRISPR/Cas12a system. However, for a single-base mismatch located at other positions, an evident statistical difference can only be observed for the whole TS1/TS2, while for the full-length TS no difference is found when the mismatch position is >5 away from the PAM region (3,20). These can be attributed to the weakened proximity effect as a result of a single-base mismatch, which is a disadvantage for the formation of a hydrazone bond and the ensuing whole TS1/TS2. Therefore, the introduction of hydrazone chemistry reduces the tolerance and increases the sensitivity of the CRISPR/Cas12a system activated by a single-base mismatched TS. Moreover, a decrease in cross-reactivity can be found for the hydrazone-linked whole TS1/TS2 in comparison with that for the full-length TS. As shown in Supplementary Figure S4, the single-base mismatched mutants make the full-length TS produce a high fluorescence background. In contrast, almost no effect can be found for hydrazone-linked whole TS1/TS2. These results signify that the introduction of a hydrazone bond can increase the specificity of the CRISPR/Cas12a system.
Figure 2A shows that synthetic target DNA induces the formation of the TS1/TS2 strand. Target DNA can competitively bind with Probe, resulting in the occurrence of a strand displacement reaction and the release of TS1-NHNH2. The released TS1-NHNH2 strand will bind to TS2-CHO through complementary base pairing. By virtue of the proximity effect, the hydrazine group of TS1-NHNH2 and the aldehyde group of TS2-CHO will react to form a hydrazone bond. In turn, the formed hydrazone bond accelerates the occurrence of complementary base pairing. Finally, hybrid strand TS1/TS2 will form through the hydrazone bond. In contrast, the strand displacement reaction will not occur and TS1/TS2 will not form without synthetic target DNA. As shown in Figure 2B, a new band in L4 indicates the formation of a Probe/TS1-NHNH2 hybrid. Moreover, the new band at the top of L5 can be explained by the formation of TS1/TS2 through a hydrazone bond. In the absence of Target, two bands in L6 can be separately ascribed for Probe/TS1-NHNH2 and TS2-CHO, suggesting no occurrence of a strand displacement reaction. In the presence of Target, two new bands shown in red squares belong to TS1/TS2 and Probe/Target, respectively. We further utilize the trans-cleavage capability of CRISPR/Cas12a to confirm the formation of TS1/TS2. As shown in Figure 2C, almost no fluorescence peak can be found with separate addition of Probe/TS1-NHNH2, TS2-CHO or Target, as a result of no formation of TS1/TS2 to activate the CRISPR/Cas12a system. In contrast, compared with that for full-length TS, a similar fluorescence peak can be found with the addition of Target into the mixture of Probe/TS1-NHNH2 and TS2-CHO. The result confirms the formation of TS1/TS2 resulting from the strand displacement reaction. Moreover, the band of long-stranded DNA (LDNA) as the substrate of CRISPR/Cas12a trans-cleavage disappears with the addition of Target in L11 in comparison with that without the addition of Target in L7 (Figure 2D). In addition, the LDNA band also vanishes in the presence of TS1/TS2. These results are in good agreement with those obtained through fluorescence spectroscopy and verify that the synthetic target DNA can mediate the formation of the TS1/TS2 strand.
The principle of the hydrazone chemistry-mediated CRISPR/Cas12a system for bacterial analysis is illustrated in Figure 3. With highly conserved regions across species and species-specific variable regions, bacterial 16S rRNA gene (16S rDNA) sequences are usually utilized for the identification of various bacteria (21). As shown in Figure 3, 16S rDNA can competitively bind with the Probe from the Probe/TS1-NHNH2 hybrid, resulting in the release of TS1-NHNH2 and the formation of Probe/16S rDNA. The released TS1-NHNH2 can hybridize with TS2-CHO through complementary base pairing, so as to accelerate the formation of TS1/TS2 through a hydrazone bond between the hydrazine group of TS1-NHNH2 and the aldehyde group of TS2-CHO. The formed TS1/TS2 can activate Cas12a/crRNA to discriminately cleave ssDNA-FAM, resulting in the recovery of fluorescence. In contrast, in the absence of bacteria, the formation of TS1/TS2 will not happen and the fluorescence will not recover. After smearing and Gram staining, the slender Gram-negative bacilli with variable lengths as well as bluntly rounded ends in the form of spherical rods or threads can be observed under light microscopy (Image a, Figure 3B), which could be characterized as P. aeruginosa. Meanwhile, the red fluorescence can be found for P. aeruginosa by using the 16S rDNA gene probe (22) labeled with the Cy5 fluorescent moiety (Image b, Figure 3B). The result signifies that the probe can be successfully applied for bacterial analysis. Furthermore, almost no fluorescence peak can be observed without P. aeruginosa (Image b, Figure 3C). In contrast, an evident high fluorescence peak can be found in the presence of P. aeruginosa (Image a, Figure 3C). The results clearly demonstrate that P. aeruginosa can induce the formation of TS1/TS2 to activate CRISPR/Cas12a, leading to the recovery of fluorescence. Meanwhile, the control experiment was designed and conducted, and the corresponding results are shown in Supplementary Figure S5. Almost no change of fluorescence intensity can be observed for TS1 or TS2, implying that TS1 or TS2 cannot activate the CRISPR/Cas12a system. High fluorescence intensity can be found for TS1 + TS2 and TS1-NHNH2 + TS2-CHO, confirming the activation of the CRISPR/Cas12a system. However, a higher activation efficiency can be found for TS1-NHNH2 + TS2-CHO in comparison with that of TS1 + TS2, considering that the former gives a quicker reaction rate (745.94 mol/l/s), a higher maximized fluorescence intensity (4126.80) and a shorter time needed to reach steady state (10 min) than those (130.70 mol/l/s, 3792 and 14 min) of the latter. The results verify that the formation of a hydrazone bond between the hydrazine group of TS1-NHNH2 and the aldehyde group of TS2-CHO can accelerate the formation of the whole TS1/TS2, so as to efficiently activate the CRISPR/Cas12a system. Therefore, the established method based on the hydrazone chemistry-mediated CRISPR/Cas12a system can be developed to detect bacteria.
As shown in Figure 4A, we first quantitatively analyzed the synthesized DNA Target strand using the established method. As the concentration of the synthetic DNA Target strand increases from 0 nM to 100 nM, the fluorescence intensity at 520 nm gradually increases (Figure 4A). The presence of the Target allows the release of TS1-NHNH2 from the Probe/TS1-NHNH2 double hybrid, culminating in the formation of the hydrazone bond-mediated hybridized TS1/TS2, which activates the trans-cleavage activity of CRISPR/Cas12a. It has been further found that the fluorescence intensity values increase linearly with increased logarithmic values of the synthetic DNA Target strand concentrations from 0.1 nM to 100 nM (Figure 4B). A linear equation: I = 1021.37 + 903.85 × log CTarget can be fitted, and the lowest detection limit has been calculated to be 0.074 nM (3σ/S), which is lower than other reported values for the detection of synthetic DNA (23,24). By calculating the slope of the three regression equations for the concentrations of the synthetic DNA Target strand from 0 nM to 100 nM, a relative standard deviation (RSD) value of 3.7% could be obtained, and the results indicate the good precision of our established method. Subsequently, on the basis of quantitative analysis of synthetic DNA Target, we used the established method to quantitatively analyze the bacteria which have been determined by the dilution coating plate method (Figure 4C). As the amounts of bacteria increase from 3.8 × 101 to 3.8 × 107 CFU/ml, the fluorescence intensities gradually increase (Figure 4D). The fluorescence intensity increases linearly as the logarithmic values of bacterial concentration increased from 3.8 × 102 to 3.8 × 106 CFU/ml. The linear equation I = –931.07 + 669.35 × log CP. aeruginosa (R2 = 0.9924) can be obtained (Figure 4E), with a linear detection range wider than the reported value (Supplementary Table S2) (25,26). The calculated detection limit is 24 CFU/ml (3σ/S), which is lower than the previously reported value (26–28). In addition, an RSD value of 6.6% can be obtained, which indicates the good reproducibility of the established method.
Different bacteria have been used to validate the specificity of the established method for the analysis of P. aeruginosa. Gram staining has been used to identify different bacteria. As shown in Figure 5A, different bacteria have different morphological characteristics. Moreover, red fluorescence can only be observed for P. aeruginosa (Figure 5B), and the result confirms the specific capturing of the designed 16S rDNA gene Probe on P. aeruginosa. Meanwhile, a low fluorescence intensity can be observed for E. coli 2571, E. coli 25922 and S. aureus (Figure 5C). In contrast, P. aeruginosa exhibits high fluorescence intensity. These results demonstrate the high specificity of the established method for the detection of P. aeruginosa. This can be attributed to the high selectivity of the 16S rDNA gene Probe for the detection of P. aeruginosa. To verify the practicability of the method, we use pure water, milk, grapefruit juice and green tea from a local supermarket as the sample sources to spike with different concentrations of P. aeruginosa. As shown in Figure 5D and Supplementary Table S3, the relative recovery varies between 90% and 110%, with a relative error of <8.7%, indicating that the constructed method can be used to analyze P. aeruginosa in real samples. The hydrazone chemistry-mediated CRISPR/Cas12a system can be easily used for the detection of other target genes, due to the sequence programmability of the target binding domain in the DNA probe. The hydrazone chemistry-mediated CRISPR/Cas12a system has been explored for the detection of S. aureus, and the corresponding experimental results are shown in Supplementary Figures S6, S7 and S8. Supplementary Figure S6 illustrates the detection principle of S. aureus through the hydrazone chemistry-mediated CRISPR/Cas12a system. Probe2 can specifically bind with TS3-NHNH2 to form Probe2/TS3-NHNH2 through complementary base pairing. 16S rDNA from S. aureus can bind with Probe2 through a strand displacement reaction, resulting in the release of TS3-NHNH2. With the formation of the hydrazine linkage, the released TS3-NHNH2 can react with TS4-CHO to give TS3/TS4, which can activate the CRISPR/Cas12a system so as to produce the fluorescence signal. The designed Probe2 can be successfully applied to image S. aureus (Supplementary Figure S7). Moreover, as shown in Supplementary Figure S8, in the absence of S. aureus, no fluorescent signal can be observed, confirming the stability of TS3-NHNH2 and TS4-CHO. In contrast, a high fluorescence peak appears in the presence of S. aureus. Therefore, the hydrazone chemistry-mediated CRISPR/Cas12a system can be developed to analyze S. aureus. These results signify that the system could be universal and can be used for other target genes. Additionally, almost no fluorescence can be found when using a scrambled sequence (s-Probe3) instead of the designed sequence (Probe2), confirming good specificity of the established method. Thus it can be seen that the hydrazone chemistry-mediated CRISPR/Cas12a system not only has good stability and universality, but also has good specificity for indirect detection of non-nucleic acid targets.
In conclusion, we have constructed a hydrazone chemistry-mediated CRISPR/Cas12a system and have explored its ability to distinguish single-base mismatches. Taking advantage of the proximity effect generated by complementary base pairing, the formation of hydrazone bonds can be accelerated. In view of its modularity and unique structural property, the pervasive and versatile hydrazone chemistry can link the split activated strand to the whole activated strand, so as to activate the CRISPR/Cas12a system effectively. Based on the system, a highly sensitive detection platform has been further developed and applied for bacterial detection. The developed platform is simple and sensitive, with a low detection limit and good specificity. Moreover, the platform can not only be applied for the detection of 16S rDNA in bacteria, but can also serve for direct detection of nucleic acid targets with the help of an aptamer or probe-based recognition cascade reaction. Meanwhile, the platform can also provide a stable and cost-effective assay system for indirect detection of other non-nucleic acid targets. So, the introduction of hydrazone chemistry can also broaden the scope of application of the CRISPR/Cas12a system.
All data supporting the findings of this study are available within the article and its supplementary information, or will be made available from the authors upon request.
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PMC9561369 | 36156150 | Lisa Lirussi,Dilara Ayyildiz,Yan Liu,Nicola P Montaldo,Sergio Carracedo,Miriam R Aure,Laure Jobert,Xavier Tekpli,Joel Touma,Torill Sauer,Emiliano Dalla,Vessela N Kristensen,Jürgen Geisler,Silvano Piazza,Gianluca Tell,Hilde Nilsen | A regulatory network comprising let-7 miRNA and SMUG1 is associated with good prognosis in ER+ breast tumours | 26-09-2022 | Abstract Single-strand selective uracil–DNA glycosylase 1 (SMUG1) initiates base excision repair (BER) of uracil and oxidized pyrimidines. SMUG1 status has been associated with cancer risk and therapeutic response in breast carcinomas and other cancer types. However, SMUG1 is a multifunctional protein involved, not only, in BER but also in RNA quality control, and its function in cancer cells is unclear. Here we identify several novel SMUG1 interaction partners that functions in many biological processes relevant for cancer development and treatment response. Based on this, we hypothesized that the dominating function of SMUG1 in cancer might be ascribed to functions other than BER. We define a bad prognosis signature for SMUG1 by mapping out the SMUG1 interaction network and found that high expression of genes in the bad prognosis network correlated with lower survival probability in ER+ breast cancer. Interestingly, we identified hsa-let-7b-5p microRNA as an upstream regulator of the SMUG1 interactome. Expression of SMUG1 and hsa-let-7b-5p were negatively correlated in breast cancer and we found an inhibitory auto-regulatory loop between SMUG1 and hsa-let-7b-5p in the MCF7 breast cancer cells. We conclude that SMUG1 functions in a gene regulatory network that influence the survival and treatment response in several cancers. | A regulatory network comprising let-7 miRNA and SMUG1 is associated with good prognosis in ER+ breast tumours
Single-strand selective uracil–DNA glycosylase 1 (SMUG1) initiates base excision repair (BER) of uracil and oxidized pyrimidines. SMUG1 status has been associated with cancer risk and therapeutic response in breast carcinomas and other cancer types. However, SMUG1 is a multifunctional protein involved, not only, in BER but also in RNA quality control, and its function in cancer cells is unclear. Here we identify several novel SMUG1 interaction partners that functions in many biological processes relevant for cancer development and treatment response. Based on this, we hypothesized that the dominating function of SMUG1 in cancer might be ascribed to functions other than BER. We define a bad prognosis signature for SMUG1 by mapping out the SMUG1 interaction network and found that high expression of genes in the bad prognosis network correlated with lower survival probability in ER+ breast cancer. Interestingly, we identified hsa-let-7b-5p microRNA as an upstream regulator of the SMUG1 interactome. Expression of SMUG1 and hsa-let-7b-5p were negatively correlated in breast cancer and we found an inhibitory auto-regulatory loop between SMUG1 and hsa-let-7b-5p in the MCF7 breast cancer cells. We conclude that SMUG1 functions in a gene regulatory network that influence the survival and treatment response in several cancers.
Single-strand selective uracil–DNA glycosylase 1 (SMUG1) forms the Family 3 of uracil–DNA glycosylases and is present in vertebrates, insects and some eubacteria (1,2). Although structurally related to two other uracil–DNA glycosylases, uracil–DNA glycosylase (UNG) and thymine–DNA glycosylase (TDG), the SMUG1 amino acid sequence diverges substantially. SMUG1 initiates repair of DNA base damage via the base excision repair (BER) pathway, removing uracil, both from single-stranded DNA as well as U:G mismatches and U:A pairs (3), and several pyrimidine oxidation products (e.g. 5-formyluracil (4,5), 5-carboxyuracil (6) and 5-hydroxymethyl uracil (5-hmU) (5,7,8)). SMUG1 has pan-nuclear localization with some enrichment in subnuclear structures, like nucleoli and Cajal bodies (9). We recently showed that UNG and SMUG1 act synergistically with respect to uracil repair in mouse (10), which shows that SMUG1 is important for uracil repair in vivo. Depending on their origin, SMUG1 substrates may have high mutagenic potential: uracil arising from cytosine deamination gives mutagenic U:G pairs which give rise to C-to-T transitions upon replication. A small, but additive mutagenic effect was found upon suppressing SMUG1 expression in Ung−/− mouse embryonic fibroblasts (MEFs) (10). Whole genome sequencing of thymic lymphomas arising in Ung/Smug1-deficient mice showed that loss of uracil BER led to both an expected accumulation of C-to-T transition mutations and a noticeable increase in transversion mutations at A:T base pairs likely contributed by mismatch repair (10). This suggests that SMUG1 has a role in protecting the genome from spontaneous mutations, but the impact on mutation accumulation is rather modest. When present in U:A pairs, uracil is read by replicative polymerases as a cognate T:A pair. Similarly, when 5-hmU is present in a 5-hmU:A base pair after direct oxidation of thymine it will likely not be mutagenic (11), but it might affect the binding of proteins such as transcription factors (12,13). The observation that C-to-T mutations in Ung/Smug1-deficient mice was found primarily in CpG dinucleotides suggests that SMUG1 might, indirectly, affect gene regulation. Similarly, the SMUG1 substrate 5-hmU, which might form as an intermediate of oxidative demethylation of 5-methylcytosine (5-mC) (14), might influence gene expression through epigenetic regulation. Thus, SMUG1 might influence cancer risk directly through an anti-mutagenic function and indirectly through gene regulation. Interestingly, several studies indicate that SMUG1 status is associated with modified cancer risk and response to therapy (15–17). Although SMUG1 appears to be constitutively regulated during the cell cycle (15), it is up-regulated in breast cancer and in breast cancer cell lines (overexpressed in 167 of 210 analyzed cancer cell lines, EMBL-EBI Gene expression Atlas, http://www.ebi.ac.uk/gxa/). Previous antibody based staining of breast cancer tissue arrays, suggested that low SMUG1 expression was correlated with aggressive breast cancer (16) and served, both, as an independent prognostic biomarker in ER+ breast cancers and as predictive marker for response to adjuvant chemotherapy (17). Potentially regulatory single-nucleotide polymorphisms within the SMUG1 gene were identified as independent prognostic factors that predicted poor survival in colon cancer (18,19) and as risk modifiers in bladder (20) and cervical carcinoma (21). Recently, analyses of tumor sequencing data indicated that mutations in the SMUG1 promoter correlate with an increase in C-to-T mutations in breast and colorectal cancer as well as melanoma (22). Hence, there are indications that SMUG1 expression might affect risk of cancer development and response to adjuvant therapy. The mechanisms behind these observations remains unknown, as current evidence suggests that the impact of SMUG1 on spontaneous mutagenesis is modest. Evidence from our laboratory indicates that SMUG1 might have a general function in RNA metabolism (9,23). Thus, SMUG1 appears as a multifunctional protein, potentially affecting many cellular functions including carcinogenesis, cancer pathogenesis and evolution. The present work aimed at exploring the association of SMUG1 expression with tumor progression and chemoresistance. We define a bad prognosis signature in different cancer types by mapping out a SMUG1 interaction network and identify the existence of an auto-regulatory loop between SMUG1 and let-7b-5p in breast cancer. As let-7-5p is an established risk modulator in breast cancer, it is likely that SMUG1 also modulates cancer risk and response to therapy through the regulation of gene expression.
MCF7, MDA-MB-231, BT-474 and HeLa cell lines were grown in Dulbecco's modified Eagle's medium, GlutaMAX (DMEM, Life Technologies) supplemented with 10% (vol/vol) fetal bovine serum (FBS, Lonza) and 1× penicillin–streptomycin (Life Technologies) whereas ZR-751 cells were cultured in Roswell Park Memorial Institute 1640 medium (RPMI1640, Life Technologies) containing 10% (vol/vol) FBS and 1× penicillin/streptomycin. Cells were grown at 37°C with 5% CO2.
The stable SMUG1 knockout (KO) cell lines (MCF7 and MDA-MB-231) were generated using CRISPR-Cas9 technology. Alt-R® CRISPR-Cas9 system (Integrated DNA Technologies) was used according to the manufacturers’ instructions. Briefly, the gRNA targeting the exon 3 of SMUG1 was created by annealing a tracrRNA (Integrated DNA Technologies) with SMUG1 specific crRNA (Integrated DNA Technologies). The gRNA was then incubated with HiFidelity Cas9 protein (Integrated DNA Technologies) to form individual ribonucleotide protein complexes (RNPs). The cell lines were electroporated with RNPs and seeded for colony formation. Electroporation was carried out as per manufacturers’ instructions (Neon® Transfection system, Thermo Fisher Scientific). After 10–15 days, colonies were picked and plated into 96-well plates. Clones emerging were collected and validated by sequencing (Eurofins Genomics) and by western blotting. The sequence of crRNA used for generating SMUG1 KO cells is provided below:-SMUG1 crRNA: 5′-GGGCATCATCTACAATCCCGGTTTTAGAGCTATGCT-3′
For overexpression and siRNA experiments, cells were seeded onto 6-well plates and transfected 24 h later. The construct used for SMUG1 overexpression was pcDNA3.1-SMUG1-Flag (Genscript) or pEYFP-N1-SMUG1 (Clontech); an empty vector was used in control transfections. For the rescue experiments, cells were electroporated with the Neon Transfection system (Life Technologies) following the manufacturers’ instructions; the constructs used were pHH25-SMUG1, pHH25-SMUG1 E29/31R or pHH25-SMUG1 H239L (23). For siRNA experiments, either a scrambled control or SMUG1 specific siRNAs were used (Ambion). For miRNA transfections, hsa-let-7b-5p mimic or inhibitor and negative control miRNAs were used (Life Technologies). FuGENE® 6 (Roche), Lipofectamine™ 3000 and Lipofectamine™ RNAiMAX (Invitrogen) transfection reagents were used as per manufacturer's indications. Transfected cells were harvested 24 or 72 h after transfection (siRNA treated).
ULTImate Y2H screening was performed at Hybrigenics Services per their standard protocols. Briefly, the coding sequence for full-length human SMUG1 (NM_001243787.1; aa 1–270) was PCR-amplified and cloned into pB29 plasmid (N-bait-LexA-C fusion) as a carboxy (C)-terminal fusion to LexA (LexA-SMUG1). The pB29-LexA-SMUG1 construct was used to screen a random primed human breast tumor epithelial cell cDNA library (RP1) cloned into the pB43 plasmid (N-bait-GAL4-C fusion). Each screen was performed to ensure a minimum of 50 million interactions tested.
Co-immuprecipitation experiments were carried out as previously described (9). Briefly, 2 × 107 cells were harvested and washed twice with ice-cold PBS. Cells were suspended in 500 μl lysis buffer (20 mM Tris–HCl pH 7.5, 400 mM KCl, 20% glycerol, 1 mM DTT, 1× Complete EDTA-free protease inhibitor cocktail) and incubated on ice for 10 min before three freeze-thaw cycles in liquid N2 and ice. Cellular debris were discarded by centrifugation at 15 000 × g for 15 min at 4°C and the whole cell extract was dialysed overnight at 4°C against 1 l dialysis buffer (25 mM Tris–HCl pH 7.5, 5 mM MgCl2, 100 mM KCl, 10% glycerol, 1 mM DTT, 0.5 mM PMSF). Approximately 1 mg cell lysate was used per immunoprecipitation. The cell lysates were preliminary treated with 160 U DNase I-RNase free for 30 min at 30°C. The cell lysates were then incubated with 50 μl anti-GFP antibody (Roche) overnight at 4°C. The following day, 40 μl Protein G Sepharose™ 4 Fast Flow (GE Healthcare) pre-equilibrated with IP buffer (25 mM Tris–HCl pH 7.9, 5 mM MgCl2, 10% glycerol, 0.1% NP-40, 1 mM DTT, 1× Complete EDTA-free protease inhibitor cocktail) containing 100 mM KCl was added and gently mixed for 2 h at 4°C. Immune complexes were washed three times with IP buffer containing 150 mM KCl and two times with IP buffer containing 100 mM KCl, each for 5 min at 4°C. Immunoprecipitates were boiled in SDS-sample buffer (25 mM Tris–HCl pH 6.8, 2% SDS, 10% glycerol, 0.05% bromophenol blue, 5% 2-mercaptoethanol) for 5 min, separated by SDS-polyacrylamide gel electrophoresis (PAGE), stained in colloidal Coomassie blue and subject to mass spectrometry.
Immunopurified proteins from total cell extracts from HeLa cell clones expressing the ectopic SMUG1-eGFP-tagged protein or transfected with the empty vector were processed in parallel. After staining with colloidal Coomassie blue, Coomassie G-250 stained gel pieces were in-gel digested with 0.2 μg trypsin (Promega) for 16 h at 37°C. The digestion was stopped by adding 5 μl 50% formic acid and the generated peptides were purified using a ZipTip C18 (Millipore), and dried using a Speed Vac concentrator (Concentrator Plus, Eppendorf). The tryptic peptides were dissolved in 10 μl 0.1% formic acid/2% acetonitrile and 5 μl analyzed using an Ultimate 3000 nano-HPLC system connected to a LTQ-Orbitrap XL mass spectrometer (Thermo Fisher Scientific) equipped with a nanoelectrospray ion source. For liquid chromatography separation, an Acclaim PepMap 100 column (C18, 3 μm beads, 100 Å, 75 μm inner diameter, 15 cm length) (Dionex) was used. A flow rate of 300 nL/min was employed with a solvent gradient of 4–35% B in 47 min, to 50% B in 20 min and then to 80% B in 2 min. Solvent A was 0.1% formic acid and solvent B was 0.1% formic acid/90% acetonitrile. The mass spectrometers were operated in the data-dependent mode to automatically switch between MS1 and MS2 acquisition. Survey full scan MS spectra (from m/z 300 to 2000) were acquired with the resolution R = 60 000 at m/z 400 (LTQ-Orbitrap XL), after accumulation to a target of 1e6. The maximum allowed ion accumulation times were 60 msec. The method used allowed sequential isolation of up to six most intense ions, depending on signal intensity (intensity threshold: 1.7e4), for fragmentation using collision induced dissociation (CID) at a target value of 10 000 charges in the linear ion trap of the LTQ-Orbitrap XL. Target ions already selected for MS2 were dynamically excluded for 60 s. For accurate mass measurements, the lock mass option was enabled in MS mode. Data were acquired using Xcalibur v2.5.5 and raw files were processed to generate peak list in Mascot generic format (*.mgf) using ProteoWizard. Database searches were performed using Mascot in-house version 2.2.0 to search the SwissProt database (Human, 20 411 proteins) assuming the digestion enzyme trypsin, at maximum one missed cleavage site, fragment ion mass tolerance of 0.6 Da, parent ion tolerance of 10 ppm, oxidation of methionines, acetylation of the protein N-terminus, pyroglutamate formation of N-terminal peptides with glutamine, and propionamide formation of cysteines as variable modifications.
After fixation with PFA 4% for 20 min at RT, Flag-tagged SMUG1 cells were permeabilized for 5 min in PBS 0.25% (vol/vol) Triton X-100. Cells were incubated in blocking solution (FBS 10% in TBS 0.1% [vol/vol] Tween-20) for 1 h at RT. Incubation with primary antibodies (anti-Flag (Sigma-Aldrich) and anti-SFPQ (Abcam), anti-MATR3 (Abcam), anti-RPLP0 (Abcam), anti-NPM1 (Abcam) or anti-DNA Ligase I (Abcam) diluted 1:200 in blocking solution) was carried out overnight at 4°C. After three washes in PLA Washing buffer A, PLA was performed following the manufacturer's protocol. Briefly, PLUS and MINUS PLA probes were diluted 1:5 in Duolink® Antibody diluent and added to the coverslips for 1 h at 37°C. Cells were washed twice in PLA Washing buffer A and the ligation step (ligase diluted 1:40 in Ligation buffer 1×) was carried out for 30 min at 37°C followed by amplification (Polymerase diluted 1:80 in Amplification buffer 1×) for 100 min at 37°C. Coverslips were washed twice in PLA Washing buffer B for 10 min each, in PLA Washing buffer A for 1 min and counterstained for SFPQ, MATR3, RPLP0 or DNA Ligase I, incubating the cells with Alexa Fluor 488 conjugated anti-rabbit (Life Technologies) for 2 hr at RT. Cells were washed twice in PLA Washing buffer A for 2 min, rinsed with PLA Washing buffer B 0.01× and mounted with Prolong Diamond Antifade mounting medium. Technical control, represented by the omission of the anti-Flag antibody, resulted in loss of PLA signal.
Primary antibodies used for immunofluorescence were SFPQ (1:200, Abcam), MATR3 (1:200, Abcam), RPLP0 (1:500, Abcam), DNA Ligase I (1:200, Abcam), NPM1 (1:500, Abcam) and Flag (1:200, Sigma-Aldrich). Secondary antibody for immunofluorescence (Alexa Fluor 488 conjugated goat-anti-rabbit) was purchased from Life Technologies. Immunoblotting was carried out using the following antibodies: SMUG1 (1:2000, Abcam) and α-Tubulin (1:3000, Sigma-Aldrich) or GAPDH (1:2000, Cell Signaling Technology) as loading controls.
Whole-cell lysates were prepared in RIPA buffer [10 mM Tris–HCl (pH 8.0), 140 mM NaCl, 1 mM EDTA (pH 8.0), 0.5 mM EGTA, 0.1% SDS (wt/vol), 0.1% sodium deoxycholate (wt/vol) and 1% Triton X-100 (vol/vol)] containing protease inhibitors (Sigma-Aldrich). Protein extracts were run on any kD Mini-PROTEAN TGX precast gel (Bio-Rad) and blotted on nitrocellulose membrane. Blots were blocked in 5% non-fat milk dissolved in 1x PBS, 0.1% Tween-20 (blocking solution). After the incubation with the specific primary antibody, secondary antibody incubation was carried out for 1 h (1:3000 in blocking solution) at RT. Blots were developed with SuperSignal West Pico Chemiluminescent substrate (Thermo Scientific). The chemiluminescent signals were detected with a ChemiDoc Imaging system (BioRad).
Total RNA was isolated with miRNeasy mini kit (Qiagen) following the manufacturer's instructions. Reverse transcription was performed using High-Capacity cDNA Reverse Transcription kit (Applied Biosystems). Quantitative PCR was carried out on a QuantStudio 7 Flex detection system (Applied Biosystems) with the Power SYBR green PCR master mix (Applied Biosystems). Each sample was analysed in triplicate. Primer sequences are provided in Supplementary Table S1.
microRNA specific qPCR assay was performed as described previously (24) with minor modifications. Briefly, following treatment of MCF7 with siRNAs or miRNAs, cells were rinsed in PBS, scraped from the wells and lysed in 700 μl of Qiazol. Cellular RNAs were isolated using the miRNeasy mini kit (Qiagen) by following manufacturer's instructions. For elongating miRNAs, 1 μg of total RNA was diluted in 4 μl of nuclease free water, mixed with 4 μl of Elongation mix (1× T4 Rnl2 Buffer (New England Biolabs), 5 μM MgCl2, 15% PEG 8000, 1.5 μM miLINKER (Integrated DNA Technologies), 4U RNase inhibitor (Life Technologies) and 40U Rnl2tr K227Q (New England Biolabs)) and incubated for 2 h at 25°C. At the end of the incubation, 12 μl of cDNA Synthesis mix (1× RT buffer, 2 μl mQ-RT primer (Life technologies), 1× dNTPs, 1 μl MultiScribe™ Reverse Transcriptase and 6 μl of nuclease free water) were added to each sample and reverse transcription was carried out as per manufacturer's instructions. cDNAs were then diluted 200 times and qPCR/ddPCR assays were performed. Primer sequences are provided in Supplementary Table S2.
MCF7 cells silenced for SMUG1 or treated with control siRNAs (72 h) were pulsed for three hours with 4-thiouridine (4sU, Sigma) at a final concentration of 150 μM. After 3 h, media was changed in normal DMEM High Glucose and cell pellets collected at different time points (up to 12 h).
Total RNA was isolated using the miRNeasy kit (Qiagen) following the manufacturer's procedure. The protocol followed for the half-life measurement was performed as described previously (25) with few modifications. Briefly, 100 μg 4sU-labeled RNA were used for the biotinylation reaction. Biotinylation reactions were carried in labeling buffer (10 mM Tris pH 7.4, 1 mM EDTA pH 8.0) and 0.2 mg/ml EZ-Link Biotin-HPDP (Pierce) for 2 h at 25°C. Unbound Biotin-HPDP was removed by chloroform/isoamylalcohol (24:1) extraction using MaXtract (high density) tubes (Qiagen), following the kit procedure. RNA was precipitated adding an equal volume of isopropanol and 1:10 volume of 5M NaCl; samples were then centrifuged 17 000 × g for 20 min. The pellet was washed with an equal volume of 75% ethanol and precipitated again at 17 000 × g for 10 min. The pellet was resuspended in 100 μl RNase-free water. Biotinylated RNA was captured using Dynabeads MyOne Streptavidin T1 beads (Invitrogen). Biotinylated RNA was incubated with 100 μl Dynabeads with rotation for 15 min at 25°C. Beads were magnetically fixed and washed with 1 × Dynabeads washing buffer (5 mM Tris pH 7.5, 0.5 mM EDTA pH 8.0 and 1M NaCl). cDNA synthesis of the captured RNA-4sU was performed on beads using the SuperScript VILO cDNA synthesis kit (Life technologies), adding in the mastermix the RT probe for TaqMan® Assay for hsa-let-7b-5p (Life Technologies).
The cDNA was assayed via ddPCR using Droplet Digital PCR QX system (Bio-Rad). Briefly, the cDNA was added to a 20 μl PCR mixture containing 10 μl 2x QX200 ddPCR Supermix for Probes (No dUTP) (Bio-Rad) and 1 μl of TaqMan® Assay for hsa-let-7b-5p (Life Technologies). 20 μl of PCR mixture and 70 μl Droplet generation oil for Probe (Bio-Rad) were mixed. Droplets were generated using a QX100 Droplet Generator (Bio-Rad). The following PCR conditions were used: after enzyme activation at 95°C for 10 min, 40 cycles at 94°C for 30 s and 60°C for 1 min were followed by 1 step at 98°C for 10 min. Reactions were read in the QX200 Droplet Reader (Bio-Rad).
RNA immunoprecipitation assay was performed as described previously (9) with minor modifications. Briefly, cells were washed twice in PBS and cross-linked in 1% formaldehyde–1× PBS for 10 min at room temperature. Glycine (pH 2.5) was added to 0.2 M in order to quench the reaction before washing the cells twice with ice-cold PBS. Cells were lysed in lysis buffer A [50 mM HEPES (pH 7.8), 1 mM EDTA (pH 8.0), 1% Triton X-100 (vol/vol), EDTA-free protease inhibitor complex] and sonicated for 10 cycles with 30 s ON and 30 s OFF per cycle using a Bioruptor (Diagenode). The sonicated lysate was diluted in 1 volume of lysis buffer B [50 mM HEPES (pH 7.8), 1 mM EDTA (pH 8.0), 50 mM MgCl2, 10 mM CaCl2, 0.4 U/μl RNaseOUT recombinant ribonuclease inhibitor (Invitrogen)]. DNA was digested with DNAse I RNAse free (Life Technologies) at 37°C for 15 min and digestion was stopped adding 20 mM EDTA (pH 8.0). The lysate was centrifuged at 4°C for 5 min at 20 000 × g. The supernatant was incubated with SMUG1 and normal rabbit IgG covalently coupled to Protein G dynabeads (Invitrogen). The RIP was performed at 4°C overnight. Beads were washed once with Binding buffer [50 mM HEPES (pH 7.8), 20 mM EDTA (pH 8.0), 0.5% Triton X-100 (vol/vol), 25 mM MgCl2, 5 mM CaCl2], FA500 buffer [50 mM HEPES (pH 7.8), 1 mM EDTA (pH 8.0), 1% Triton X-100 (vol/vol), 500 mM NaCl, 0.1% Na-deoxycholate (wt/vol)], LiCl buffer [10 mM Tris–HCl (pH 7.5), 1% Triton X-100 (vol/vol), 1 mM EDTA (pH 8.0), 250 mM LiCl, 0.5% Na-deoxycholate (wt/vol)] and TES buffer [10 mM Tris–HCl (pH 7.5), 1 mM EDTA (pH 8.0), 10 mM NaCl]. RNA–protein complexes were eluted twice with 2.5 bead volumes of Elution buffer [100 mM Tris–HCl (pH 7.8), 10 mM EDTA (pH 8.0), 1% SDS (wt/vol)] for 10 min at 37°C. RNA-protein complexes and input samples were reverse-crosslinked with 200 mM NaCl for 1 h at 65°C and incubated at 42°C for 1 h after adding 20 μg proteinase K. The RNA was extracted with Trizol solution (Invitrogen) and analyzed by qPCR as percentage of input.
MCF7 cells silenced for SMUG1, treated with hsa-let-7b-5p mimic miRNA (24 hr), or SMUG1 KO cell lines (MCF7 and MDA-MB-231) were harvested and seeded as single-cell suspension in six multi-well plates (1000 cells/well for MCF7 and 400 cells/well for MDA-MB-231). Cells were incubated at 37°C with 5% CO2 for twelve days. Cells were then fixed and stained with 0.3% crystal violet (Sigma-Aldrich) in 70% ethanol for 30 min at RT. The number of colonies were counted. Six wells were set up per each condition.
MCF7 cells silenced for SMUG1, treated with hsa-let-7b-5p mimic miRNA (48 h), or MCF7 SMUG1 KO cell lines were serum starved for 16 h. A scratched area was created using a sterile 200 μl pipette tip and cells were incubated in complete medium for 48 h. The migration capacity of the cells into the wound area was monitored by acquiring images with an inverted microscope at different time points (0, 6, 24, 36 and 48 h). Wound closure was quantified by measuring the wound area at the different time points using ImageJ software and presented as the percentage relative to the initial scratched area.
0.5 × 106 SMUG1 knock-down cells (MCF7) or SMUG1 KO cell lines (MCF7 and MDA-MB-231) were collected, washed once in cold PBS and fixed in ice-cold 70% ethanol. Cells were stored overnight at –20°C. The cells were centrifuged, washed twice in cold PBS and stained with a solution containing 0.04 mg/ml propidium iodide (PI, Sigma-Aldrich), 0.1 mg/ml ribonuclease A (Sigma-Aldrich) in PBS. Samples were incubated at 25°C for 30 min in the dark. Cell cycle distribution was determined by flow cytometry analysis (FACSCanto™ II, BD Biosciences). Cells were analyzed using FlowJO™ v10.8 software (BD Biosciences). Forward scatter (FSC-A) and side scatter (SSC-A) were used to identify cell population while PI fluorescence pulse area (PI-A) and PI fluorescence pulse width (PI-W) were used to identify single cells. Cell cycle distribution were analyzed in PI histogram plots. Data is available in FlowRepository under the following accession codes: FR-FCM-Z5F8 (Cell cycle analyses on MCF7 siSMUG1), FR-FCM-Z5FA (Cell cycle analyses on MCF7 overexpressing hsa-let-7b-5p), FR-FCM-Z5FC (Cell cycle analyses on MCF7 SMUG1 KO), and FR-FCM-Z5FD (Cell cycle analyses on MDA-MB-231 SMUG1 KO).
WT and SMUG1 KO MDA-MB-231 cells were serum starved for 16 h, trypsinized and resuspended in serum-free medium. Cells were seeded 5 × 104 cells/well in the upper chamber of a 24-well insert with 8-μm membrane (Corning). Growth medium supplemented with 15% FBS was used as an attractant in the lower chamber. After 24-h incubation, cell migrated through the membrane were fixed and stained with 0.3% crystal violet (Sigma) in 70% ethanol for 30 min at RT. Images were captured by microscope using a 10× magnification and six random fields were counted.
MCF7 cells (WT and SMUG1 KO clones) were seeded at sub-confluent density (2 × 104 cells/well) in collagen IV-coated 96-well glass bottom plates (Merck). Coating was carried out by treatment of each well with 20 μg/ml of collagen IV (Merck) in PBS at 4°C for 20 h. After seeding, the plates were placed in a CO2 incubator for 6 h to allow cells to attach to the collagen-coated glass surface. Subsequently, cells were placed in an ImageXpress Micro Confocal high-content microscope controlled by the MetaXpress 6 software and equipped with an environmental chamber maintaining 5% CO2 and 37°C (Molecular Devices). Time lapse series of phase contrast images were acquired using a 20 × 0.45 NA Ph1 air objective, camera binning = 2, a frame rate of 3 min between frames and a total imaging period of 12 h. Time lapse series were analyzed by particle tracking using the TrackMate plugin in Fiji ImageJ (26,27) in combination with an in-house Python-based script (Python 3.7.6). Average displacement speed was calculated as the average of all tracked cell displacements within a 12 h period of imaging.
The list of SMUG1-interacting partners was used to construct the corresponding PPI network by defining the interactions between the partners using the InWeb_InBioMap tool, applying the suggested parameters (28). The SMUG1-PPI network was represented as an undirected graph (i.e. nodes and edges symbolize proteins and interactions between them, respectively), and it was visualized via Cytoscape (v3.6.1) (29). The network enrichment analysis was performed using the ClueGO tool, using standard parameters (30). The hubs of the network were obtained by using the Cytohubba tool based on the global metric, betweenness centrality (31).
The differential gene expression results from TCGA and normal datasets (GTEX data) for the genes encoding the proteins in the SMUG1-PPI network were obtained via the GDC data portal hub (https://portal.gdc.cancer.gov/, last accessed July 2018). In order to better estimate the differentially expressed genes between the tumor and the corresponding normal datasets, we obtained ‘in-silico empirical’ negative controls, i.e. the least significantly DE genes based on a first-pass DE analysis performed prior to RUVg normalization (32). Pearson correlations were calculated between the gene expression profiles of SMUG1 and SMUG1-PPI in cancer patients or in the control groups using the stats package inside the R/Bioconductor environment.
The list of genes positively and negatively correlated with SMUG1 in breast cancer RNA-seq data (TCGA–BRCA, n = 1034; SCAN-B/GSE96058, n = 3273; SCAN-B/GSE81538, n = 405, for a total patients n = 4712) was obtained using the online correlation module of Breast Cancer Gene Expression Miner dataset v4.3 (http://bcgenex.ico.unicancer.fr/BC-GEM/GEM-Requete.php) (33). Pathway enrichment analysis was done using g:Profiler (34) and visualized with the Cytoscape Enrichment Map application (35) as described in (36). Clusters of nodes were labelled using the AutoAnnotate Cytoscape application (37).
Normalized mRNA and miRNA expression data, together with clinical data (PAM50 subtypes and estrogen receptor (ER) status) for the TCGA cohort, were downloaded from the Xena browser (https://xenabrowser.net/datapages/). Altogether, 747 tumor samples had matching mRNA and miRNA data. Spearman's rank correlation was used to compute the correlation between SMUG1 mRNA and miRNA expression. Spearman's rank correlations between SMUG1 and hsa-let-7b-5p/hsa-let-7c-5p expression were computed in R and visualized as dot plots (https://www.R-project.org/).
For the TCGA–BRCA dataset, differentially expressed genes (multiple correction adjustment using the Benjamini–Hochberg method, Padj < 0.05; absolute log fold change difference ≥ 1) corresponding to SMUG1 interacting partners and SMUG1 median expression were used to perform survival analyses. Kaplan–Meier plots were drawn using the RTCGA Bioconductor package, which uses maximally selected rank statistics (maxstat) to determine the optimal cutpoint for continuous variables. Samples stratification was done within the 30–70% percentile range of gene expression by the optimal cutpoint value. The Benjamini-Hochberg method was used for p-value correction of Kaplan–Meier plots.
miRNAs targeting the gene sets for selected cancer-specific PPI sub-modules were retrieved by miRWalk (38). Only experimentally validated miRNAs (from Mirtarbase) having miRWalk score higher than 0.95 were selected. The functional enrichment analysis of miRNAs was achieved by using mirPath v3.0 from the DIANA Tools (39).
Formalin-fixed, paraffin-embedded breast tumor samples from 66 breast cancer patients were collected at Akershus University Hospital, Norway. Individual data and information on primary and advanced disease were collected from electronic health records and treated anonymously according to strict privacy standards. Ethical permission for this study was approved by the regional ethical committee of south-east Norway (No. 2014-895).
Chromogenic in situ Hybridization (CISH) for hsa-let-7b-5p was carried out using miRNAscope™ HD Assay Red (ACD). Briefly, 4 μm-thick FFPE tissue sections were baked in dry oven for 1 h at 60°C. Sections were deparaffinized in xylene, and post-fixed in 10% neutral buffered formalin overnight, followed by RNAscope® hydrogen peroxide incubation for 10 min. Heated target retrieval was perfomed in RNAscope® 1× Target Retrieval Reagent for 15 min. Sections were then transferred into ACD EZ-Batch™ slide holder and incubated with RNAscope® Protease Plus at 40°C for 30 min within HybEZ™ Humidifying system. Hsa-let-7b-5p probe (ACD) were then added for 2 h at 40°C. miRNAscope™ Positive Control Probe-SR-RNU6-S1 and miRNAscope™ Negative Control Probe-SR-Scramble-S1 were added on separate FFPE control slides for 2 h at 40°C. Signal amplification Amp1-6 were applied sequentially and incubated 15 or 30 min according to the manufacturer's instruction. Fast red working solution was added for 10 min to detect the red signal. The samples were then counterstained with hematoxylin and mounted with EcoMount. Whole slide images were scanned at 40× using Aperio ScanScope AT. Tissue sections were examined under a standard bright field microscope at 40× magnification and scored by semi-quantitative scoring guideline utilizing the estimated number of punctate dots present within each cell boundary (score 0, no staining or less than 1 dot/cell; score 1, 2–10 dots/cell; score 2, 11–20 dots/cell and score 3, >20 dots/cell).
Briefly, antigen retrieval was performed with EnVision™ FLEX Target Retrieval Solution, low pH (Dako) for 20 min at 97°C in PT-Link station (Dako); endogenous peroxidase activity was quenched by incubating the slides in EnVision™ FLEX peroxidase blocking reagent (Dako) for 10 min; miRNAscope™ Negative Control Probe-SR-Scramble-S1 was added for 2 h at 40°C; Protein block (Histolab) was incubated for 10 min; then SMUG1 (Origene) was diluted 1:200 in 5% bovine serum albumin (BSA, Merk) and slides were incubated for 1 h at 40°C; donkey anti-goat IgG-HRP secondary antibody (Santa Cruz) was diluted 1:1000 in 5% BSA and added on slides for 1 h at RT; at last, sections were reacted with 3,30‐diamino‐benzidine tetrahydrochloride (DAB) solution (Dako) for 10 min and counterstained with hematoxylin (Dako) for 10 min. The total scores of SMUG1 were calculated by multiplying the staining intensity for the individual scores of the positive cells (40). Scores of positive cells were defined as: 0 (≤5%); 1 (5–24%); 2 (25–49%); 3 (50–74%) and 4 (>75%). Staining intensity scores were defined as follows: weak (1 point); medium (2 points); and strong (3 points). The total score is divided into the following levels: −, 0 points; +, 1–4 points, ++, 5–8 points; +++, ≥9 points where ‘−’ and ‘+’ are considered low expressions, and ‘++’ and ‘+++’ high expressions. The IHC results were evaluated by two independent pathologists blinded of clinical information.
All quantified data are presented as mean ± s.e.m., mean ± s.d. and fold change unless stated otherwise (refer to figure legends for detailed information). Student t-test or one-way ANOVA were used to assess the statistical significance in GraphPad Prism 7 (GraphPad software). A P <0.05 was considered as statistical significant. P values were indicated with asterisks. Replicates, statistical tests carried out and statistical significances are reported in the corresponding figure legends. The Kaplan–Meier estimator and log-rank tests were performed using the functions Surv, survfit, and survdiff (R package survival v2.42–3). In the box-and-whisker plots, the line within each box represents the median. Upper and lower edges of each box represent 75th and 25th percentile, respectively. The whiskers represent the lowest datum still within [1.5 × (75th − 25th percentile)] of the lower quartile and the highest datum still within [1.5 × (75th − 25th percentile)] of the upper quartile.
Reduced levels of SMUG1 mRNA and protein were previously correlated with increased aggressiveness and poor prognosis in primary breast cancers, pointing at SMUG1 as a possible negative prognostic marker for adjuvant therapy in breast tumors (16). However, previous studies showed a very modest increase in spontaneous mutagenesis when SMUG1 expression was suppressed in MEFs (41). This suggested to us that the negative correlation between SMUG1 and poor prognosis, if causal, might be ascribed to functions of SMUG1 other than its anti-mutagenesis properties. To further explore the possible underlying mechanisms, we first analyzed SMUG1 expression levels in breast tumor vs adjacent normal tissues in the TCGA–BRCA cohort (Figure 1). When considering all breast tumor samples as one group we found increased SMUG1 mRNA levels compared to normal breast tissue (Figure 1A). As estrogen receptor (ER) positive breast tumors have a very different biology than ER negative tumors, we further stratified SMUG1 expression according to ER status and found that ER+ tumors showed significant increase of SMUG1 mRNA levels when compared to both ER− and normal adjacent tissue (Figure 1B and Supplementary Figure S1). Breast cancer-specific mortality stratified by high or low SMUG1 expression levels was assessed using Kaplan–Meier plots (Figure 1C and Supplementary Figure S2). Surprisingly, for the breast cancer cohorts we analyzed (with at least 100 patients included), low SMUG1 mRNA expression levels were associated with better survival compared to patients with high levels of SMUG1. Although not always significant, the same trend was observed in all 7 cohorts analyzed (Figure 1C and Supplementary Figure S2). Interestingly, improved survival with low SMUG1 expression was more pronounced for ER+ samples (Figure 1C and Supplementary Figure S2). While it is clear that patients with better prognosis tended to have a lower SMUG1 expression, it also appeared that SMUG1 expression alone cannot be used as an independent predictor of survival for breast cancer as, in contrast to previously reported (16), the multivariate cox regression analyses were not significant. If SMUG1 has an indirect role in cancer development, we would expect its expression to be correlated with gene expression programs associated with oncogenesis. Genes positively and negatively correlated with SMUG1 in breast cancer RNA-seq data were identified using the online correlation module of Breast Cancer Gene Expression Miner dataset v4.3 (http://bcgenex.ico.unicancer.fr/BC-GEM/GEM-Requete.php) (Supplementary Table SI, worksheet ‘Gene_correlation_table’) (33). Gene ontology (GO) analyses of these genes did not show any enrichment for classical pathways associated with oncogenesis, pointing instead to mitochondrial electron transport and respiratory processes as main pathways associated with genes co-expressed with SMUG1 in breast cancer (Supplementary Figure S3). In addition, also regulation of T cells, immune response and fatty acid transport were enriched (Supplementary Table SI, worksheet ‘GO_enrichment_table’).
SMUG1 is a multifunctional protein involved in RNA quality control as well as in DNA repair (9,23,42). We therefore investigated whether the functional impact of SMUG1 in breast cancer might be defined, not only through SMUG1 expression, but also through the expression and activity of the complex network of SMUG1 involving its interacting partners. Although a few protein and RNA partners of SMUG1 are known (9,23), the SMUG1 interactome is still poorly defined, in particular with respect to protein-protein interactions. Thus, to gain a deeper understanding of the possible role of SMUG1 in breast cancer, we identified novel SMUG1 interactors using yeast two-hybrid (Y2H) and co-immunoprecipitation followed by mass spectrometry approaches (Figure 2A). First, we identified binary in vivo protein-protein interactions (PPI) taking advantage of a high throughput Y2H screen using a breast cancer library as bait. To expand the dataset of SMUG1 PPIs, the list of positive hits from the Y2H screen (ELAVL1, EXOC6 and GPN3) was complemented with SMUG1-associated proteins identified through mass spectrometric analyses following co-immunoprecipitation of eGFP-SMUG1 in HeLa cells. In sum, a list of 534 potential SMUG1 interactors were identified (Supplementary Table SII, worksheet ‘SMUG1_PPI_HeLa’). Direct protein-protein interaction with SMUG1 was confirmed via Proximity Ligation assay (PLA) for selected interactors involved in RNA metabolism (MATR3, RPLP0, NPM1 and SFPQ) and DNA repair (DNA Ligase I) (Figure 2B and Supplementary Figure S4). The list of interactors was, next, used to establish a SMUG1-PPI network (Supplementary Table SII, worksheet ‘SMUG1_PPI_total’). Direct and/or indirect interactions between these molecules were retrieved by the InWeb_InBioMap web tool, giving rise to undirected PPI network with 525 nodes and 5685 edges (data not shown). Gene ontology analyses for functional gene enrichment based on biological process (BP) identify 389 unique IDs. The enriched BP are consistent with functions of SMUG1 in DNA and RNA metabolism, but also, suggested a role for SMUG1 in protein metabolism/stability (Figure 2C and Supplementary Table SIII). This complex PPI-network was then further analyzed focusing on its most critical elements, by performing a hub analysis based on the betweenness centrality metric, a measure of how often a node occurs on all shortest paths among pairs of nodes in a network, meaning the importance of each node/protein for the connectivity of the network (43). The resulting top 30 hub nodes were extracted from the main SMUG1-PPI network as hub-subnetworks (Figure 2D and Supplementary Table SIV). This hub module was then analyzed with ClueGO to categorize these genes/IDs in the GO biological processes (Supplementary Table SIV). As shown in Figure 2C, ribonucleoprotein complex biogenesis, RNA processing/splicing and regulation of cellular protein metabolism were the most enriched processes, for the global network. Taken together, this analysis revealed a prominent representation of RNA and protein metabolism within the SMUG1-PPI network, suggesting that SMUG1 may act as a central hub connecting the different subnetworks with diverse functions.
In order to evaluate whether the association with poor/good prognosis improved when considering SMUG1-interactome in breast and other cancer types, we interrogated TCGA cancer cohorts. The genes that were significantly differentially expressed (Padj < 0.05, absolute log fold change > 1) and significantly correlated (P < 0.05, absolute Pearson correlation > 0.6) with the expression profile of SMUG1 were calculated through the analysis of 33 TCGA datasets (Supplementary Table SV and Table S3). To assess whether the SMUG1 interactome correlated more consistently with clinical outcomes than SMUG1 expression alone (Figure 1C), Kaplan–Meier plots were obtained for each gene in each dataset, allowing us to define good and bad prognosis gene signatures on a per cancer basis. The distribution of the differentially expressed genes with respect to good or bad prognosis (P < 0.05) signature per cancer datasets are summarized in Supplementary Table SVI. Six datasets, having different ratios in the number of bad-good prognosis genes (higher number of bad prognosis genes: hepatocellular carcinoma [LIHC] and human skin cutaneous melanoma [SKCM]; similar number of genes between bad and good prognosis: acute myeloid leukemia [LAML] and lower grade glioma [LGG]; lower number of bad prognosis genes: breast cancer [BRCA] and glioblastoma [GBM]) were analyzed further. In general, the SMUG1 interactome did not show any defined prognostic signature in the majority of the datasets analyzed: although a few datasets (i.e. LIHC and SKCM) showed a clear bad prognosis signature (Supplementary Figure S5A and Supplementary Tables SV and VI). This suggests that additional regulators might affect the prognosis. In fact, although the number of genes for good and bad prognosis are similar in the TCGA–BRCA dataset, Kaplan–Meier analysis using the survival outcomes of patients having high/low expression of the bad prognosis genes (n = 85) showed that high expression of the bad prognosis genes was significantly associated with lower survival probability (P < 0.0001) (Supplementary Figure S5B and Table SV, worksheets ‘BRCA’; ‘Report’). To assess the possibility these gene sets have common upstream regulators, we used the miRWalk tool to identify common miRNA regulators. We found that 36 miRNAs target the highest number of genes in each bad prognostic network (Figure 3A and Supplementary Table SV, worksheet ‘Heatmap’). Among the top 10 miRNAs of all datasets, miR-92a-3p, hsa-let-7b-5p, miR-149-5p, miR-193b-3p, miR-615-3p and miR-320a target the highest number of genes in these networks (Figure 3A). Gene Ontology analyses indicate the involvement of these miRNAs in several biological processes relevant for cancer biology, such as epigenetic regulation of gene expression and maintenance of differentiation (Figure 3B and Supplementary Table SVII).
A clear role for the let-7 miRNA family as tumor suppressors has been demonstrated (44) and patients with breast cancer showed dysregulated levels of hsa-let-7b-5p and hsa-let-7c-5p (44–47). For this reason, we interrogated the TCGA breast cancer dataset with respect to a possible correlation existing between SMUG1 levels and these two members of the let-7 family, hsa-let-7b-5p and hsa-let-7c-5p, hereafter named let-7b-5p and let-7c-5p. Interestingly, only let-7b-5p had a weak but significant negative correlation with SMUG1 levels (Spearman's rho = –0.18, correlation P-value = 7.2e−7; Figure 3C), in particular in Luminal A and B datasets (Supplementary Figure S6) that also have the highest SMUG1 expression level (Supplementary Figure S1). This suggests a potential co-regulatory mechanism between SMUG1 and let-7b-5p.
Prompted by the negative association existing between SMUG1 and let-7b-5p, as observed in the TCGA breast cancer data, we studied the possible co-regulation of SMUG1 and let-7b-5p in MCF7 cells, a well-established breast adenocarcinoma cell line expressing both estrogens and progesterone receptors. As SMUG1 binds RNA molecules (9,23), we asked if SMUG1 physically interacts with let-7b-5p. In RNA-immunoprecipitation experiments (RNA-IP), we detected statistically significant enrichment of let-7b-5p using an anti-SMUG1 antibody compared to the immunoglobulin G (IgG) control (Figure 4A). Interestingly, SMUG1 also binds miR-92a-3p in vivo, the only common upstream miRNA in all the TCGA datasets considered (Figure 3A), as expected due to its overexpression in malignant tumors (48), and other members of the let-7 microRNA family (Supplementary Figure S7A). We then checked the expression levels of let-7b-5p and of the other miRNAs bound by SMUG1 in MCF7 cells transiently silenced for SMUG1 (Figure 4B and C and Supplementary Figure S7B and C). As seen in Figure 4C, the let-7b-5p expression increased in SMUG1 knock-down cells. Increased expression of let-7b-5p in SMUG1 knock-down cells, was also confirmed in three other breast cancer cell lines (MDA-MB-231, BT-474 and ZR-751), confirming a role for SMUG1 in let-7b-5p regulation (Supplementary Figure S8). Interestingly, the same behavior was also observed for the other miRNAs bound by SMUG1 (Supplementary Figure S7C), suggesting that SMUG1 may have a role in miRNA processing or degradation. Considering the function of SMUG1 in regulating hTERC maturation and processing (23), we followed the let-7b-5p maturation process from pri-/pre-let-7b to the mature form (Figure 4D). We measured the levels of mature let-7b-5p and the two immature forms, pri-let-7b and pre-let-7b (Figure 4D). Transient silencing of SMUG1 did not affect the ratio between mature and pri-let-7b (Figure 4D, left), but a significant reduction in mature vs pre-let-7b ratio was observed in several cell lines (Figure 4D, right, and Supplementary Figure S8G–I). Taken together, these data suggest that the precursor transcripts, in the form of pre-let-7b, accumulate in SMUG1-depleted cells, pointing to a role for SMUG1 during miRNA processing from pre-miRNA to the mature form. In vivo metabolic labeling experiments showed an increased stability of let-7b-5p in SMUG1 knock-down cells further confirming not only an increase of let-7b-5p expression but also activity (Figure 4E), and indicating that post-transcriptional processing might be responsible for the expression levels and stability of let-7b-5p in the absence of SMUG1. To test whether SMUG1 substrates might be present in let-7b-5p molecules, we used a previously described assay based on reduced amplification of transcripts containing modified bases after SMUG1 digestion (23). No reduction in amplification for let-7b-5p was observed between siCTRL and siSMUG1 cells, indicating the absence of SMUG1 substrates in let-7b-5p (data not shown). In order to test the functional impact on the let-7b-5p-mRNA regulatory axis, we selected some known let-7b-5p target mRNAs associated with pluripotency and proliferation (LIN28A, CCNB2, PLK1 and CCNA2) (49) and analyzed their expression profile via qRT-PCR in siCTRL and siSMUG1 cells. As expected, increased let-7b-5p miRNA levels corresponded to significantly decreased mRNA levels in siSMUG1 cells, indicating that let-7b-5p negatively regulated the expression of LIN28A, CCNB2, PLK1 and CCNA2 (Figure 4F). Considering the negative correlation between SMUG1 and let-7b-5p and the increased levels of SMUG1 in breast cancer samples, the mRNA of genes regulated by let-7b-5p should be upregulated. We therefore investigated the mRNA expression levels of these genes (LIN28A, CCNB2, PLK1 and CCNA2) in normal and BRCA cancer specimens by GEPIA (Figure 4G). All the genes showed a higher expression in BRCA samples than controls (Figure 4G). Interestingly, correlation analyses of SMUG1 mRNA expression and the mRNAs of these downstream targets of let-7b-5p showed significant positive (although weak) correlations in ER+ tumors (Supplementary Figure S9). Hence, SMUG1 affects let-7b-5p levels and their expression is negatively correlated in breast cancer (Figures 3C and 4C).
Prompted by our previous results, we suspected that SMUG1 mRNA itself might be a let-7b-5p target. Indeed, TargetScan predicted the presence of a let-7b-5p target sequence 1.75 kb into the SMUG1 3’UTR (Figure 4H). Validation of SMUG1 as a let-7b-5p target was also confirmed in other tissues as kidney, bone marrow, mammary gland and cervix using the online DIANA-TarBase v8 tool (50). Partial inhibition of let-7b-5p did not affect SMUG1 expression, probably due to the amount of endogenous let-7b-5p left (Figure 4I, J and Supplementary Figure S10A). However, overexpression of let-7b-5p mimic in MCF7 cells led to significant reduction of SMUG1 mRNA and protein levels (Figure 4I, J and Supplementary Figure S10B). Together, these data support a negative regulation loop between let-7b-5p and SMUG1 in breast cancer samples.
Previous studies suggested a role for let-7b-5p as tumor suppressor in breast cancer development and progression (51–53). Thus, we tested the impact on SMUG1 knockdown, and its consequent increased level of let-7b-5p, on cell proliferation and migration (Figure 5). We first looked at cell proliferation in MCF7 transiently silenced for SMUG1 and overexpressing let-7b-5p. Increased levels of the microRNA caused a reduced number of colonies in both conditions (Figure 5A and Supplementary Figure S11A). Cell cycle analyses indicated a mild, but significant, accumulation of cells in the G1 phase (Figure 5B and Supplementary Figure S11B), in concordance with the cell proliferation data. Tumor suppressors can control tumorigenesis not only via their anti-proliferative activities, but also through modulation of cell migration, a property critical for tumor invasion and metastasis. The cell spreading capacity of MCF7 cells silenced for SMUG1 or overexpressing let-7b-5p was tested using the wound healing assay. As shown in Figure 5C and Supplementary Figure S11C, cells with elevated let-7b-5p levels presented a reduced migration capacity compared to the controls. Thus, in combination these results confirmed the role of let-7b-5p as tumor suppressor affecting both cell proliferation and migration in breast cancer. This suppressor activity of let-7b-5p might explain the observed association of low SMUG1 levels with increased survival in ER+ breast cancers (Figure 1 and Supplementary Figure S2), suggesting an indirect effect of SMUG1 in cancer development.
In order to confirm the data obtained in MCF7 transiently silenced for SMUG1, we generated SMUG1 knock-out (KO) clones using CRISPR/Cas9 technology in two breast cancer cell lines, MCF7 and MDA-MB-231. As expected SMUG1 transcription was not affected (data not shown), but no protein was detected using an antibody directed towards the N-terminal domain of SMUG1 (Figure 6A and Supplementary Figure S12A). Real-time PCR for let-7b-5p levels revealed a ∼ 2-fold increase of this microRNA in two independent clones of each cell line (Figure 6B and Supplementary Figure S12B). We observed a reduced mature-to-pre-let-7b ratio in both SMUG1 KO MCF7 and MDA-MB-231 cells (Figure 6C and Supplementary Figure S12C), supporting a possible role for SMUG1 in the microRNA maturation process. Next, we tested the presence of SMUG1 substrates on pre-let-7b and we saw a reduced number of possible substrates in both the clones (Figure 6D and Supplementary Figure S12D), suggesting that the accumulation of pre-let-7b in SMUG1 KO and the increased levels of the mature form might be the consequence of an inefficient RNA processing. As in the knock-down system, both cell proliferation and cell migration were negatively affected by the elevated levels of let-7b-5p observed in the SMUG1 KO clones (Figure 6E–H, Supplementary Figures S12E–G and S13). The observed accumulation of cells in G1 phase (Figure 6E and Supplementary Figure S12E) was again accompanied by reduced cellular proliferation, as measured by the colony formation assay (Figure 6F, Supplementary Figure S12F and Figure S13A), as well as cellular migration, measured by wound healing and by high content imaging for MCF7 cells (Figure 6G, H and Supplementary Figure S13B) and by the transwell migration assay for the MDA-MB-231 clones (Supplementary Figure S12G). Finally, to better characterize what SMUG1 function is required for let-7b-5p regulation, we performed complementation assays (Supplementary Figure S14). Let-7b-5p levels were reduced when the expression of SMUG1-WT and of DKC1-binding mutant (SMUG1 E29/31R) was restored in SMUG1 KO cells. Interestingly, the expression of a SMUG1 mutant with significantly hampered damage-excision activity due to inefficient binding to the substrate (SMUG1 H239L) failed to complement the microRNA levels, pointing at SMUG1 substrate affinity and RNA binding as critical features for let-7b-5p regulation in breast cancer cells possibly through facilitating the recruitment of critical processing factors.
To assess whether the negative correlation between SMUG1 and let-7b-5p expression found in RNA-seq datasets (Figure 3C) was confirmed in tumor tissue, we checked SMUG1 and let-7b-5p expression and subcellular localization in serial sections (Supplementary Figure SS15) from tissues from a cohort of 66 breast cancer samples comprising Luminal A (LumA, 21 samples), Luminal B (LumB, 12 samples), Triple negative (TNBC, 17 samples), and HER2-positive (HER2, 16 samples) subtypes. The clinico-pathological characteristics are summarized in Supplementary Table SVIII. Expression levels and subcellular localization were analyzed for both SMUG1 and let-7b-5p, using IHC and CISH, respectively (Figure 7). SMUG1 presented a general nuclear staining with positive nucleoli in all tissue types (Figure 7A), consistent with its known direct protein interaction with DKC1 and function in ribosomal RNA biogenesis (9,23). Interestingly, a positive correlation between SMUG1 and its interacting protein expression could be observed as well in breast cancer tissues, confirming the bioinformatic analyses (Supplementary Figure SS16). An increased percentage of SMUG1-positive cells was observed in tumor samples, where 41% of the samples presented high SMUG1 expression level versus 25% of the normal ones (Figure 7B), in accordance with SMUG1 mRNA data (Figure 1A). We then focused on let-7b-5p levels. As shown in Figure 7C-J, let-7b-5p displayed a general cytoplasmic localization in both tissues (Figure 7C–J). Interestingly, decreased let-7b-5p levels were seen in the tumor when compared to the adjacent normal tissue (Figure 7K). In conclusion, the negative correlation between SMUG1 and let-7b-5p was confirmed in tumor tissue.
In the present study, we identified a regulatory loop between SMUG1 and let-7b-5p miRNA in breast cancer cells. Functional relevance of this regulatory loop is supported by a negative correlation between the expression of SMUG1 and let-7b-5p in breast cancer datasets (Figures 3C and 7). On the mechanistic level, SMUG1 physically interacts with let-7b-5p and other let-7 microRNAs in vivo and regulates let-7b-5p expression. Consequently, when SMUG1 expression was down-regulated or constitutively knock-out in breast cancer cells, we observed increased levels of let-7b-5p and accumulation of its precursor, pointing at miRNA misprocessing events during the maturation steps in SMUG1 knock-down and knock-out cells (Figures 4 and 6, Supplementary Figures S8 and S12). The same negative correlation between SMUG1 and let-7b-5p expression levels was also confirmed in vivo by IHC and CISH on a breast cancer cohort (Figure 7). While the let-7b-5p target sequence does not contain bases that could be converted to 5-hmU, e.g. by direct oxidation or AID/APOBEC deamination of 5-hydroxymethylcytosine (5-hmC) derived from 5-mC, the precursor form contains several Cs in the hairpin-loop region that could be converted into SMUG1 substrates (Figure 6 and Supplementary Figure S12). Our data suggests that in absence of SMUG1 the equilibrium between distinct pre-let-7b populations (modified vs unmodified) shifts preferentially towards the unmodified/moderately modified, possibly due to a change in the stability. Interestingly, SMUG1 is also a downstream target of let-7b-5p, having a let-7b-5p response element in its 3′-UTR region, suggesting a co-regulatory mechanism between SMUG1 and let-7b-5p (Figure 4). microRNA expression is often altered in malignancies and although some have been implicated and well-studied in breast cancer, for example let-7a, little is known about the specific relationship of let-7b, breast cancer subtypes and clinical outcomes (51,54,55). A few independent studies observed deregulation of let-7b during early breast cancer progression and showed that its expression is downregulated during epithelial-mesenchymal transition and associated with less aggressive breast cancer (54–58). It has been suggested that let-7b has tumor suppressor properties in breast cancer development and progression. Accordingly, SMUG1 KO breast cancer cells with elevated let-7b-5p levels showed accumulation in the G1 phase, consistent with reduced proliferation. With respect to cell mobility, we observed reduced cell migration for the clones analyzed, albeit with some clonal variation in the magnitude of the effect (Figures 5 and 6, Supplementary Figure S12). We also found a significant negative correlation between let-7b expression and patient overall survival, relapse-free survival and tumor lymph node metastasis in breast cancer cohorts (51–53). Even though let-7b levels are generally reduced in tumor tissues, its expression varies within the different subtypes and as a function of the grade, with its level decreasing as the grade increases. In less differentiated and more aggressive subtypes, as basal-like and HER2+, let-7b expression is reduced; on the contrary, relative increased levels are described for luminal A, luminal B and normal-like tumors (51,59). Bioinformatic analyses of SMUG1 mRNA expression in different breast cancer cohorts showed increased SMUG1 levels in tumor compared to control samples (Figure 1). Even though ER+ datasets showed increased SMUG1 mRNA levels when compared to ER− tumors and normal tissue, reduced levels of SMUG1 were associated with better survival, especially in the ER+ dataset of the cohorts analyzed (Figure 1 and Supplementary Figure S2). Thus, the higher survival observed for low SMUG1 in ER+ cohorts could be associated with the increased levels of let-7b-5p and its tumor suppressor activities rather than a direct role of SMUG1 in tumorigenesis. A previous study reported that low SMUG1 expression was associated with worse prognosis in the UPSA breast cancer cohort, and this effect was predominant in ER+ tumors. On the contrary, in ER− tumors that received chemotherapy and in gastric cancers low SMUG1 expression showed better survival, suggesting a complex role for SMUG1 in carcinogenesis (16). It is difficult to compare our results to those previously observed, because the final Kaplan–Meier result could be influenced by several factors such as the normalization method of the microarray data and the stratification of the SMUG1 groups. These differences led us to look in more detail into the UPSA data and we generated Kaplan–Meier curves by splitting the cohorts according to the expression of genes with known association with survival, i.e.ESR1, ERBB2 and MKI67, and found the expected results, such as higher ERBB2 expression associates with worse survival or high ESR1 with better outcome. These conflicting results suggest that SMUG1 mRNA expression alone cannot be used as a robust prognostic marker for breast cancer nor its response to adjuvant therapy. SMUG1 protein-protein interactors or its associated RNAs form a complex network that affects SMUG1 functions and influence the surrounding cellular environment. Since SMUG1 is a multifunctional protein, analyzing its PPI could reveal how its different functions are working together to determine its impact on breast cancer survival, where the dominating effects may be ascribed to functions other than DNA repair, as previously described for Apurinic/apyrimidinic Endonuclease 1, another key DNA repair protein in the BER pathway (60). We characterized the SMUG1 protein–protein interactome via a combined approach of Y2H and immunoprecipitation. We analyzed the impact of SMUG1 interactors, defined as bad prognosis genes in TCGA datasets, on breast cancer cohort showing lower survival probability in patients having these genes highly expressed (Figure 3 and Supplementary Figure S5). Taken together our results suggest that SMUG1 role in breast cancer is associated with RNA-related functions and its protein-protein network rather than only its DNA repair activity. Inefficient DNA repair and defective DNA damage response increase the mutation frequency, leading to genomic instability and cancer development (61). Even though SMUG1 was suspected to have an anti-tumor role via preventing the accumulation of mutations arising from deamination of cytosine residues and from several pyrimidine oxidation products (i.e. 5-hmU, 5-fU and 5-caU) (5–8,10,42), previous studies showed a modest increase in the mutagenesis ratio in MEFs knock-out for SMUG1 (41). Apart from its role in DNA repair, SMUG1 is involved in RNA metabolism and RNA quality control (9,23). In fact, increased SMUG1 protein levels significantly protect against killing 5-fluorouracil (FU)-treated cells, increasing cell and drug resistance in tumors (62). All drugs used in adjuvant chemotherapy induce ribosome biogenesis defects (63) suggesting that the role of SMUG1 in RNA metabolism may affect the treatment response. A role for SMUG1 in RNA metabolism may also be consistent with the observation that SMUG1 contributes to the cellular response to recovery from FU (4). We conclude that the correlation of SMUG1 alone with survival does probably not reflect a direct role of SMUG1 in cancer development and it should not be used as a prognostic marker. However, the present analysis suggests that SMUG1 is part of a gene regulatory network (possibly regulated by miRNAs) that influence survival and treatment response in several cancers.
The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (64) partner repository with the dataset identifier PXD025929. Data associated with FACS analysis is available in FlowRepository under accession FR-FCM-Z5F8, FR-FCM-Z5FA, FR-FCM-Z5FC and FR-FCM-Z5FD. All other datasets presented in this manuscript are available online.
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PMC9561619 | Sen Zhang,Hui Huangfu,Qinli Zhao,Yujun Li,Lina Wu | Downregulation of long noncoding RNA HCP5/miR-216a-5p/ZEB1 axis inhibits the malignant biological function of laryngeal squamous cell carcinoma cells | 30-09-2022 | invasion,lncRNA,miRNA,migration,proliferation,ZEB1 | Previous studies find that long noncoding RNA human leukocyte antigen complex P5 (HCP5) is regarded as an oncogene via accelerating cancer cell growth, invasion, metastasis, vascularization, and drug resistance in renal cell carcinoma, gastric cancer, and colorectal cancer. Nevertheless, the effect and regulatory mechanism of HCP5 in laryngeal squamous cell carcinoma (LSCC) remains unknown. In this study, HCP5 expression levels were confirmed to be prominently raised in LSCC cell lines. HCP5 knockdown reduced cell proliferation and migration and invasive ability of LSCC cell lines. Furthermore, miR-216a-5p was confirmed to sponge HCP5, and its expression was prominently downregulated in LSCC cell lines and upregulated in HCP5-silenced LSCC cell lines. miR-216a-5p overexpression downregulated the cell proliferation and migration and invasive ability of LSCC cells. Additionally, the protein level of zinc finger E-box binding homeobox 1 (ZEB1), one target gene of miR-216a-5p, was highly expressed in LSCC cell lines, and its expression level was downregulated by HCP5 knockdown and miR-216a-5p overexpression. An miR-216a-5p inhibitor reversed the effect of HCP5 knockdown on the proliferation and migration and invasive ability of LSCC cells. In conclusion, knocking down HCP5 may be a strategy to suppress the malignant biological function via regulating miR-216a-5p/ZEB1. Therefore, HCP5 may become a prospective therapeutic target for LSCC. | Downregulation of long noncoding RNA HCP5/miR-216a-5p/ZEB1 axis inhibits the malignant biological function of laryngeal squamous cell carcinoma cells
Previous studies find that long noncoding RNA human leukocyte antigen complex P5 (HCP5) is regarded as an oncogene via accelerating cancer cell growth, invasion, metastasis, vascularization, and drug resistance in renal cell carcinoma, gastric cancer, and colorectal cancer. Nevertheless, the effect and regulatory mechanism of HCP5 in laryngeal squamous cell carcinoma (LSCC) remains unknown. In this study, HCP5 expression levels were confirmed to be prominently raised in LSCC cell lines. HCP5 knockdown reduced cell proliferation and migration and invasive ability of LSCC cell lines. Furthermore, miR-216a-5p was confirmed to sponge HCP5, and its expression was prominently downregulated in LSCC cell lines and upregulated in HCP5-silenced LSCC cell lines. miR-216a-5p overexpression downregulated the cell proliferation and migration and invasive ability of LSCC cells. Additionally, the protein level of zinc finger E-box binding homeobox 1 (ZEB1), one target gene of miR-216a-5p, was highly expressed in LSCC cell lines, and its expression level was downregulated by HCP5 knockdown and miR-216a-5p overexpression. An miR-216a-5p inhibitor reversed the effect of HCP5 knockdown on the proliferation and migration and invasive ability of LSCC cells. In conclusion, knocking down HCP5 may be a strategy to suppress the malignant biological function via regulating miR-216a-5p/ZEB1. Therefore, HCP5 may become a prospective therapeutic target for LSCC.
Head and neck cell carcinoma is an invasive malignant tumor that includes oral, hypopharyngeal, and laryngeal cancer, and its incidence ranks sixth among various types of tumors (1). In particular, laryngeal squamous cell carcinoma (LSCC) is the usual cancer type of the larynx, accounting for approximately 90% of all laryngeal carcinomas (2). Surgical excision is an effective treatment method for early LSCC, but this strategy is limited for advanced LSCC (3). Hence, the identification of potential targets involved in the occurrence and metastasis contributes to exploring novel targets for treatment of LSCC. Long noncoding RNA (lncRNA) has been considered in previous studies to play a key role in the progression, vascularization, and aggressive behavior of cancer (4, 5). In LSCC, dysregulated lncRNA, such as SNHG16, PTCSC3, and XIST, can regulate LSCC cell growth, metastasis, angiogenesis, and chemoresistance (6–8). Human leukocyte antigen complex P5 (HCP5), an lncRNA, is located on human chromosome 6p21.33 (9). Previous studies find that HCP5 is regarded as an oncogene via accelerating cancer cell growth, metastasis, and drug resistance in renal cell carcinoma, gastric cancer, and colorectal cancer (10–12). Additionally, HCP5 expression is confirmed to be prominently increased in oral SCC, which has a key role in promoting cancer cell invasion (13). These studies suggest that HCP5 is an oncogene. Nevertheless, the biological behavior and regulatory mechanism of HCP5 in LSCC remains unknown. At the same time, oral SCC and LSCC belong to head and neck cell carcinoma; hence, we infer that HCP5 also plays an oncogenic role in LSCC. Therefore, this study selected HCP5 to study its function in LSCC and to clarify whether it could be a potential therapeutic target for LSCC. Therefore, we determined HCP5 expression and roles in LSCC cell lines. We also investigated the regulatory mechanism of HCP5 in LSCC by sponging microRNAs (miRNAs).
Human keratinocytes HaCaT and LSCC cell including Tu-686, SNU899, SNU46, Tu-177, and AMC-HN-8 (ATCC, Manassas, VA, USA) were cultured as previously described (14). Negative control miRNA mimic/inhibitor (NC mimic and NC inhibitor), miR-216a-5p mimic/inhibitor, small interference RNAs (siRNAs) targeting RNA sequence of HCP5, and negative control siRNA were synthesized from RiboBio (Guangzhou, China). Each of the products (50 nM) was transfected with Lipofectamine 3000 (Life technologies, Carlsbad, CA, USA). Their sequences are shown as follows: 5′‐GGCAGATTACAATTACAATCAAGDTDT‐3′ (si-HCP5-1), 5′‐GAGATGT CTTTGATTTTTAAAATDTDT‐3′ (si-HCP5-2), and 5′‐ATGATGTTGTCAATGAAATAAAGDTDT‐3′ (si-HCP5-3). The sequence of negative control siRNA was 5′‐TTCTCCGAACGTGTCACGTDTDT‐3′.
HaCaT and LSCC cell lines and transfected Tu-177 and Tu-686 cells were washed with PBS, and then, 1 ml TRIzol reagent (Invitrogen) was used in each well to isolate total RNA. To analyze the expression level of HCP5, a reverse transcription reaction to obtain cDNA was carried out according to the method of the PrimeScript™ RT reagent Kit (TaKaRa, Dalian) using reverse transcription primer olig dT. To analyze miR-216a-5p expression levels, a reverse transcription reaction to obtain cDNA was carried out according to the method of the HyperScript III miRNA 1st Strand cDNA Synthesis Kit (by stem-loop) (NovaBio, Shanghai, China). The QPCR reaction system (20 μl) was prepared according to the instructions of SYBR GREEN qPCR Super Mix (Invitrogen). PCR reaction was performed using the ABI 7500 Real-time PCR system (Applied Biosystems, Foster City, CA, USA). GAPDH and U6 were analyzed as the internal control gene for HCP5 and miR-216a-5p, respectively. The 2−ΔΔct method was used to calculate the relative expression level of HCP5 and miR-216a-5p (15). Primers (5′‐3′) for HCP5 are GACTCTCCTACTGGTGCTTGGT (forward primer, F) and CACTGCCTGGTGAGCCTGTT (reverse primer, R); Primers (5′‐3′) for GAPDH are GCTCATTTGCAGGGGGGAG (F) and GTTGGTGGTGCAGGAGGCA (R). Primers (5′‐3′) for miR-216a-5p are ACACTCCAGCTGGGAAGGGTAATCTCAGCTGGCAA (F) and CTCAACTGGTGTCGTGGA (R). Primers (5′‐3′) for U6 are CTCGCTTCGGCAGCACA (F) and AACGCTTCACGAATTTGCGT (R).
Twenty-four hours after transfection, 1×104 transfected Tu-177 and Tu-686 cells were seeded in 96-well plates. After culture for 0, 24, 48, and 72 h, 10 μl AQueous One Solution reagent (Promega) was added into each well. After cultivation for 4 h, the optical density at an absorbance of 490 nm (OD490 nm) was measured.
To assess the migrated ability, 1×105 transfected Tu-177 and Tu-686 cells of each group (in serum-free culture medium) were seeded in the upper Transwell chamber (Corning, Corning, NY, USA), and 600 µl culture medium supplemented with 10% serum was put into the lower well. After culture for 24 h, cells on the lower surface of the membrane were stained with crystal violet solution. Photos (100×) were taken, and cells in each photo were counted. For the invasion assay, the upper Transwell chamber was precoated with Matrigel (BD Biosciences, Bedford, MA, USA), and the remaining steps are the same as the migration operation.
StarBase 2.0 (16) was used to predict the possible sponged miRNAs of HCP5. TargetScan version 7.1 and StarBase version 2.0 were used to predict the potential target genes of miR-216a-5p. The wild-type HCP5 and ZEB1 3′-UTR (WT-HCP5 and WT-ZEB1) or mutant HCP5 and ZEB1 3′-UTR (Mut-HCP5 and Mut-ZEB1) were cloned into a psi-CHECK2 vector. Thirty nanograms of either WT-HCP5 and Mut-HCP5 or WT-ZEB1 and Mut-ZEB1 were cotransfected with 50 nM of either miR-216a-5p mimics or NC mimic. After 48 h, Renilla and firefly luciferase activity were measured according to the instructions of the Dual‐Luciferase Assay kit (Promega), and their ratio (Renilla/firefly) was used as the relative luciferase activity to evaluate whether miR-216a-5p has binding sites on the predicted sequence of HCP5 and ZEB1 3′-UTR.
The total protein (30 μg per lane) was isolated using RIPA buffer. After 10% SDS-PAGE, proteins were transferred onto methanol-pretreated polyvinylidene fluoride membranes. Following this, membrane blocking, primary antibody incubation, and secondary antibody incubation were performed according to conventional methods. The dilution of zinc finger E-box binding homeobox 1 (ZEB1) monoclonal antibody (14-9741-80, Ebioscience, San Diego, CA, USA) and loading control GAPDH monoclonal antibody (MA5-15738, Ebioscience) were 1:1000 and 1:5000, respectively. The dilution of horseradish peroxidase-conjugated secondary antibody goat anti-mouse IgG (G-21040, Ebioscience) was 1:1000. Enhanced chemiluminescent reagent (Thermo Scientific Pierce, Rockford, IL, USA) was used to visualize the protein abundance in the membrane.
The GEPIA website was used to analyze HCP5 expression in 44 normal and 519 head and neck squamous cell carcinoma tissues. One-way analysis of variance (ANOVA) followed by Dunnett’s test were used to analyze to statistical difference of all the experimental data by SPSS 19.0 software (SPSS Inc., Chicago, IL, USA). All data in the bar graphs are presented as mean ± standard deviation. *p <.05 was considered statistically significant.
To understand the HPC5 expression in LSCC tissues and cells, HCP5 expression in tumor tissues and LSCC cells were measured by GEPIA and RT-qPCR, respectively. HCP5 expression in tumor tissues was prominently higher than that in the normal group ( Figure 1A ). HCP5 expression was prominently raised in all LSCC cells, particularly in Tu-177 and Tu-686, compared with the expression in HaCaT cells ( Figure 1B ). Thus, we chose the Tu-177 and Tu-686 cell lines for further experiments.
To study the function of HCP5 in LSCC, HCP5 was silenced by transfecting si-HCP5 (si-HCP5-1/2/3) into both Tu-177 and Tu-686 cells. RT-qPCR results shows that si-HCP5 transfection significantly downregulated the HCP5 expression in both Tu-177 and Tu-686 cells, especially for si-HCP5-3 ( Figure 2A ). Thus, we chose si-HCP5-3 for further experiments. Next, silenced HCP5 (the si- HCP5 group) significantly reduced the proliferation, migration, and invasion abilities of Tu-177 and Tu-686 compared with the si-NC group ( Figures 2B–D ).
To characterize the downstream mechanisms underlying the inhibitory effect of HCP5 in LSCC cells, the sponged miRNAs of HCP5 were predicted using StarBase 2.0 databases. Among miRNAs, miR-216a-5p was found to be the possible sponged-miRNA of HCP5 ( Figure 3A ). An miR-216a-5p mimic prominently lessened the relative luciferase activity in the WT-HCP5 group while not affecting that in the mut-HCP5 group ( Figure 3B ). These results indicate a direct bond between HCP5 and miR-216a-5p. miR-216a-5p expression was prominently lower in LSCC cells than that in HacaT cells, which was not regulated by HCP5 knockdown ( Figures 3C, D ). All results found that HCP5 only sponged miR-216a-5p in LSCC cells.
To study the function of miR-216a-5p in LSCC, miR-216a-5p mimic was transfected into Tu-177 and Tu-686 and it was found that miR-216a-5p expression was prominently improved in LSCC cells ( Figure 4A ). The proliferation, migration, and invasion abilities of Tu-177 and Tu-686 in the miR-216a-5p mimic group were prominently lower than that in the NC mimic group ( Figures 4B–D ).
To further verify the correlation between miR-216a-5p and HCP5 in LSCC, si-HCP5 and miR-216a-5p inhibitors were cotransfected into Tu-177 and Tu-686. miR-216a-5p expression was prominently inhibited after cotransfection ( Figure 5A ). The proliferation, migration, and invasion abilities in the si-HCP5+miR-216a-5p inhibitor group were prominently enhanced compared with those in the si-HCP5+NC inhibitor group ( Figures 5B–D ).
The target site for miR-216a-5p binding was found to be the 3′-UTR of ZEB1 ( Figure 6A ). An miR-216a-5p mimic significantly decreased the relative luciferase activity in the WT-3′-UTR ZEB1 group, but did not affect MUT-3′-UTR ZEB1 ( Figure 6B ), which indicates the direct binding between miR-216a-5p with the 3′-UTR of ZEB1. The protein level of ZEB1 was higher in LSCC cells than in HacaT cells ( Figure 6C ). HCP5 silenced or miR-216a-5p overexpression significantly decreased ZEB1 protein in both Tu-177and Tu-686 cells ( Figure 6D ). ZEB1 protein was obviously enhanced 48 h after cotransfection of si-HCP5 and miR-216a-5p inhibitor in both Tu-177and Tu-686 cells ( Figure 6E ).
Tumor metastasis is an important reason for poor prognoses in LSCC patients. Here, we elucidated that HCP5 is prominently upregulated in LSCC cell line, and HCP5 downregulation inhibited proliferation, migration, and invasion, suggesting that HCP5 is an oncogene in LSCC. miR-216a-5p was sponged by HCP5 in LSCC. miR-216a-5p overexpression reduced proliferation, migration, and invasion in LSCC, suggesting that it is a tumor suppressor miRNA. Furthermore, silenced miR-216a-5p reversed the function of HCP5 silencing, suggesting that HCP5 promotes LSCC progression via sponging miR-216a-5p. Moreover, ZEB1 is a regulated target gene for miR-216a-5p. Silencing its expression reversed the effect of HCP5 silencing on ZEB1 expression, suggesting that HCP5 enhanced ZEB1 protein by sponging miR-216a-5p. These results suggest that HCP5 promotes LSCC progression by inhibiting the miR-216a-5p/ZEB1 axis. This study is the first to discover the role and mechanism of HCP5 in LSCC, which enriches the theory of the occurrence and development mechanism of LSCC. HCP5 closely contributes to tumor initiation and progression. HCP5 is a novelty diagnostic and prognostic biomarker in gastric and bladder cancers (17, 18). In addition, HCP overexpression enhanced chemoresistance in gastric cancer and esophageal carcinoma (19, 20). Besides this, HCP5 was prominently upregulated and acted as an oncogene in pancreatic cancer, bladder cancer, gastric cancer, and cutaneous squamous cell carcinoma (21–24). Consistent with previous reports of other cancers, HCP5 expression was also upregulated in LSCC cells, and HCP5 was an oncogene. In recent years, increasing evidence has found that abnormal expression and dysfunction of miRNAs also plays important roles in LSCC (25, 26). Here, miR-216a-5p was downexpressed in LSCC cells and acts as an anticancer miRNA in the LSCC. miR-216a-5p expression was elucidated to prominently reduce in breast, pancreatic, colorectal, and small cell lung cancers and reversing its expression significantly suppressed cancer development (27–31). Importantly, miR-216a-5p expression was prominently reduced in esophageal SCC and promotes its indeterminate growth (32). Studies have found that miR-216a-5p acts as an anticancer miRNA, which is consistent with its role in LSCC. Besides this, lncRNA is elucidated to enhance the expression of targeted genes by sponging with miRNAs (33). HCP5 promotes cancer development by sponging miR-140-5p, miR−138−5p, miR-29b-3p, and miR-143-3p (21–24). In addition, HCP5 can sponge miR-216a-5p in cervical cancer (34). Here, we confirm that HCP5 promotes LSCC progression via sponging miR-216a-5p. Next, ZEB1 is a directly regulated target gene for miR-216a-5p. ZEB1 expression was prominently upregulated in NSCLC, which can judge the overall survival rate (35). ZEB1 accumulation enhanced the invasion and EMT of liver and gastric cancer cells (36, 37). Importantly, ZEB1 acts as an oncogene and is closely related to EMT and prognosis in LSCC (38, 39). Our study shows that ZEB1 expression was enhanced in LSCC cells, and it was inhibited by silencing HCP5 and promoted by cosilencing HCP5 and miR-216a-5p. These results reveal that ZEB1 is a downstream targeted gene that is regulated by the HCP5/miR-216a-5p axis. Previous conclusions show that lncRNA-SNHG16 can regulate miR-216a-5p/ZEB1 and promote tumor development in cervical cancer tissues, which partly supports our results (40). This article has several limitations. First, the expression of HCP5 in LSCC tissues and its correlation with clinical features of LSCC were not explored. Second, the effect of HCP5 on LSCC was not performed to verify in vivo. In addition, the downstream signaling pathways regulated by ZEB1 in LSCC need to be found in further exploration. Finally, the clinical application of HCP5 still needs to overcome many problems. The entry of all lncRNA-based therapies into the clinic, such as specificity, delivery mode, and immunogenicity (41), has been hindered. The lncRNA may be taken up by other cells than the target cells, resulting in off-target effects and low specificity. The structural instability of lncRNAs leads to low efficiency of intracellular delivery of lncRNA; in addition, exogenous lncRNAs are prone to lead to tolerance problems (immunogenicity problems).
HCP5 promotes the proliferation, migration, and invasion of LSCC by regulating miR-216a-5p/ZEB1, and HCP5 knockdown exerts the opposite effect ( Figure 7 ), suggesting that HCP5 may be a prospective therapeutic target for LSCC. The therapeutic efficacy of HCP5 on LSCC needs to be validated by more in vivo and clinical investigations.
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.
SZ: Conceptualization, Data Curation, Visualization, and Writing - Original Draft; HH and QZ: Conceptualization, Formal analysis, and Writing - Review and Editing YL: Project administration and Data Curation; LW : Investigation and Data Curation and Writing - Review and Editing. All authors contributed to the article and approved the submitted version.
This study was supported by Science Foundation for Youths of Shanxi Province of China (No. 201601D021140) Natural Science Foundation of Basic research program of Shanxi Province, China (No. 20210302123250) and Startup Foundation for Doctors of Shanxi Medical University (No. 03201628).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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PMC9562033 | Xulin Zhou,Fengyun Zhong,Yongmin Yan,Sihui Wu,Huizhi Wang,Junqiang Liu,Feifan Li,Dawei Cui,Min Xu | Pancreatic Cancer Cell-Derived Exosomes Promote Lymphangiogenesis by Downregulating ABHD11-AS1 Expression | 23-09-2022 | pancreatic cancer,exosomes,lymphangiogenesis,ABHD11-AS1 | Simple Summary Lymphatic metastasis of pancreatic cancer is an important factor leading to poor prognosis of patients. In order to explore the relevant mechanism, we designed research and found that pancreatic cancer cell-derived exosomes promote lymphangiogenesis by downregulating the ABHD11-AS1 expression. This finding provides a new therapeutic strategy for inhibiting lymphatic metastasis metastasis in pancreatic cancer. Abstract Research on pancreatic cancer microbiomes has attracted attention in recent years. The current view is that enriched microbial communities in pancreatic cancer tissues may affect pancreatic cancer metastasis, including lymph node (LN) metastasis. Similar to carriers of genetic information between cells, such as DNA, mRNA, protein, and non-coding RNA, exosomes are of great importance in early LN metastasis in tumors, including pancreatic cancer. Our previous study showed that the long non-coding RNA ABHD11-AS1 was highly expressed in tissues of patients with pancreatic cancer, and was correlated with patient survival time. However, the role of ABHD11-AS1 in pancreatic cancer LN metastasis has rarely been studied. Hence, in this paper we confirmed that exosomes derived from pancreatic cancer cells could promote lymphangiogenesis in vitro and in vivo, and that the mechanism was related to the downregulation of ABHD11-AS1 expression in lymphatic endothelial cells, and to the enhancement of their ability to proliferate, migrate, and form tubes. These findings preliminarily show a new mechanism by which pancreatic cancer cells regulate peripheral lymphangiogenesis, providing a new therapeutic strategy for inhibiting LN metastasis in pancreatic cancer. | Pancreatic Cancer Cell-Derived Exosomes Promote Lymphangiogenesis by Downregulating ABHD11-AS1 Expression
Lymphatic metastasis of pancreatic cancer is an important factor leading to poor prognosis of patients. In order to explore the relevant mechanism, we designed research and found that pancreatic cancer cell-derived exosomes promote lymphangiogenesis by downregulating the ABHD11-AS1 expression. This finding provides a new therapeutic strategy for inhibiting lymphatic metastasis metastasis in pancreatic cancer.
Research on pancreatic cancer microbiomes has attracted attention in recent years. The current view is that enriched microbial communities in pancreatic cancer tissues may affect pancreatic cancer metastasis, including lymph node (LN) metastasis. Similar to carriers of genetic information between cells, such as DNA, mRNA, protein, and non-coding RNA, exosomes are of great importance in early LN metastasis in tumors, including pancreatic cancer. Our previous study showed that the long non-coding RNA ABHD11-AS1 was highly expressed in tissues of patients with pancreatic cancer, and was correlated with patient survival time. However, the role of ABHD11-AS1 in pancreatic cancer LN metastasis has rarely been studied. Hence, in this paper we confirmed that exosomes derived from pancreatic cancer cells could promote lymphangiogenesis in vitro and in vivo, and that the mechanism was related to the downregulation of ABHD11-AS1 expression in lymphatic endothelial cells, and to the enhancement of their ability to proliferate, migrate, and form tubes. These findings preliminarily show a new mechanism by which pancreatic cancer cells regulate peripheral lymphangiogenesis, providing a new therapeutic strategy for inhibiting LN metastasis in pancreatic cancer.
Pancreatic cancer is one of the most lethal solid tumors occurring worldwide. In China, pancreatic cancer ranks tenth in incidence and sixth in mortality among all malignancies [1]. Despite recent advances in diagnosing and treating pancreatic cancer, the prognosis of patients with pancreatic cancer remains poor, with a 5-year survival rate of <5% [2]. As pancreatic cancer is prone to early metastasis, patients often miss the best time to seek medical attention after they are diagnosed. Lymph node (LN) metastasis is one of the important means of pancreatic cancer metastasis, and the premature formation of metastases also makes some treatments intolerable for patients. Following treatment, the likelihood of recurrence is also greatly increased [3]. Therefore, inhibiting early LN metastasis in pancreatic cancer is essential in pancreatic cancer treatment. Enriched lymphatic vessels around solid tumors are often a means for tumor cells to enter peripheral lymphatic vessels and invade the peripheral lymphatic system via LN metastasis, causing distant metastasis. The regulatory effect of tumor cells on the generation of the peripheral lymphoid system has been studied in many tumors, including breast cancer [4], lung cancer [5], prostate cancer [6], and colon cancer [7]. Tumor cells secrete various cytokines to regulate the proliferation, migration, and tube-forming abilities of their surrounding endothelial cells, enriching the vasculature around tumor cells. The regulatory role of pancreatic cancer cells on their peripheral lymphangiogenesis has also been explored for many years. Various molecules are involved in the regulation of lymphangiogenesis in pancreatic cancer. Heparanase can promote lymphangiogenesis in pancreatic neuroendocrine tumors [8], KAI1 can inhibit LN metastasis in pancreatic cancer cells [9], and proteinase-activated receptor–2 can inhibit tumor cell-mediated lymphangiogenesis; however, these molecules have no direct regulatory effect on lymphatic endothelial cells [10]. miR-206 inhibits lymphangiogenesis in pancreatic cancer [11], and circNFIB1 interacts with miR-486-5p to regulate miR-486-5p/PIK3R1/VEGF-C and inhibit lymphatic proliferation, tube hyperplasia, and metastasis in pancreatic cancer [12]. Relevant in vivo experiments have contributed to the progress of research on pancreatic cancers. Current studies have shown that the simultaneous targeting of TGF-β/EGFR/HER2 can inhibit the proliferation of lymphatic vessels in pancreatic cancer models [13]. Moreover, lymphatic hyperplasia in pancreatic cancer is vital for lymphatic metastasis in pancreatic cancer; related molecular mechanisms have always attracted the attention of researchers. Exosomes are extracellular vesicles with a diameter of 30–150 nm, and are rich in diverse biologically active molecules such as proteins, nucleic acids, and lipids. After being endocytosed and taken up by recipient cells, these exosomes can regulate the biological functions of recipient cells [14]. In the formation of a tumor microenvironment, tumor cell-derived exosomes have always been considered to be a key factor in the regulation of intercellular communication. According to studies, tumor cell-derived exosomes have certain regulatory effects on tumor cell proliferation, metastasis, and stemness maintenance [15,16,17]. In pancreatic cancer, exosomes are important for the early diagnosis of tumor patients [18]. However, in-depth studies on exosomes associated with lymphatic vessel proliferation in pancreatic cancer are not yet available. The long non-coding RNA (lncRNA) ABHD11-AS1 is highly expressed in many cancers, including pancreatic cancer [19], papillary thyroid cancer [20], epithelial ovarian cancer [21], non-small cell lung cancer [22], gastric cancer [23], and colon cancer [24]. In patients with pancreatic cancer, high ABHD11-AS1 expression in the serum and tissues of patients is correlated with a poor prognosis [25]. However, studies on the association of high ABHD11-AS1 expression with lymphangiogenesis in pancreatic cancer are unavailable. Furthermore, whether pancreatic cancer cell-derived exosomes regulate LN metastasis in pancreatic cancer via ABHD11-AS1 is also unclear. Thus, we hypothesize that microbes in the digestive tract colonize the pancreas via the bile duct, and secrete exosomes to promote the formation of pancreatic cancer. Simultaneously, pancreatic cancer cell-derived exosomes enhance the proliferation, migration, and tube formation of pancreatic cancer cells of lymphatic endothelial cells by regulating ABHD11-AS1 expression and causing lymphatic proliferation around the tumor, thereby promoting lymphatic metastasis in pancreatic cancer. In this study, we showed that pancreatic cancer cell-derived exosomes could promote the proliferation, migration, and tube formation of lymphatic endothelial cells in vitro and in vivo; furthermore, pancreatic cancer cell-derived exosomes could downregulate ABHD11-AS1 expression, indicating a regulatory role of ABHD11-AS1 in tube formation in lymphatic cells. We explored a novel mechanism leading to abnormal lymphatic proliferation around pancreatic cancer, which could be a means to a new strategy for treating pancreatic cancer lymphatic metastasis.
A total of 42 tumor tissues from patients with pancreatic cancer were obtained from the Affiliated Hospital of Jiangsu University. These patients were deemed eligible if they had pathologically confirmed PCa. All experiments were conducted with the approval of the Committees for Ethical Review of Research involving Human Subjects at Jiangsu University. Informed consent was obtained from all participants before their sample collection.
The human PCa cell lines Patu8988 and BxPC-3, and the normal human lymphatic endothelial cell (HULEC), were purchased from the American Type Culture Collection (Rockville, VA, USA). Patu8988 and HULEC cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM; Gibco, New York, NY, USA) supplemented with 10% FBS. HULEC cells were cultured in RPMI 1640 medium (Gibco) supplemented with 10% FBS in a humidified incubator with 5% CO2 at 37 °C.
Exosomes were purified from PC cell-derived conditioned media through the polymer precipitation method. The PC cells were cultured in DMEM supplemented with 10% fetal bovine serum. The exosomes in bovine serum were depleted via ultracentrifugation at 160,000× g at 4 °C for 16 h before use. After the designated amount of time, the conditioned media were collected and centrifuged at 10,000× g at 4 °C for 30 min, and the supernatant was filtered through a 0.22-micrometer filter (Millipore, Burlington, MA, USA), followed by ultracentrifugation at 2000× g for 30 min at 4 °C. The exosome concentration solution was added to a supernatant in the ratio of 1:4. This mixture was preserved at 4 °C for 12 h, followed by centrifugation at 1500× g at 4 °C for 30 min, with collection of the precipitate, filtration through a 0.22-micrometer filter, and then ultracentrifugation at 2000× g for 30 min at 4 °C. The exosome pellet was washed with calcium and magnesium-free phosphate-buffered saline (PBS), followed by a second round of ultracentrifugation at 2000× g for 30 min at 4 °C and resuspension in PBS. The number of exosomes was determined by the BCA assay.
After washing in PBS, the exosomes were fixed in 1.5 M sodium cacodylate buffer (pH 7.4) and absorbed onto Formvar/carbon support film copper-mesh grids, and negatively stained with 2% (w/v) uranyl acetate. The sample was observed under a transmission electron microscope (TEM). Digital images were acquired with an AMT digital camera system.
HLECs at 90–95% confluence were serum starved in a 6-well plate for 24 h. Then, the cells were carefully scratched with sterilized pipette tips. The movement of HLECs was recorded under the DM IRE2 microscope every 6 to 18 h. Both the migration path and direction of HLECs were imaged by microscopy and analyzed with ImageJ software.
Transwell migration assays were performed with 24-well Transwell chamber plates (Corning, NY, USA). HLECs (8 × 104 cells/150 μL/well) were seeded in the upper compartment of the transwell chamber. The lower compartment was supplemented with 0.6 mL of the cell culture medium. After 12 h of incubation, the HLECs that had migrated through the polycarbonate membrane were fixed, stained, and enumerated. The images were analyzed with ImageJ software.
HLECs were trypsinized into a 6-well plate at a concentration of 1000 cells/well, and cultured for 14 days under standard high-glucose conditions. The culture medium was replaced whenever required. The colonies were fixed and stained. Visible colonies were enumerated manually.
Cell viability was evaluated using the Cell Counting Kit-8 (CCK-8), according to the manufacturer’s guidelines. For the cell proliferation assay, HLECs were seeded onto a 96-well plate (5000 cells/plate) with 400 μg/mL exosomes for 24, 48, and 72 h. These cells were then incubated with the CCK8 kit at 37 °C for 2 h. Finally, the absorbance at 450 nm was measured with a microplate reader, in order to evaluate the viability of the indicated cells.
Total RNA was extracted from the cells or tissues using Trizol and the enzyme RNA extraction kit (Takara, RR820A, Beijing, China). RNA (1 μg) was reverse-transcribed with a reverse transcription kit (Takara). Quantitative real-time PCR (qRT-PCR) was performed with gene-specific primers (Biotechnology, Shanghai, China) on the 7500ABI Biological System Machine. The comparison threshold was employed to calculate the absolute mRNA number. The relative gene expression normalized to β-actin was determined using the 2−ΔΔCT method. The primer sequences used for ABHD11-AS1 were as follows: forward: 5′-ATGAAGCCATTGCCAAGAAG-3′; reverse: 5′-GCCTCTCTCTGCAGC TGATT-3′T.
This experiment was performed as per the standard procedure. Briefly, approximately 60 μg of the total proteins were loaded and resolved in sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and then transferred onto a polyvinylidene difluoride (PVDF) membrane. We blocked the PVDF membrane with 5% nonfat milk. Next, the membrane was co-incubated with the corresponding antibodies. Eventually, the membrane was subjected to electrochemiluminescence (ECL) and exposed under appropriate conditions.
The HLECs stimulated with 400 μg/mL exosomes were planted on glass coverslips in a 24-cell plate. These cells were treated with 0.4% paraformaldehyde for 30 min, and then with 0.5% Triton X-100 for 15 min, followed by washing thrice with PBS to remove the residual Triton X-100. Then, 0.5% goat serum was used to treat the cells for 1 h, followed by the application of the corresponding antibodies. The nucleus was then stained with DAPI. The pictures were recorded using confocal microscopy.
For immunohistochemical staining for D2-40 and LYVE-1, the tumor sections were deparaffinized and rehydrated, and the endogenous peroxidase was inactivated by 3% H2O2 for 30 min. Next, the slides were immersed in preheated antigen retrieval solution (0.01 M, pH 6.0, citrate buffer) for 30 min. After blocking with 5% BSA, the tumor slides were probed with a primary antibody against D2-40 (Abcam, Cambridge, UK) and LYVE-1 (Abcam) overnight at 4 °C, and then incubated with biotin-conjugated anti-rabbit IgG and streptavidin-biotin. Finally, the sections of tumor tissues were visualized with the DAB horseradish peroxidase color development kit (Boster, Wuhan, China) and counterstained with hematoxylin. Positive actions were defined as those shown brown signals in the cell cytoplasm. A stained index (value, 0–12) was determined by multiplying the score for staining intensity with the score for positive area. The intensity was scored as follows: 0, negative; 1, weak; 2, moderate; and 3, strong. The frequency of positive cells was defined as follows: 0, less than 5%; 1, 5% to 25%; 2, 26% to 50%; 3, 50% to 75%; and 4, greater than 75%. For example, a specimen containing 75% tumor cells with moderate intensity (3 × 2 = 6) and another 25% tumor cells with weak intensity (1 × 1 = 1) receive a final score of 6 + 1 = 7. Relevant images were acquired using a pathological section scanner (3DHISTECH, Budapest, Hungary). The FISH kit (GenePharma, Shanghai, China) was used to perform the FISH assay. ABHD11-AS1 was labeled with the FAM probe, and the nucleus was stained with DAPI. The images were recorded using fluorescence microscopy. The fluorescence intensity was recorded and analyzed via ImageJ. The value of fluorescence intensity is defined as the expression of ABHD11-AS1.
Full-length human ABHD11-AS1 cDNA was constructed into vectors (pCDH-CMV-ABHD11-AS1 cDNA-EF1a-GFP-T2A-Puro). Small-interfering RNA (siRNA) targeting ABHD11-AS1 and control-scrambled siRNA were designed (Genepharma, Suzhou, China). Pancreatic cancer cells were seeded up to 80% confluence in a 6-well plate in triplicate. Lipofectamine 2000 (Life Technologies, Carlsbad, CA, USA) reagent was used for the transfection of the ABHD11-AS1 expression vector or synthetic siRNA oligos into pancreatic cancer cells. The cell RNA samples were harvested at 48 h after transfection and subjected to Western blotting or quantitative RT-PCR analysis.
Data were presented as the means ± SDs (standard deviations). Statistical significance between the two groups was analyzed via Student’s t-test using GraphPad Prism version 5.0 software. One-way analysis of variance (ANOVA) followed by the Dunnett test was applied for the analyses of more than two groups. A two-sided p < 0.05 was considered to indicate statistical significance.
We followed a polymer precipitation method to extract exosomes from the cell supernatants. We collected the supernatants of pancreatic cancer cell lines Patu8988 and Bxpc3, as well as human normal pancreatic ductal epithelial cells H6C7, and performed exosome extraction and purification on the corresponding supernatants. The Patu8988-derived exosomes were named Patu-ex; the Bxpc3-derived exosomes were named Bxpc3-ex; and the H6C7-derived exosomes were named H6C7-ex. The Western blot assay results showed that exosome-specific marker proteins cluster of differentiation (CD)9, CD63 and CD81 were present in Patu-ex, Bxpc3-ex, and H6C7-ex (Figure 1A). CD63 and CD81 were also present in these exosomes as per the flow cytometry analysis (Figure 1D). The typical bilayer structure and size of 30–100 nm were confirmed through transmission electron microscopy and nanoparticle tracking analysis, respectively (Figure 1B,C). The purified exosomes were labeled with the fluorescent membrane tracer DIO (green) and cultured with the human-derived lymphatic endothelial cells, in order to observe their distribution in lymphatic endothelial cells. After 48 h, cells phagocytosing exosomes were detected using confocal microscopy (Figure 1E). These results suggest that the extracted exosomes have typical characteristics of exosomes, and can be successfully phagocytosed by lymphatic endothelial cells.
In order to investigate whether pancreatic cancer cell-derived exosomes have a certain regulatory effect on the biological function of lymphatic endothelial cells, we co-cultured Patu-ex, Bxpc3-ex, and H6C7-ex with the lymphatic endothelial cells for 48 h, and the same amount of a PBS buffer was used as a control. The subsequent scratch, migration, CCK8, and plate cloning experiments were performed to detect the migration and proliferation of the lymphatic endothelial cells after co-culturing with the exosomes. The results indicated that the migration ability of the lymphatic endothelial cells that were treated with the pancreatic cancer cell-derived exosomes (Patu-ex and Bxpc3-ex) was enhanced compared with that of the control group, and to cells treated with H6C7-ex (Figure 2A,Ci,Cii). Similarly, the proliferation ability of the lymphatic endothelial cells stimulated by Patu-ex and Bxpc3-ex was also significantly improved (Figure 2B,Di,Dii). Thus, we concluded that exosomes derived from pancreatic cancer cells could promote the proliferation and migration of lymphatic endothelial cells.
After confirming that Patu-ex and Bxpc3-ex can promote the proliferation and migration of human lymphatic endothelial cells, we further analyzed tube formation ability and tube formation-related proteins, in order to determine whether exosomes derived from pancreatic cancer cells can promote the formation of lymphatic vessels surrounding endothelial cells. The stimulation method and grouping were performed as described above, and tube formation was observed 4 h after initiating the tube formation experiment. The results showed that the length of the tube formed by the lymphatic endothelial cells stimulated by Patu-ex and Bxpc3-ex was longer than that of the control cells (Figure 3Ai,Aii). The intracellular lymphatic vessel marker protein LYVE-1 was detected with an immunofluorescence assay, and the results showed that LYVE-1 levels in the lymphatic endothelial cells were significantly increased compared with those in the control group after stimulation with the exosomes derived from pancreatic cancer cells (Figure 3B). Finally, we detected the levels of intracellular tube formation-related proteins after exosome stimulation with Western blotting, and the results indicated that the levels of the tube formation-related proteins TIE-2, angiopoietin-2 (Ang-2), LYVE-1, prospero homeobox protein 1, and vascular endothelial growth factor C increased (Figure 3C) the relevant statistical analysis is in the Supplementary Material. Hence, we concluded that exosomes derived from pancreatic cancer cells could promote the angiogenesis of lymphatic endothelial cells.
Based on the above experiments, we confirmed that exosomes derived from pancreatic cancer cells could improve the proliferation, migration, and tube formation of lymphatic endothelial cells. Then, we studied their molecular mechanism of action. In patients with pancreatic cancer, ABHD11-AS1 expression is associated with patient prognosis; hence, we speculate that ABHD11-AS1 also plays a role in peripheral lymphangiogenesis stimulation by pancreatic cancer cells. We found that ABHD11-AS1 expression was downregulated in patients with positive LN metastasis, and increased in patients with negative LN metastasis (Figure 4B,C). We co-cultured Patu-ex, Bxpc3-ex, and H6C7-ex with lymphatic endothelial cells for 48 h and used the same amount of the PBS buffer as a control. We performed qRT-PCR to detect intracellular ABHD11-AS1 expression. The results showed that ABHD11-AS1 expression in the lymphatic endothelial cells decreased after the action of Patu-ex and Bxpc3-ex (Figure 4A). Therefore, we proposed a new hypothesis, that after the stimulation of lymphatic endothelial cells by pancreatic cancer cell-derived exosomes, the biological function of lymphatic endothelial cells is regulated through downregulating the lncRNA ABHD11-AS1. In order to test this hypothesis, we overexpressed ABHD11-AS1 (Flag-ABHD11-AS1) via lentiviral transfection in lymphatic endothelial cells, and also set a negative control (vector). Simultaneously, in another group of lymphatic endothelial cells, we used siRNA to interfere with ABHD11-AS1 expression (si-ABHD11-AS1), and also set a negative control (si-NC). The tube-forming ability was tested. The results of the CCK8 assay indicated that the proliferation of the lymphatic endothelial cells decreased after ABHD11-AS1 overexpression, whereas the proliferation of the lymphatic endothelial cells increased after interfering with ABHD11-AS1 expression (Figure 5A,B). The migration and tube formation experiments also showed similar results. The migration of the lymphatic endothelial cells and the ability to form tubes decreased after ABHD11-AS1 overexpression, whereas the migration of the lymphatic endothelial cells and the ability to form tubes increased after interfering with ABHD11-AS1 expression (Figure 5C–F). Subsequently, we tested this hypothesis. We stimulated lymphatic endothelial cells overexpressing ABHD11-AS1 with Patu-ex labeled with the membrane red dye DIL and verified the proliferation, migration, and growth of these cells. The results showed that after exosome stimulation, the proliferation, migration, and tube formation inhibition caused by ABHD11-AS1 overexpression were reversed (Figure 6A–C). Thus, we confirmed the hypothesis that pancreatic cancer cell-derived exosomes affect the proliferation, migration, and angiogenesis of lymphatic endothelial cells by downregulating ABHD11-AS1 expression in lymphatic endothelial cells.
After confirming that exosomes derived from pancreatic cancer cells can promote the proliferation, migration, and tube formation of lymphatic endothelial cells in vitro, we also performed in vivo experiments to verify these results. In pancreatic cancer patients with positive and negative lymphatic metastases, we collected tumor tissues from them to perform immunohistochemical experiments. In the tumor tissues, lymphatic vessels were observed to be less enriched, whereas in the adjacent tissues, lymphatic vessels were enriched to a lesser extent. The degree of enrichment was high (Figure 7A). We injected intratumoral exosomes after tumor formation in a nude mouse model. The results suggested that exosomes could promote the growth of cancerous tumors. The tumor bodies of these nude mice were significant in size and weight. The same volume of PBS was injected into the control group (Figure 7B,C). After slicing the tumor, LYVE-1 immunohistochemistry showed that the enrichment of lymphatic vessels in the exosome-injected tumor was higher than that in the control group (Figure 7D). Thus, we showed that pancreatic cancer cell-derived exosomes can promote pancreatic cancer proliferation and lymphatic metastasis in vivo.
In this study, we explored the role and mechanism of pancreatic cancer cell-derived exosomes in regulating lymphatic endothelial cells to form tubes and promote lymphangiogenesis. We found that exosomes derived from pancreatic cancer cells could promote the in vitro and in vivo proliferation of lymphatic endothelial cells and lymphangiogenesis. Pancreatic cancer cell-derived exosomes promote lymphangiogenesis by downregulating ABHD11-AS1 expression in lymphatic endothelial cells. In contrast, our results showed that ABHD11-AS1 overexpression in the lymphatic endothelial cells led to decreased cell proliferation, migration, and tube-forming ability, whereas interfering with ABHD11-AS1 expression reduced cell proliferation, migration, and tube-forming ability. The ABHD11-AS1-overexpressing lymphatic endothelial cells increased, and their proliferation, migration, and tube formation abilities increased after their co-culturing with the exosomes, consequently promoting lymphangiogenesis. Pancreatic cancer is one of the deadliest diseases worldwide, with a median survival time of only 3–6 months. Despite recent advances in diagnosing and treating pancreatic cancer, the prognosis of patients with pancreatic cancer remains unsatisfactory [26]. Microorganisms have certain regulatory effects on the occurrence and development of pancreatic cancer. Microorganisms that are present in the pancreas are probably involved in the development of chronic pancreatitis [27]. Lymphatic metastasis is one of the important means of tumor metastasis, and is one of the crucial reasons for poor patient prognoses. In patients with pancreatic cancer, early lymphatic metastasis often leads to missed opportunities for optimal treatment by the time patients present symptoms. The abnormally enriched lymphatic vessels around the tumor can promote the early LN metastasis of pancreatic cancer; hence, research on lymphatic vessel hyperplasia in pancreatic cancer has high clinical application value. However, studies on the regulatory role of microorganisms in the lymphatic metastasis of pancreatic cancer are scarce. Exosomes are vesicles secreted by cells that are important for information exchange between cells. In recent years, intestinal flora-derived exosomes have been confirmed to be involved in the occurrence and progression of gastrointestinal diseases. Intestinal flora-derived exosomes can mediate steatosis in hepatocytes carrying HMGB1 [28]. In inflammatory bowel disease, exosomes can regulate local inflammation. Microorganisms in a tumor microenvironment play a key role in the construction and transformation of the microenvironment for tumor progression [29]. During the progression of colon cancer [30], liver cancer [31], and pancreatic cancer [32], the early detection of microorganisms can be used as a marker of patient prognosis. However, the specific mechanism remains unclear. Moreover, in a pancreatic cancer microenvironment, exosomes are important information carriers. Exosomes from various sources have regulatory effects on various cells in a tumor microenvironment, ultimately forming a microenvironment that is suitable for tumor growth. Exosomes derived from pancreatic cancer cells promote the activation of pancreatic stellate cells and affect their regulation in a tumor microenvironment [33]. Exosomes can also promote polarity changes in macrophages, which in turn regulate inflammatory responses in a tumor microenvironment [34]. There are few previous studies on pancreatic cancer cell-derived exosomes and lymphangiogenesis. By co-culturing exosomes with lymphatic endothelial cells, we observed that the exosomes derived from pancreatic cancer could promote the proliferation, migration, and tube formation of the lymphatic endothelial cells. Subsequently, we detected the tube-forming-related proteins including LYVE-1, Ang2, and TIE-2. The results also showed that the exosomes derived from pancreatic cancer cells could enhance tube-forming ability. Similar results have been reported in other tumors, where exosome-derived miR-320b promoted lymphatic endothelial cell angiogenesis by regulating the AKT pathway in esophageal squamous cell carcinoma [35]. VASH1 downregulation in cervical squamous cell carcinoma-derived exosomes carrying miR-221-3p resulted in enhanced cell tube-forming ability [36]. Hepatoma cell-derived exosomes carrying miR-296 regulated EAG1/VEGFA pathway, affecting the tube-forming ability of cells [37]. Therefore, exosomes derived from pancreatic cancer cells can promote lymphangiogenesis in vitro. This finding is also consistent with the proliferative effect of other tumor-derived exosomes on lymphatic vessels. Subsequently, we performed some experiments to understand the mechanism. In recent years, lncRNAs have been implicated in various cellular life activities, such as cell proliferation, apoptosis, and differentiation [38]. Recent studies have shown that the lncRNA ABHD11-AS1 can promote the proliferation and metastasis of various cancer cells, such as papillary thyroid cancer [39], cervical cancer [40], breast cancer [41], and colon cancer [42]. ABHD11-AS1 expression promoted pancreatic cancer development [19]. In our previous study, we reported that ABHD11-AS1 was highly expressed in pancreatic cancer tissues, and was associated with poor patient prognoses [25]. The effect of ABHD11-AS1 on lymphatic endothelial cells is currently unknown. In this study, we hypothesized that pancreatic cancer-derived exosomes carrying lncRNA ABHD11-AS1 could promote the angiogenesis of lymphatic endothelial cells. However, the qRT-PCR results showed that ABHD11-AS1 expression was downregulated in lymphatic endothelial cells stimulated by the exosomes. In addition, after ABHD11-AS1 overexpression in these lymphatic endothelial cells, their angiogenesis ability decreased. In contrast, after interfering with ABHD11-AS1 expression, the angiogenesis ability of the lymphatic endothelial cells increased. We further stimulated the ABHD11-AS1-overexpressing lymphatic endothelial cells with exosomes, in order to restore the decreased vascular capacity. Therefore, we confirmed that the pancreatic cancer-derived exosomes regulated the angiogenesis ability of the lymphatic endothelial cells by downregulating ABHD11-AS1 expression. These results suggest that the lncRNA ABHD11-AS1 can inhibit the angiogenesis of lymphatic endothelial cells, and pancreatic cancer exosomes can promote cell angiogenesis by downregulating ABHD11-AS1 expression in lymphatic endothelial cells. Finally, we confirmed the above results in vivo. In clinical tissues, by labeling lymphatic vessels, we could see that their enrichment degree in paracancerous tissues was higher than that in cancerous tissue. Areas with fewer lymphatic vessels were also observed. Subsequently, we established a nude tumor mouse model and injected the exosomes into the tumor. The results showed that the tumor became larger and heavier after exosome injection, and surrounding lymphatic vessels became more enriched. Exosomes can promote the proliferation of lymphatic vessels in pancreatic cancer. According to other studies, the generation of pancreatic cancer cell-derived exosomes induced under hypoxic conditions can promote microvascular angiogenesis in vivo [43]. Under normal conditions, pancreatic cancer cell-derived exosomes promote angiogenesis by regulating the CCAT1/miR-138-5p/HMGA1 axis [44]. However, under in vivo conditions, whether pancreatic cancer cell-derived exosomes can promote the proliferation of lymphatic vessels around pancreatic cancer, is still unknown. This study also has limitations. Firstly, we did not fully explore the specific regulatory cellular pathways of exosomes derived from pancreatic cancer cells that promote lymphatic vessel proliferation. Furthermore, the specific downstream molecules of ABHD11-AS1 in lymphatic endothelial cells were not thoroughly studied. Secondly, early molecular typing to understand pancreatic cancer has recently attracted attention; despite this, we did not focus on whether molecular typing and pathological differences in cancer types would specifically affect the promotion of lymphatic vessel proliferation. Therefore, performing related studies is necessary.
We confirmed that pancreatic cancer cell-derived exosomes promote cell proliferation, migration, and angiogenesis by downregulating the expression of the lncRNA ABHD11-AS1 in lymphatic endothelial cells, thereby promoting lymphangiogenesis in pancreatic cancer cells. This finding provides a new therapeutic target for pancreatic cancer lymphatic metastasis, and a new strategy for the prognosis of patients with pancreatic cancer. | true | true | true |
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PMC9562272 | Jin-Yong Zhou,Jin-Yan Liu,Yu Tao,Chen Chen,Shen-Lin Liu | LINC01526 Promotes Proliferation and Metastasis of Gastric Cancer by Interacting with TARBP2 to Induce GNG7 mRNA Decay | 09-10-2022 | gastric cancer,lncRNA,LINC01526,TARBP2,GNG7,mRNA stability | Simple Summary Many long noncoding RNAs play an important role in gastric cancer progression. In this study, we focused on LINC01526. Through expression and functional analyses, we obtained a preliminary understanding of the pro-cancer role of LINC01526 in gastric cancer. Furthermore, RNA pull-down and RNA immunoprecipitation chip assays demonstrated that LINC01526 interacts with TARBP2, an RNA-binding protein controlling mRNA stability. Moreover, TARBP2 could bind and destabilize GNG7 transcripts. Finally, the rescue assay disclosed that LINC01526 promoted gastric cancer progression by interacting with TARBP2, leading to the degradation of GNG7 mRNA. Abstract Gastric cancer is the most common malignancy of the human digestive system. Long noncoding RNAs (lncRNAs) influence the occurrence and development of gastric cancer in multiple ways. However, the function and mechanism of LINC01526 in gastric cancer remain unknown. Herein, we investigated the function of LINC01526 with respect to the malignant progression of gastric cancer. We found that LINC01526 was upregulated in gastric cancer cells and tissues. The function experiments in vitro and the Xenograft mouse model in vivo proved that LINC01526 could promote gastric cancer cell proliferation and migration. Furthermore, LINC01526 interacted with TAR (HIV-1) RNA-binding protein 2 (TARBP2) and decreased the mRNA stability of G protein gamma 7 (GNG7) through TARBP2. Finally, the rescue assay showed that downregulating GNG7 partially rescued the cell proliferation inhibited by LINC01526 or TARBP2 silencing. In summary, LINC01526 promoted gastric cancer progression by interacting with TARBP2, which subsequently degraded GNG7 mRNA. This study not only explores the role of LINC01526 in gastric cancer, but also provides a laboratory basis for its use as a new biomarker for diagnosis and therapeutic targets. | LINC01526 Promotes Proliferation and Metastasis of Gastric Cancer by Interacting with TARBP2 to Induce GNG7 mRNA Decay
Many long noncoding RNAs play an important role in gastric cancer progression. In this study, we focused on LINC01526. Through expression and functional analyses, we obtained a preliminary understanding of the pro-cancer role of LINC01526 in gastric cancer. Furthermore, RNA pull-down and RNA immunoprecipitation chip assays demonstrated that LINC01526 interacts with TARBP2, an RNA-binding protein controlling mRNA stability. Moreover, TARBP2 could bind and destabilize GNG7 transcripts. Finally, the rescue assay disclosed that LINC01526 promoted gastric cancer progression by interacting with TARBP2, leading to the degradation of GNG7 mRNA.
Gastric cancer is the most common malignancy of the human digestive system. Long noncoding RNAs (lncRNAs) influence the occurrence and development of gastric cancer in multiple ways. However, the function and mechanism of LINC01526 in gastric cancer remain unknown. Herein, we investigated the function of LINC01526 with respect to the malignant progression of gastric cancer. We found that LINC01526 was upregulated in gastric cancer cells and tissues. The function experiments in vitro and the Xenograft mouse model in vivo proved that LINC01526 could promote gastric cancer cell proliferation and migration. Furthermore, LINC01526 interacted with TAR (HIV-1) RNA-binding protein 2 (TARBP2) and decreased the mRNA stability of G protein gamma 7 (GNG7) through TARBP2. Finally, the rescue assay showed that downregulating GNG7 partially rescued the cell proliferation inhibited by LINC01526 or TARBP2 silencing. In summary, LINC01526 promoted gastric cancer progression by interacting with TARBP2, which subsequently degraded GNG7 mRNA. This study not only explores the role of LINC01526 in gastric cancer, but also provides a laboratory basis for its use as a new biomarker for diagnosis and therapeutic targets.
Over the past decade, gastric cancer (GC) has been a major contributor to global cancer cases. With the reduction in H. pylori infections and the improvement of quality of life, the incidence of GC has gradually decreased [1]. However, the impact of GC on human health should not be underestimated, as GC still ranks fifth (5.6%) in incidence and fourth (7.7%) in mortality globally, according to the GLOBOCAN 2020 Global Cancer Statistics [2]. The occult nature of the early clinical symptoms of GC and the absence of invasive gastroscopy hinder the diagnosis of early GC; moreover, the complexity of the disease and the emergence of drug resistance limit the treatments’ effects [3,4,5,6]. Thus, the search for new GC biomarkers and therapeutic targets is particularly important. In recent years, long noncoding RNAs (lncRNAs) have gained increasing attention as a cancer biomarker for early screening, diagnosis, prognosis, and the response to drug therapy [7,8,9]. LncRNAs, a heterogeneous set of polyadenylated RNAs longer than 200 nucleotides without a protein-coding capacity [10,11], extensively participate in various physiological and pathological processes [12,13,14,15], including tumorigenesis [16,17,18]. Many lncRNAs play crucial oncogenic or tumor-suppressant roles and regulate the initiation and progression of GC. For instance, GC patients have remarkably elevated levels of LINC01503, which mediates cell cycle progression and tumorigenesis [19]; SNHG22 promotes the proliferation and invasion of GC [20]; patients with chemotherapy-resistant GC express high EIF3J-DT levels [21]; meanwhile, SEMA3B-AS1 is downregulated in gastric cardia adenocarcinoma and suppresses tumor progression [22]. Overall, the role of lncRNAs in the development of GC and its molecular mechanism deserve to be explored. In a recent study, Cheng et al. have established a prognostic signature for predicting the disease-free survival in GC patients [23]. They suggested LINC01526 as a prognostic marker for GC [23], but the function of LINC01526 has not been explored. The current study was designed to investigate the carcinogenic effect of LINC01526 in GC and the underlying mechanism involved in it. We found that LILNC01526 was highly expressed in gastric cancer tissues and cells, and LINC01526 overexpression was associated with a poor prognosis for GC patients. Moreover, loss-of-function assays indicated that LINC01526 could promote GC cell proliferation and migration in vitro and in vivo. Finally, the exploration of the mechanism revealed that LINC01526 interacts with TAR (HIV-1) RNA-binding protein 2 (TARBP2) and thereby destabilizes G protein gamma 7 (GNG7) mRNA. In summary, this study describes the role of LINC01526 in GC progression and suggests a potential biomarker for the detection or prognosis of GC.
We obtained clinical and genetic expression data from tissues of 32 normal subjects and 375 GC patients from The Cancer Genome Atlas (TCGA) dataset and analyzed them as previously described [24]. Moreover, we used TEISER (Tool for Eliciting Informative Structural Elements in RNA), a computational framework that captures both structural and sequence information contained in RNA sequences [25], to discover the structural RNA stability element (sRSE) regions bound by TARBP2.
We purchased a tissue microarray with 28 GC tissue samples and paired adjacent normal tissues from Outdo Biotechnology (Shanghai, China). We carried out FISH assays using a FISH Kit (RiboBio, Guangzhou, China) according to the manufacturer’s instructions. RiboBio Biotechnology (Guangzhou, China) designed and synthesized a unique probe targeting LINC01526. We captured and analyzed all microscopy images using a confocal laser microscope (Zeiss LSM710, Carl Zeiss, Oberkochen, Germany) [26,27].
We extracted total RNA from cells using the RNA isolator Total RNA Extraction Reagent (Vazyme, Nanjing, Jiangsu, China) according to the manufacturer’s instructions. Next, we reverse-transcribed RNA into cDNA using a HiScript III RT SuperMix qPCR kit (R323-01, Vazyme, Nanjing, China). We performed RT-qPCR using SYBR qPCR SuperMix Plus (Novoprotein Scientific Inc., Shanghai, China) on an Applied Biosystems 7500 Real-Time PCR system. We normalized the relative expression of genes to 18S ribosomal RNA (18srRNA) expression and analyzed it using the 2−ΔΔCT method. The primers used in this study were: LINC01526-F, 5′-GGAAGGTCCTGCCCTTTGTT-3′; LINC01526-R, 5′-CTGTCCTATTCAGTGGGGGC-3′; TARBP2-F, 5′-GCCTGAGGACATTCCGGTTT-3′; TARBP2-R, 5′-TCACTGTGTACTCCGGCAAC-3′; GNG7-F, 5′-AAGCTCTCTGAACAACGGGG-3′; GNG7-R, 5′-CGCTCAATCCCGGCTTCTAT-3′; CDKN2A-F, 5′-CCAGAGGCAGTAACCATGCC-3′; CDKN2A-R, AAACTACGAAAGCGGGGTGG-3′; GSDMD-F, 5′-CATGGTTCTGGAAACCCCGT-3′; GSDMD-R, 5′-CCACACTCAGCGAGTACACA-3′ POLG-F, 5′-AGGGGCATTGTTGCTTGTTG-3′; POLG-R, 5′-ACTGCCTTGGAGCAGGTTTAT-3′; 18srRNA-F, 5′-AAACGGCTACCACATCCAAG-3′; 18srRNA-R, 5′-CCTCCAATGGATCCTCGTTA-3′.
We purchased human GC cell lines (HGC-27, AGS, SNU-1, and Hs746T) and normal human gastric epithelial cells (GES-1) from the Institute of Biochemistry and Cell Biology of the Chinese Academy of Sciences (Shanghai, China). The cell lines were identified by STRs (Short Tandem Repeat) without mycoplasma contamination. We cultured all the cells using Roswell Park Memorial Institute (RPMI)-1640 medium (Gibco, Grand Island, NY, USA) containing 10% fetal bovine serum (ExCell Bio, New Zealand) and 1% penicillin-streptomycin (NCM Biotech, Suzhou, China) at 37 °C with 5% CO2 in a humidified incubator. GenePharma (Shanghai, China) designed small interfering RNAs (siRNAs) targeting LINC01526, TARBP2, GNG7, and negative control and DNA plasmids. We transfected HGC-27 and AGS cells with the siRNAs and DNA plasmids using Lipofectamine 2000 (Invitrogen, Waltham, MA, USA) according to the manufacturer’s instructions. After 48 h post-transfection, we harvested cells for the further experiments, including transfection efficiency and function assay. The siRNA sequences were as follows: si-LINC01526 #1, 5′-GCUGGUUCUAGGACCAUAU-3′; si-LINC01526 #2, 5′-GCUCCUAAAGGUUCCUUUA-3′; si-TARBP2 #1, 5′-GCUGCCUAGUAUAGAGCAA-3′; si-TARBP2 #2, 5′-GCCCACCGCAAAGAAUUCA-3′; si-GNG7 #1, 5′-GAGCUACUGUGAGCAACAU-3′; si-GNG7 #2, 5′-CCACUAACAACAUAGCCCA-3′; si-NC, 5′-UUCUCCGAACGUGUCACGU-3′.
We assessed cell proliferation through Cell-Counting Kit-8 (CCK8), colony formation, and 5-ethynyl-2-deoxyuridine (EdU) assays in HGC-27 and AGS cells. After being transfected with siRNAs for 48 h, cells were inoculated into 96-well plates (2500 cells/well). Next, we added the CCK8 solution (Beyotime Institute of Biotechnology, Nantong, China) to cells at 0, 24, 48, 72, and 96 h, and measured the absorbance at 450 nm with a microplate reader (Bio-Rad Model 680, Richmond, CA, USA) according to the standard procedure [24,28]. For the colony formation assay, we seeded the cells into six-well plates (800 cells/well) 48 h post-transfection. As the clones are visible at 2 weeks, we fixed the cells with methanol and stained them with 0.1% crystal violet (Beyotime Institute of Biotechnology, Nantong, China), as previously described [29,30]. For the EdU assay, we used a detection kit (Ribobio, Guangzhou, China) following the manufacturer’s instructions as previously described [29]. Briefly, we fixed the cells treated with 50 μM EdU labeling medium for 2 h with 4% paraformaldehyde and permeabilized them using 0.5% Triton X-100. Next, we added an anti-EdU working solution and a 4′,6-diamidino-2-phenylindole (DAPI) staining solution. Lastly, we observed EdU-positive cells under a confocal laser-scanning microscope (Zeiss LSM710, Carl Zeiss).
We assessed apoptosis by performing a terminal deoxynucleotidyl transferase-mediated dUTP nick-end-labeling (TUNEL) assay using a TUNEL Detection Kit (Vazyme, Nanjing, Jiangsu, China) as described previously [28,29]. We observed TUNEL-positive cells through a confocal laser-scanning microscope.
We evaluated the migration capacity of HGC-27 and AGS cells through Transwell assays. We seeded transfected cells with 300 μL of serum-free medium into the 24-well Transwell chamber with 8 μm pore size (Corning, Corning, NY, USA), and 700 μL of complete medium under the chamber. After 48 h, we fixed and stained the migrated cells under the chamber membrane surface.
We housed five-week-old BALB/c nude mice under specific pathogen-free conditions in individually ventilated cages with sterilized food and water. Each mouse received a subcutaneous injection of HGC-27 cells (5 × 106 in 0.1 mL of phosphate-buffered saline (PBS)) stably transfected with sh-LINC01526 or an empty vector to the two armpits (n = 5). The sh-LINC01526 plasmid was constructed by GenePharma (Shanghai, China) with the sh-LINC01526 sequences cloned into the lentiviral vector 3 (LV3) vector. We routinely measured tumor size every three days. After 15 days, we sacrificed all the mice, collected the subcutaneous tumors, and fixed them in formalin for further experiments. We calculated the tumor volumes as follows: volume = 0.5 × length × width2. All procedures involving animals and their care were approved by the Animal Ethics Committee of Affiliated Hospital of Nanjing University of Chinese Medicine (No. 2020DW-35-02, approved on 14 December 2020). To investigate cell metastasis formation in vivo, we established a tail vein injection model. We injected 3 × 10 6 cells transfected with sh-LINC01526 or an empty vector in 0.1 mL of PBS into the tail vein of nude mice. Two months later, we euthanized the mice, collected lung tissues, and fixed them in formalin. Finally, we counted the lung nodules.
To identify metastatic lesions among lung nodules, we performed HE staining. After dewaxing the paraffin sections, we stained nuclei with hematoxylin and the cytoplasm with eosin. Next, we sealed the sections with tree gum and observed the tissue structures under a microscope. For immunofluorescence [30,31], we blocked the section undergoing antigen retrieval with 1 % bovine serum albumin and incubated it with primary antibodies and secondary antibodies successively. Finally, we captured images with a confocal laser-scanning microscope and analyzed them. We used the same primary antibodies as in our previous article [30].
We transcribed LINC01526 with T7 RNA polymerase (Ambio Life, Shanghai, China) and labeled it with a Biotin RNA-Labeling Mix (Ambio Life, Shanghai, China) according to the manufacturer’s instructions. Next, we performed RNA pull-down using a Pierce Magnetic RNA-Protein Pull-Down Kit (Thermo Scientific, Waltham, MA, USA) as previously described [24]. Finally, we identified the proteins that interacted with LINC01526 by liquid chromatography–mass spectrometry (LC–MS/MS) analysis [32].
We lysed the cells with a Radio Immunoprecipitation Assay solution (Beyotime Institute of Biotechnology, Nantong, China) containing 1% protease inhibitor phenyl methyl sulfonyl fluoride, separated the obtained proteins by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and transferred them to polyvinylidene difluoride membranes (Millipore, Bedford, MA, USA). Then, we blocked the membranes with 5% skimmed milk for 1 h and incubated them with primary antibodies and then with horseradish peroxidase-conjugated secondary antibodies. Finally, we revealed the band signals via an enhanced chemiluminescent substrate and quantified them with Image-Pro plus. The anti-tubulin and anti-TARBP2 antibodies came from the Beyotime Institute of Biotechnology and Proteintech (Chicago, IL, USA).
We performed the RIP assays using a Magna RIP RNA-binding Protein Immunoprecipitation Kit (Millipore) as previously described [24]. After treating the cells with the RIP lysis buffer, we incubated the extracted proteins with anti-TARBP2 (Proteintech) or anti-IgG (Abcam, Cambridge, MA, USA) antibodies. Finally, we analyzed the purified RNAs bound to beads by RT-qPCR.
We extracted RNA from HGC-27 cells transfected with si-TARBP2 or si-NC (n = 3 in each group) and sequenced it with the 2 × 150 bp paired-end (PE150)-sequencing strategy on an Illumina NovaSeq™ 6000 platform following the vendor’s recommended protocol (San Diego, CA, USA). We selected differentially expressed genes (DEGs) based on a fold change > 2.0 and false discovery rate (FDR) < 0.05; then, we conducted Gene Ontology (GO) enrichment analyses.
We treated the cells transfected with siRNA or plasmid vectors with 1 μg/mL actinomycin D and collected them at different time points. We then evaluated the relative mRNA levels through RT-qPCR.
We performed statistical comparisons using Student’s t-test (pairs of groups) or one-way analysis of variance (ANOVA; multiple groups) via GraphPad Prism 9.0 and presented the results as mean ± standard deviation (SD). We considered p values < 0.05 as indicating statistical significance. We repeated each experiment at least three times. Biological replicates are shown in figure legend for their different respective experiments.
Based on the RNA-sequencing dataset extracted from the TCGA database, we found that GC tissues (n = 375) expressed higher LINC01526 levels than normal tissues (n = 32) (Figure 1A). Furthermore, as the overall survival (OS), disease-free survival (DFS), disease-free interval (DFI), and progression-free interval (PFI) curves showed, a high LINC01526 expression was associated with shorter survival times in patients with GC (Figure 1B–E). Next, we performed a FISH assay on 28 paired human GC tissues and corresponding adjacent tissues and confirmed that LINC01526 was highly expressed in GC tissues and localized in the cytoplasm (Figure 1F,G). Furthermore, GC cell lines (HGC-27, AGS, SNU-1, and Hs746T) also expressed higher LINC01526 levels than normal human gastric epithelial cells (GES-1) (Figure 1H). According to these findings, LINC01526 may be essential to the regulation of GC carcinogenesis and progression.
To document the biological features of LINC01526 in malignant GC progression in vitro, we performed loss-of-function experiments using HGC-27 and AGS cells, which express high LINC01526 levels (Figure 1H). The siRNAs si-LINC01526 #1 and #2 markedly and independently knocked down LINC01526 mRNA siRNAs (Figure 2A,B). Apparently, the viability of the cells transfected with si-LINC01526 diminished (Figure 2C,D). Additionally, the colony formation assays confirmed that knocking LINC01526 down inhibited GC cell colony formation (Figure 2E,F). Furthermore, the EdU, CCK8, and colony formation assays proved that downregulating LINC01526 impaired cell proliferation (Figure 2I,J). Next, the Transwell assays revealed that silencing LINC01526 suppressed the migratory capacity of HGC-27 and AGS cells (Figure 2G,H). In addition, the TUNEL assays confirmed that decreasing LINC01526 expression induced GC cell apoptosis (Figure 2K,L). These results suggest that knocking LINC01526 down suppresses GC cell proliferation and migration and promotes apoptosis in vitro.
To further elucidate the role of LINC01526 in GC tumorigenesis in vivo, we established a xenograft tumor-bearing nude mouse model by injecting HGC-27 cells stably expressing sh-LINC01526 or an empty vector to nude mice (n = 5). During the xenograft tumor growth, we measured and calculated the tumor volumes, and found that the tumors grew much more slowly in the sh-LINC01526 group than in the empty vector group (Figure 3A). Fifteen days after the injection, we sacrificed the mice. The tumors derived from the sh-LINC01526 cells were much smaller and lighter than those from the empty vector group (Figure 3B,C). It was clearly seen that tumors from the sh-LINC01526 group expressed lower LINC01526 levels compared with the empty vector group (Figure 3D). Moreover, the immunofluorescence analysis revealed that the sh-LINC01526 group had fewer Ki67-positive cells than the empty vector group (Figure 3E,F), indicating that the LINC01526 knockdown suppressed GC cell growth in vivo. Our next question was: how does LINC01526 affect GC metastasis in vivo? To answer this, we established a GC lung metastasis model by injecting HGC-27 cells transfected with sh-LINC01526 or an empty vector into the tail vein of nude mice (n = 5). Unsurprisingly, after 2 months, the sh-LINC01526 group had strikingly fewer lung metastases nodules than the empty vector group (Figure 3G,H). Similarly, the H&E staining suggested that the lung nodules derived from the tumors (Figure 3I). To evaluate whether the epithelial-mesenchymal transition played a part in the invasiveness of GC, we monitored specific epithelial–mesenchymal transition markers such as E-cadherin, N-cadherin, and vimentin. We observed more E-cadherin-positive cells and fewer N-cadherin- and vimentin-positive cells in the sh-LINC01526 group than in the empty vector group (Figure 3J,K). Taken together, these results suggest that knocking LINC01526 down suppresses GC cell growth and metastasis in vivo.
To further explore the potential molecular mechanism of LINC01526 in GC, we performed an RNA pull-down-LC-MS/MS assay and identified the potential proteins interacting with LINC01526 in the GC cells (Figure 4A). The Venn diagram analysis revealed 45 overlapping proteins from three independent RNA pull-down assays (Figure 4B). The most meaningful of these proteins was TARBP2, which had more unique peptides than the other identified proteins (Table S1). Furthermore, Western blotting and RIP analysis confirmed this abundance of binding sites in the HGC-27 and AGS cells (Figure 4C–E). In addition, the anti-TARBP2 siRNAs downregulated TARBP2 in the HGC-27 and AGS cells (Figure 4F,G). Unsurprisingly, both the CCK8 and colony formation assays confirmed that downregulating TARBP2 reduced GC cell proliferation (Figure 4H–K). The Transwell assays confirmed that silencing TARBP2 suppressed the migratory capacity of both the HGC-27 and AGS cells (Figure 4L,M). Finally, we analyzed TARBP2 expression in GC through GEPIA database (http://gepia2.cancer-pku.cn/, accessed on 23 September 2022). The result showed that TARBP2 was overexpressed in GC tissue compared with normal tissue (Figure S1A).
TARBP2, a double-stranded, RNA-binding protein [33], binds and destabilizes its target mRNAs [34]. We identified the tumor suppressors repressed by TARBP2 through RNA sequencing. After a TARBP2 knockdown in the HGC-27 cells, we found 313 upregulated transcripts and 349 downregulated transcripts (Figure 5A,B, and Table S2). Afterward, the GO analysis revealed that these DEGs were enriched in many biological processes, including the “cell cycle process”, “microtubule cytoskeleton organization”, “protein-containing complex assembly”, “DNA biosynthetic process”, “cellular response to DNA damage stimulus”, “regulation of translation”, “DNA metabolic process”, “gene expression”, “RNA transport”, and “metabolism of proteins” (Figure 5C,D). Among these DEGs, CDKN2A [35,36,37], GNG7 [38], GSDMD [39,40,41,42], and POLG [43] are known tumor suppressors in GC. An RT-qPCR analysis confirmed that GNG7 and CDKN2D were sharply overexpressed after the TARBP2 knockdown in the HGC-27 cells (Figure 5E). Subsequently, to confirm the target gene of TARBP2, we carried out RNA stability assays. In the HGC-27 cells treated with actinomycin D, upregulating TARBP2 dramatically decreased the GNG7 mRNA’s half-life, and had a minor effect on the CDKN2A mRNA’s stability (Figure 5F,G). Moreover, based on the GEPIA database, we found that the expression of GNG7 in GC was lower than normal tissues (Figure S1B). Thus, we speculated that GNG7 is the major downstream target mRNA of TARBP2 in GC cells.
Downregulating TARBP2 and LINC01526 in HGC-27 and AGS cells, respectively, significantly upregulated GNG7 (Figure 5E and Figure 6A–C). Consistently, the tumors derived from the sh-LINC01526 group also expressed higher levels of GNG7 (Figure 6D). However, what kind of functional connections do they have? According to previous studies, TARBP2 preferentially binds double-stranded RNAs (e.g., stem-loops), with high GC closely resembling sRSE (GC-rich structural cis-regulatory RNA elements) [44]. Goodarzi et al. confirmed that TARBP2 negatively regulates the stability of amyloid precursor protein (APP) and zinc finger protein 395 (ZNF395) by binding sRSEs in the 3′UTR (untranslated regions) and promotes cancer [34]. To identify potential TARBP2-binding RNAs in GC, we employed TEISER, a framework for identifying the structural motifs that are informative of whole-genome measurements across all the transcripts [25]. Consistent with our estimate, we found eleven sRSEs in the 3′UTR region of GNG7 that potentially binds to TARBP2 (Figure 6E and Table S3). More importantly, the protein level of TARBP2 remained virtually unchanged (Figure 6F,G), but the RIP assay confirmed that markedly reduced amounts of GNG7 were precipitated with TARBP2 in the LINC01526-knockdown HGC-27 and AGS cells (Figure 6H). Conversely, an LINC01526 overexpression increased the amount of GNG7 bound to TARBP2 in the HGC-27 and AGS cells (Figure 6H). Subsequently, the RNA stability assays confirmed that downregulating LINC01526 increased the GNG7 mRNA half-life and overexpressing TARBP2 did not attenuate this increase in the HGC-27 and AGS cells (Figure 6I,J), suggesting that LINC01526 is required for TARBP2-mediated GNG7 mRNA decay. Furthermore, overexpressing LINC01526 decreased the GNG7 mRNA half-life and si-TARBP2 could rescue this change (Figure 6K,L). This finding demonstrated that LINC01526 affected the GNG7 mRNA stability in a manner dependent on TARBP2. Finally, the expression levels of GNG7 were negatively correlated with both LINC01526 and TARBP2 expression levels in the GC tissues (Figure 6M,N).
To further explore the biological relationship between LINC01526/TARBP2 and GNG7 in GC progression, we carried out a rescue experiment. We transfected the HGC-27 and AGS cells with si-LINC01526 or si-TARBP2, both alone or co-transfected with si-GNG7. The CCK8 and colony formation assays revealed that downregulating GNG7 partially rescued the cell proliferation inhibited by LINC01526 or TARBP2’s silencing (Figure 7A–D). Additionally, the Transwell assay indicated that co-transfection significantly increased the migratory cell count (Figure 7E,F). Taken together, our results demonstrate that LINC01526 interacts with TARBP2, thereby regulating GNG7 mRNA stability and expression, and eventually promoting GC cell proliferation and migration (Figure 7G).
The difficulty of early diagnosis and the development of drug resistance contribute to the high mortality rate associated with GC [45]. Several lncRNAs can promote or inhibit the initiation and migratory progression of GC in various ways [8,9]. Many lncRNAs have been identified as potential biomarkers for a GC diagnosis and therapy [46,47]. Among those, bioinformatics analyses have identified LINC01526 and 12 other lncRNAs as prognostic markers for GC [23], but the functions and mechanisms of LINC01526 in GC remain elusive. The present study confirmed, through bioinformatic, RT-qPCR, and FISH analyses, that LINC01526 was significantly upregulated in human GC tissues and associated with a poor outcome. Moreover, the loss-of-function assay confirmed that knocking down LINC01526 suppressed GC cell proliferation and migration in vitro and in vivo, suggesting that LINC01526 promotes GC progression. LncRNAs regulate gene expression through gene modifications, histone modifications, and chromatin remodeling without altering the DNA sequence at the pre-transcriptional level [48,49]. Moreover, they act as competing endogenous RNAs, sequestering micro RNAs to regulate their translation [50], or interact with specific proteins to maintain mRNA stability or induce mRNA decay at the post-transcriptional level [51,52,53,54]. In this article, the RNA pull-down and RIP assays demonstrated the physical connection between LINC01526 and TARBP2. TARBP2, a double-stranded, RNA-binding protein, interacts with GC-rich stem-loops in the 3′UTR region [55] and is a functional component of the RNA interference silencing complex. Previous studies have proved that TARBP2 participates in viral infections [33], micro RNA biogenesis [56], and tumorigenesis [57]. TARBP2 might act as a tumor promoter in lung cancer [34], breast cancer [58], melanoma [59], hepatocellular carcinoma [60], adrenocortical carcinoma [61], and diffuse large B-cell lymphoma [62], but as a tumor suppressor in osteosarcoma [63] and Ewing sarcoma [64]. However, the role and mechanism of TARBP2 in GC progression had remained uncertain. The CCK8, colony formation, and Transwell assays jointly confirmed that TARBP2 promotes GC cell proliferation and migration in vitro. Our RNA sequencing, GO analysis, RNA stability assays, and TEISER analysis demonstrated that TARBP2 targets GNG7 mRNA. GNG7, a member of the large G protein gamma family, is related to transmembrane-signaling pathways and is engaged in cell contact-induced growth arrest, thereby suppressing uncontrolled cell proliferation [65,66]. A large body of evidence indicates that GNG7 is downregulated in various tumors, including esophageal cancer [67], lung adenocarcinoma [68], clear cell renal cell carcinoma [69], etc. In gastrointestinal tract cancer, GNG7 suppresses cell growth in vitro and in vivo by upregulating the expression of the cyclin-dependent kinase inhibitor p27Kip1 [66]. In our study, LINC01526 only enhanced the binding of TARBP2 to GNG7 but did not affect TARBP2 protein levels. Furthermore, silencing LINC01526 increased GNG7 mRNA stability. Vitally, the capacity of TARBP2 to bind and decay GNG7 mRNA depended on LINC01526, and LINC01526 decays GNG7 mRNA through targeting TARBP2. In addition, the expression levels of GNG7 were negatively correlated with both LINC01526 and TARBP2 in the GC tissues. Finally, the rescue experiment confirmed the role of the LINC0526/TARBP2/GNG7 axis in GC. In this study, some limitations exist in the knockdown experiments in vitro using siRNA, which yields a transient knockdown and is also associated with multiple off-target effects. Both stable knockdown experiments using lentiviral vectors and knockout experiments in the future will be more credible. Additionally, they will be employed in a further study.
Overall, this study has shown that LINC01526 was upregulated in GC tissues. The elevated LINC01526 levels promoted GC cell proliferation and migration in vitro and in vivo and were associated with poor outcomes in patients. Furthermore, LINC01526 interacted with TARBP2, and “LINC01526-TARBP2” bound and decayed GNG7 mRNA. Finally, knocking down GNG7 rescued the cell proliferation and migration inhibited by LINC01526 or TARBP2’s silencing. In conclusion, LINC01526 promotes GC progression through interacting with TARBP2, thereby inducing GNG7 mRNA degradation. The mechanistic characterization of LINC01526 may help to shed light on the future development of lncRNA-based GC therapies. | true | true | true |
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PMC9562639 | Yibo Bian,Yang Wang,Shufen Xu,Zhishuang Gao,Chao Li,Zongyao Fan,Jie Ding,Keming Wang | m6A Modification of Long Non-Coding RNA HNF1A-AS1 Facilitates Cell Cycle Progression in Colorectal Cancer via IGF2BP2-Mediated CCND1 mRNA Stabilization | 27-09-2022 | colorectal cancer,m6A,HNF1A-AS1,IGF2BP2,CCND1 | Background: Long non-coding RNAs modulate tumor occurrence through different molecular mechanisms. It had been reported that HNF1A-AS1 (HNF1A Antisense RNA 1) was differently expressed in multiple tumors. The role of HNF1A-AS1 in colorectal cancer was less analyzed, and the mechanism of regulating the cell cycle has not been completely elucidated. Methods: Differentially expressed lncRNAs were screened out from the TCGA database. HNF1A-AS1 was examined in CRC clinical samples and cell lines by RT-qPCR. CCK8 assay, colony formation assay, flow cytometry, transwell assays, tube forming assay and vivo experiments were performed to study the function of HNF1A-AS1 in CRC tumor progression. Bioinformatic analysis, luciferase report assay, RNA pull-down and RIP assays were carried out to explore proteins binding HNF1A-AS1 and the potential downstream targets. Results: Our results showed that HNF1A-AS1 was upregulated in CRC and associated with unfavorable prognosis. HNF1A-AS1 promoted proliferation, migration and angiogenesis, accelerated cell cycle and reduced cell apoptosis in CRC. Bioinformatics prediction and further experiments proved that HNF1A-AS1 could promote CCND1 expression by suppressing PDCD4 or competitively sponging miR-93-5p. Meanwhile, METTL3 mediated HNF1A-AS1 m6A modification and affected its RNA stability. HNF1A-AS1/IGF2BP2/CCND1 may act as a complex to regulate the stability of CCND1. Conclusion: In summary, our result reveals the novel mechanism in which m6A-mediated HNF1A-AS1/IGF2BP2/CCND1 axis promotes CRC cell cycle progression, along with competitively sponging miR-93-5p to upregulate CCND1, demonstrating its significant role in cell cycle regulation and suggesting that HNF1A-AS1 may act as a potential prognostic marker of colorectal cancer in the future. | m6A Modification of Long Non-Coding RNA HNF1A-AS1 Facilitates Cell Cycle Progression in Colorectal Cancer via IGF2BP2-Mediated CCND1 mRNA Stabilization
Background: Long non-coding RNAs modulate tumor occurrence through different molecular mechanisms. It had been reported that HNF1A-AS1 (HNF1A Antisense RNA 1) was differently expressed in multiple tumors. The role of HNF1A-AS1 in colorectal cancer was less analyzed, and the mechanism of regulating the cell cycle has not been completely elucidated. Methods: Differentially expressed lncRNAs were screened out from the TCGA database. HNF1A-AS1 was examined in CRC clinical samples and cell lines by RT-qPCR. CCK8 assay, colony formation assay, flow cytometry, transwell assays, tube forming assay and vivo experiments were performed to study the function of HNF1A-AS1 in CRC tumor progression. Bioinformatic analysis, luciferase report assay, RNA pull-down and RIP assays were carried out to explore proteins binding HNF1A-AS1 and the potential downstream targets. Results: Our results showed that HNF1A-AS1 was upregulated in CRC and associated with unfavorable prognosis. HNF1A-AS1 promoted proliferation, migration and angiogenesis, accelerated cell cycle and reduced cell apoptosis in CRC. Bioinformatics prediction and further experiments proved that HNF1A-AS1 could promote CCND1 expression by suppressing PDCD4 or competitively sponging miR-93-5p. Meanwhile, METTL3 mediated HNF1A-AS1 m6A modification and affected its RNA stability. HNF1A-AS1/IGF2BP2/CCND1 may act as a complex to regulate the stability of CCND1. Conclusion: In summary, our result reveals the novel mechanism in which m6A-mediated HNF1A-AS1/IGF2BP2/CCND1 axis promotes CRC cell cycle progression, along with competitively sponging miR-93-5p to upregulate CCND1, demonstrating its significant role in cell cycle regulation and suggesting that HNF1A-AS1 may act as a potential prognostic marker of colorectal cancer in the future.
RNA-sequencing datasets of CRC patients were downloaded from the TCGA website. Our inclusion criteria were as follows: (1) histopathologically confirmed colorectal cancer; (2) case-related clinical information, including age, gender, treatment, staging, survival time, etc.; (3) there was no distant metastasis before surgery; (4) other malignant tumors were excluded. A total of 52 paired colorectal samples were included, including 23 colorectal cancer samples in stage III/IV and 52 colorectal normal tissue samples. The whole process was performed based on the publication guidelines from the TCGA database.
In total, 52 pairs of tissue specimens from CRC patients were collected in the study, including colorectal tissues and their respective adjacent mucosal tissues. The patients included in the study had accepted radical surgery in the Second Affiliated Hospital of Nanjing Medical University from 2012 to 2021. Pathological diagnosis and staging were evaluated based on the eighth edition cancer staging manual. Approved by the Ethics Committee of Nanjing Medical University (ethical approval number: KY No. 121), all the patients included agreed to join in the study and signed the relative informed consent. Six colorectal cancer cell lines (HCT116, HT-29, SW480, SW620, DLD-1 and LOVO), human umbilical vein endothelial cells (HUVEC) and normal human colonic mucosal cell line (HcoEpic) were all from the Sciences cell bank of Chinese Academy. All these cell lines were cultivated in DMEM or RPMI1640, which were supplied with 10% fetal bovine serum (Gemini, Woodland, CA, USA), 100 mg/mL streptomycin and 100 U/mL penicillin.
Three shRNAs targeting HNF1A-AS1, negative control, HNF1A-AS1 over-expressing plasmid, miRNA mimics and other targeted shRNAs were designed and purchased from GenePharma Company (Shanghai, China). They were transfected into CRC cells with lipo2000 (Invitrogen, Carlsbad, CA, USA) following the manufacturer’s manual. The sequences of all shRNAs were summarized in Table S1.
Total RNA from tissues and cells was extracted by the Trizol reagent (Invitrogen, USA) and reversely transcribed into cDNA, which acted as the template to run RT-qPCR through SYBR Green Master (Vazyme, Nanjing, China) according to the instructions from the manufacturer. The expression of relative genes was analyzed by the comparative threshold cycle (2−ΔΔCt) method and normalized to GAPDH. All the primers used were outlined in Table S2.
Protein from the treated and untreated HCT116 and LOVO cells was extracted by RIPA (Beyotime, Nantong, China). The protein lysates were separated by SDS-PAGE and then transferred onto PVDF membranes. ECL chromogenic substrate was used for densitometry quantification after incubating specific antibodies at 4 °C for 12 h. Protein detection was performed using rabbit monoclonal anti-CCND1 (Abcam, Cambridge, UK, ab134175), anti-CDK4 (Abcam, ab108357), anti-P21 (Abcam, ab109520), anti-casepase3 (CST, #14220), anti-PARP (Proteintech, Rosemont, IL, USA, 13371-1-AP), anti-PDCD4 (Abcam, ab80590), anti-Vimentin (CST, #5741), anti-N-cadherin (Abcam, ab76011), anti-E-cadherin (Abcam, 76011), anti-METTL3 (Proteintech, 15073-1-AP), anti-IGF2BP2 (Proteintech, 11601-1-AP),anti-FLAG (Proteintech, 20543-1-AP), anti-pAKT (CST, #4060), anti-AKT (CST, #9272), anti-PI3K (CST, #4249), anti-pPI3K (CST, #4228). GAPDH (Affinity, West Bridgeford, UK, AF7021) was applied as the internal control.
The CCK8 assay was used to determine the proliferation ability. A total of 2000–4000 transfected tumor cells were seeded into 96-well plates, and the CCK8 solution was added every 24 h to detect absorbance at 450 nm with a microplate reader. In colony formation, 500–1000 cells were seeded in 6-well plates and fixed with methanol and stained with 0.1% crystal violet after 14 days. A total of 5 × 104 transfected cells were added to the upper chamber of insert (Millipore, Sandiego, CA, USA) and then fixed after 24–48 h. The number of formed colonies and cells migrating through the membrane were pictured and analyzed.
The treated cells were collected after 48 h of transfection and resuspended with 100 uL binding buffer, mixed with 5 uL fluorescently labeled AnnexinV-FITC and 5 uL PI Staining Solution (Vazyme, China). The solution was incubated for 5–15 min and tested on the machine immediately after adding the binding buffer. As for cell cycle analysis, 75% ethanol was used to resuspend and fix cells overnight at −20 °C. Cells were stained by propidium iodide stain and incubated in darkness for 15 min, detected by flow cytometry (FACSCalibur, Becton Dickinson, Franklin Lakes, NJ, USA).
Briefly, 50 μL Matrigel (ABW-Bio, Shanghai, China) was seeded into 96-well plates (Nest, Wuxi, China) and put in a cell incubator for 30 min until Matrigel was coagulated. Then, 4 × 104 vascular endothelial cells in 100 μL ECM (endothelial cell medium) (5% fetal bovine serum, 1% streptomycin and 1% ECGS) were added above Matrigel. Then, 100 μL supernatant of sh-NC cell and sh-HNF1A-AS1 cells was added into the plates, respectively. Within 12 h, the vascular endothelial cells stimulated by the supernatant grew and were pictured by the microscope. The length of the cell tubes was analyzed by ImageJ.
The related wild-type (WT) and mutant plasmids were constructed by Genebay company in Nanjing. The cells were plated in a 24-well plate. After 48 h of plasmid transfection, 200 uL lysis solution was added to each well at room temperature and incubated for 10 min. Next, the supernatant was collected after centrifugation, then100 uL of the supernatant was mixed with 100 uL of the luciferase reporter working solution.The firefly luciferase F value was tested on the machine and the renilla luciferase R value was measured after adding the terminating solution. The ratio of F/R was calculated for further analysis.
The animal experiments were approved by the Institutional Animal Care and Use Committee at Nanjing Medical University. Ten BALB/C nude mice (4 weeks old, female) were injected in 1 × 106 HCT116 cells in 100 uL PBS at each side. The tumor size was detected every four days after the injection of cells and calculated according to the formula (0.5 × tumor length × tumor short length2). Finally, the mice were scarified, and all tumors were stored for subsequent RNA extraction and IHC analysis.
At least 2 × 107 cells were collected and then lysed on ice in RIP lysis buffer according to the instructions provided by the Magna RIP Kit (Millipore, Sandiego, CA, USA). The lysates were conjugated with 5 ug of rabbit anti-IGF2BP2 (Proteintech, China) or 5 ug rabbit IgG antibody (Millipore, Sandiego, CA, USA) with magnetic beads in 1 mL wash buffer at 4 °C overnight. Then, the RNA-protein complex was digested and purified at 55 °C for half an hour after adding the proteinase K buffer. Total RNA was extracted by the Trizol reagent, and the expressions of related genes were detected by RT-qPCR.
The full-length plasmid of HNF1A-S1 was transcribed in vivo with mMESSAGE mMACHINE Kit (Thermo, Waltham, MA, USA), and then, the transcribed RNA was purified by MEGAclear Kit (Thermo, USA). Next, the RNA was labeled with biotin by 5′- and 3′-RACE Kit (Thermo, Waltham, MA, USA) based on the manufacturer’s instructions. A total of 50 pmol biotinylated RNA was incubated with A/G magnetic beads at room temperature for 30 min approximately. Then, about 6 × 106 cells were lysed in 400 uL of IP lysis (Beyotime, Nantong, China) added with PMSF to ensure a sufficiently high protein concentration. The washed magnetic beads were incubated with protein lysate in 100 uL protein-RNA binding buffer (Thermo, Waltham, MA, USA) at 4 °C for 2 h. Finally, the proteins binding to RNA were washed and collected for Western blot and silver staining.
MeRIP was performed based on the previous protocol using the MeRIP m6A Kit (MerckMillipore, Darmstadt, Germany) [1,2]. Briefly, the total RNA was extracted by the Trizol regent and then treated with DNase I to avoid DNA contamination. A total of 100 ug purified RNA was fragmented into 300 bps by fragment reagents. After incubating A/G magnetic beads with anti-m6A antibody (Millipore, Sandiego, CA, USA) and anti-IgG for 30 min at room temperature, the fragmented RNA was added into the magnetic beads at 4 °C overnight in 500 uL of the RIP buffer. An amount of 10 ug RNA was saved as input. Then, the following procedure was the same as the RIP method.
An amount of 5 ug/mL Actinomycin D (Abmole, Houston, TX, USA) was added into the cells after 48 h of transfection; then, the cells were harvested at 0, 2, 4, 6, 8 h or 0, 20, 40, 60 and 80 min, respectively. Total RNA was extracted by Trizol, and the expression of related genes was analyzed by RT-qPCR normalized to GAPDH. The half-life of mRNA was calculated according to the related formula.
The probe targeting HNF1A-S1 was designed by Ribo company (Guangzhou, China). Cells were fixed by 4% paraformaldehyde, and thencells were incubated with the probe at 37 °C overnight after permeabilization by PBS containing 0.5% Triton X-100 following the manufacturer’s instructions. The next day, cells were washed with SSC (Saline Sodium Citrate) buffer at 42 °C several times and incubated with anti-IGF2BP2 (Proteintech, 11601-1-AP, 1:200) overnight at 4 °C after blocking 30 minutes at room temperature. On the third day, the cells were washed and incubated with Alexa Fluor 488 anti-rabbit IgG (Abcam, 1:200, ab150077, Cambridge, UK). Nuclei were stained by DAPI, and then, the cells were pictured by confocal microscopy (LSM710, Jena, Thuringia, Germany).
GraphPad Prism version 8.0 (Sandiego, CA, USA), Rstudio version 4.0.3 and Image J version 5.4 were used for data analysis and graphing. All experiments were independently repeated three times. The data differences between the two groups were analyzed by Student’s t-test, while ANOVA was used to compare more than two groups. The Chi-Square test was used to analyze clinicopathological data, and p < 0.05 was considered to be a significant difference.
Malignant tumors have become the main origin of disease-related deaths around the world. Based on the latest statistics from the International Agency for Research on Cancer (IRIC), there were around 1,898,160 newly diagnosed cancer patients in the United States in 2021 [3]. The morbidity and mortality of colorectal cancer, a common gastrointestinal tumor, currently ranks third in both men and women [4]. Due to the insidious symptoms at initial onset, about 15% of the newly diagnosed CRC patients are accompanied by liver metastasis, and most of them lose the opportunity for radical surgery. The average 5-year survival rate of CRC is around 60%, and it had not been significantly improved with the widespread use of targeted drugs and immunotherapy. Thus, it is urgent to explore new markers that can effectively screen tumors, guide treatment and predict prognosis. Long non-coding RNAs are the special kind of RNAs with more than 200 nucleotides in length, which have no ability to encode proteins. They could modulate gene expression through chromatin modification, transcriptional regulation, post-transcription modification and in other ways [5]. LncRNAs play biological roles partly through competitively sponging microRNAs. The complementary sequences between microRNAs and target RNA transcripts, which is known as RISC (programed RNA-induced silencing complex), could silence the gene expression of target genes [6]. The competitive binding relationship also exists between lncRNAs and miRNAs. LncRNA PVT1 regulates the downstream target gene RUNX2 not only through the PVT1/miR-30d-5p/RUNX2 axis [7] but also through the PVT1/miR-455/RUNX2 axis [8,9]. As the most common epigenetic modification in eukaryotic cells, N6-methylation occurs in nearly 90% of RNAs, and it not only regulates mRNA transcription, processing, degradation and translation but also modulates much non-coding RNAs (ncRNAs). m6A modification takes part in the progression of multiple diseases, such as heart failure, glioblastoma, colorectal cancer and so on [2,10,11,12,13]. As a dynamic and reversible process, m6A methylation modification is mainly mediated by methyltransferases, demethylases and methylation recognition proteins, whose functions are to increase, remove and recognize the m6A methylation spot, respectively. There are increasing research works regarding m6A methylation modulation in lncRNAs. LncRNA FAM225A was upregulated in nasopharyngeal carcinoma (NPC) tumor tissue, and high expression of FAM225A was related with poor clinical prognosis. MeRIP experiments revealed that after silencing METTL3, the m6A level of FAM225A decreased, along with the decreased stability and expression of FAM225A [14]. There have been studies about the pivotal role of HNF1A-AS1 in NSCLC, hepatocellular carcinoma and gastric cancer [15,16,17,18,19]. In CRC, studies have shown that HNF1A-AS1 mainly played biological roles through competitively interacting with microRNAs, such as miR-34a, miR-124 and so on [20,21]. Our research explored the mechanisms of HNF1A-AS1 regulating the cell cycle in CRC deeply, which had not been studied previously. Functional assays revealed that HNF1A-AS1 could promote proliferation, migration and angiogenesis in CRC. Mechanically, we found that HNF1A-AS1 could sponge miR-93-5p by forming the HNF1A-AS1/miR-93-5p/AGO2 complex to upregulate CCND1, and it could stabilize the CCND1 mRNA mediated by METTL3-induced m6A modification as well. HNF1A-AS1 could also suppress PDCD4 to ultimately regulate CCND1 by activating the PI3K/AKT pathway. Our results revealed that HNF1A-AS1 had the potential to be a diagnosis target and novel prognosis biomarker in colorectal cancer.
To explore the potential long non-coding RNAs influencing colorectal cancer progression, we screened out 30 tumor patients with stage III/IV and 30 corresponding normal patients totally from the TCGA-CRC database. After differential analysis by edgeR, we picked up 200 potential long non-coding RNAs for further exploration based on their base expression of genes and p values. Finally, six highly expressed lncRNAs were chosen for further exploration (Figure 1A). The expressions of PCAT7 and GAS6-AS1 were shown lower than HNF1A-AS1 in several human CRC cell lines (Figure S1A). According to the TCGA database, HNF1A-AS1 was highly expressed in several cancers, including colon cancer and rectum cancer, suggesting its role as an oncogene (Figure 1B). Additionally, high expression of HNF1A-AS1 was related with poor overall survival based on the TCGA database (Figure 1C). In our 52 paired CRC patients’ samples, 70% of whom did not have positive metastasis and most of whom were diagnosed at an early stage, HNF1A-AS1 was higher expressed in tumor tissues than in normal tissues based on RT-qPCR results (Figure 1D). HNF1A-AS1 expression was upregulated in 65.4% (34 out of 52) of CRC tissues, as shown in Figure 1E. Subsequently, we then analyzed the relationship between HNF1A-AS1 and clinicopathologic factors in our samples (Table 1). The results demonstrated that high expression of HNF1A-AS1 was correlated with higher pathological stage (III/IV), positive lymph node metastasis and distant metastasis (Figure 1F,G). Meanwhile, patients with a high expression of HNF1A-AS1 showed shorter overall survival time than low-expression patients through the Kaplan–Meier analysis (Figure 1H). In conclusion, the high expression of HNF1A-AS1 was correlated with unfavorable prognosis in CRC patients.
Firstly, we detected the expression of HNF1A-AS1 in representative colorectal cancer cell lines by RT-qPCR, and the result suggested that it was upregulated in HT-29, HCT116 and LOVO cell lines compared with the human normal colon epithelial cell (HcoEpic) (Figure 2A). Thus, we selected HCT116 and LOVO cell lines for further research. Then, we designed the HNF1A-AS1 expression vector and three shRNAs (small hairpin RNAs) to explore its biological role in CRC in which shRNA1 and shRNA2 had a better knockdown efficiency and were chosen for later experiments (Figure 2B). The proliferation ability of HNF1A-AS1 was examined through CCK8 and colony formation experiments (Figure S1B,C). It was shown that a knockdown of HNF1A-AS1 significantly suppressed cell viability, while over-expression of HNF1A-AS1 increased cell viability. Meanwhile, the fraction of apoptotic cells was increased significantly (Figure 2C), and cell cycle was suppressed at the G0/G1 phase after silencing HNF1A-AS1 in HCT116 and LOVO cells through flow cytometry (Figure 2D). Our results also demonstrated that a knockdown of HNF1A-AS1 inhibited the cell migration and invasion abilities in both cell lines (Figure 2E), while over-expression of HNF1A-AS1 augmented the migration and invasion ability (Figure S1D). Tube formation assays were performed to explore cell angiogenesis ability. Results revealed that silencing HNF1A-AS1 weakened angiogenesis, while over-expressing HNF1A-AS1 promoted angiogenesis (Figure S1E). Next, we detected the relevant proteins regulating cell cycle (p21, G1-S check point protein like CCND1 and CDK4), cell death (caspase3, PARP) and EMT, which further supported our results (Figure 3A). CCND1 and CDK4 (cyclin-dependent kinase 4), which promoted the G1-S phase point transmission, were downregulated when silencing HNF1A-AS1, indicating that a knockdown of HNF1A-AS1 restrained the cell cycle progression. As a typical tumor suppression gene, p21 was upregulated after a knockdown of HNF1A-S1, supporting the role of HNF1A-AS1 in promoting the cell cycle further. Consistent with the apoptosis results, sh-HNF1A-AS1 cells expressed a significantly higher level of apoptosis-related proteins, including cleaved PARP and cleaved caspase3. In addition, N-cadherin and Vimentin proteins, playing important roles in EMT (Epithelial-mesenchymal transition), were decreased, while E-cadherin was higher expressed in sh-HNF1A-AS1-treated CRC cells. These investigations suggested that HNF1A-AS1 exerted critical influences on CRC cells by affecting the cell cycle, apoptosis and migration. Overall, our results demonstrated that HNF1A-AS1 promoted CRC cell progression in vitro.
HCT116 cells were transfected with empty vector or shHNF1A-AS1 to establish the tumor model in four-week-old BALB/c nude mice to explore HNF1A-AS1’s biological role in vivo. The treated cells were injected into both axilla of the same nude mouse, respectively (Figure 3B). The volumes of the tumors were measured every 4 days. Twenty-four days after injection, the shHNF1A-AS1 group showed a lower speed of tumor growth contrasted with the empty vector group (Figure 3C), as well as lower tumor volume and weight (Figure 3D). The expression of HNF1A-AS1 was reduced in the shHNF1A-AS1 group compared with the empty vector group based on RT-qPCR results (Figure 3E). Furthermore, IHC analysis revealed that tumors from the HNF1A-AS1-knockdown group had a weaker expression of Ki67 and CCND1 than those in the empty vector group (Figure 3F). Therefore, our results revealed that HNF1A-AS1 could promote CRC progression in vivo.
Apart from the differently expressed long non-coding RNAs, after analyzing 30 CRC patients in stage III/IV and 30 normal patients, 356 differentially expressed miRNAs (DEmiRNAs) and 5213 differentially expressed mRNAs (DEmRNAs) were also obtained from the same TCGA-CRC database. A total of 44 microRNA families aligned with HNF1A-AS1 were predicted from the miRcode website; 14 miRNAs were obtained by intersecting the matched miRNAs with 356 DEmiRNAs. Then, we obtained 936 mRNAs through predicting the aligned mRNA of these 14 miRNAs in miRDB, TargetScan and other websites. Intersecting these 936 mRNAs with 5213 differentially expressed mRNAs, we obtained 155 mRNAs, which could be the potential downstream genes of HNF1A-AS1 (Figure 4A). After the GO cluster analysis of the 155 mRNAs, it was found that the top three items clustered were growth and development regulation, cell cycle G1/S phase transition and regulation of cell division. In the KEGG pathway clustering analysis, the top three entries were tumor microRNAs, PI3K-Akt signaling pathway and cellular senescence (Figure 4B). The clustered genes among the top three entries (CCND1, PDCD4, VEGFA, SOX4 and so on) in the biological process were examined by RT-qPCR after silencing HNF1A-AS1. The results showed the expression of CyclinD1 (CCND1) was downregulated, and programed cell death 4 (PDCD4) was increased in both cell lines (Figure S2A). According to the analysis from the TCGA database, CCND1 was highly expressed, while PDCD4, as a tumor suppressor gene, was less expressed in COAD and READ than normal tissues (Figure S2B). Additionally, CCND1 and PDCD4 were both significant genes regulating the cell cycle, which corresponded to the KEGG analysis. We then further explored the protein expression of CCND1 and PDCD4 through Western blot assays. Our results suggested that CCND1 was downregulated (Figure 3A), and PDCD4 was upregulated after knocking down HNF1A-AS1 (Figure 4C). Meanwhile, the expression of CCND1 increased, and PDCD4 decreased after over-expressing HNF1A-AS1. The mRNA expression of CCND1 and PDCD4 had similar change in the cell lines (Figure 4C). Thus, we chose CCND1 and PDCD4 as the downstream target genes of HNF1A-AS1 for further exploration. We performed rescue experiments to further clarify the regulatory roles of CCND1 and PDCD4 in HNF1A-AS1. The relative protein expression of CCND1 and PDCD4 in the rescue assays was shown in Figure S2C. It turned out that the proliferation ability of CRC cells was restored after the over-expression of CCND1 or knockdown PDCD4 in CRC cells induced by silencing HNF1A-AS1 through CCK8 and colony formation assays. Similarly, over-expression of CCND1 or silencing PDCD4 could reverse the migration ability caused by silencing HNF1A-AS1 (Figure S2D,E). From the results above, we confirmed that HNF1A-AS1 could regulate CRC progression through regulating CCND1 and PDCD4.
We performed subcellular fraction experiments to identify the location of HNF1A-AS1 in HCT116 and LOVO cell lines to explore its specific mechanism (Figure 4D). HNF1A-AS1 was distributed in both the nucleus and the cytoplasm, while its ratio in the cytoplasm was much higher. The result implied that HNF1A-AS1 could participate in the transcriptional and post-transcriptional regulation of downstream genes. It was verified that lncRNAs could regulate downstream gene expression by competitively sponging specific microRNAs in the cytoplasm. Therefore, we used the Starbase and miRWalk websites to predict the potential miRNAs binding CCND1 while using miRcode to predict the potential miRNAs binding HNF1A-AS1. After intersecting these results with 356 differentially expressed miRNAs, we screened out 5 miRNAs, which could interact with HNF1A-AS1 and CCND1 in the meantime (Figure 4E). Then, we detected the expression of five miRNAs after silencing HNF1A-AS1 in HCT116 and LOVO cell lines. The result showed that only the expression of miR-93-5p increased, while the others decreased or had no change (Figure 4E,F). Therefore, we chose miR-93-5p for furtherstudy. miR-93-5p was highly expressed in normal tissues from the TCGA database, and a correlation analysis of 52 CRC samples using RT-qPCR showed that HNF1A-AS1 was negatively correlated with miR-93-5p. At the same time, we also verified that the expression of miR-93-5p decreased when over-expressing HNF1A-AS1 (Figure 4G). Then, we carried out the functional recovery experiments to explore the effect of miR-93-5p on HNF1A-AS1. miR-93-5p over-expression significantly suppressed the cell proliferation ability mediated by over-expressing HNF1A-AS1 through cck8 and colony formations. Similarly, the migration ability of CRC cells was weakened after over-expressing miR-93-5p (Figure 4H and Figure S2F). The over-expression efficiency of miR-93-5p was examined by real-time qPCR (Figure 4I). We constructed wild-type and mutant plasmids of CCND1 based on the high-scoring binding site according to the Starbase prediction results (Figure 4J). The dual luciferase reporter experiment result in the HEK293T cell demonstrated that luciferase activity declined after co-transfection of miR-93-5p mimics and CCND1-3’UTR-WT, while it had no significant change after co-transfection of CCND1- 3’UTR-MUT and miR-93-5p mimics, suggesting the direct interaction between miR-93-5p and CCND1 (Figure 4K). miRNAs were confirmed to regulate RNA degradation or translational suppression through interacting with their target genes in a AGO2-dependent way. Therefore, we conducted the RIP assay to find that AGO2 could combine with HNF1A-AS1 and miR-93-5p, illustrating that HNF1A-AS1 could affect CCND1 through forming the HNF1A-AS1/AGO2/miR-93-5p complex (Figure 4L). Additionally, CCND1 was decreased in both the RNA and the protein level after over-expressing miR-93-5p in HCT116 and LOVO cell lines (Figure 4M). In summary, HNF1A-AS1 could promote CCND1 through sponging miR-93-5p in the cytoplasm.
Apart from sponging miRNAs to play biological roles, lncRNAs could also interact with RNA binding proteins (RBPs) to regulate downstream genes. Then, we performed the RNA pull-down assays to explore the potential RBPs interacting with HNF1A-AS1. Silver staining showed that there was a significantly differently expressed protein around 70 kDa between sense-HNF1A-AS1 and antisense-HNF1A-AS1 (Figure 5A). Mass spectrometry confirmed the protein as IGF2BP2(67 kDa); thus, IGF2BP2 was selected for further study. The interaction between HNF1A-AS1 and IGF2BP2 was further confirmed through Western blot (Figure 5B). RIP (RNA immunoprecipitation) experiments also verified the direct interaction between HNF1A-AS1 and IGF2BP2 (Figure 5C). To investigate the binding site in HNF1A-AS1 in depth, we designed four deletion mutants according to the secondary structure of HNF1A-AS1 predicted from RNAfold. Our results revealed that #3(730–1140 nt) of the HNF1A-AS1 transcript interacted with IGF2BP2 much more strongly than other parts (Figure 5D). Next, we designed several IGF2BP2 mutants, mainly focusing on KH domains, to explore which domain of IGF2BP2 played the most important role between their interactions. The molecular weight of these mutants was detected through Western blot in the HEK293T cell. Further RIP assays demonstrated that the RRM domain did not interact with HNF1A-AS1, and the KH1-2 domain was much more indispensable than the KH3-4 domain for the interaction between HNF1A-AS1 and IGF2BP2 (Figure 5E). Interestingly, we found that HNF1A-AS1 failed to affect IGF2BP2 expression through RT-qPCR and Western blot, indicating that IGF2BP2 was not the target gene of HNF1A-AS1. On the other hand, HNF1A-AS1 decreased significantly when silencing IGF2BP2 (Figure 5F,G). Their relationship was further confirmed in FISH assays. HNF1A-AS1 did not affect the IGF2BP2 cellular localization, while a knockdown of IGF2BP2 weakened HNF1A-AS1 fluorescence intensity (Figure 5H). Additionally, IGF2BP2 decreased HNF1A-AS1 stability in HCT116 and LOVO cells (Figure 5I). We next explored the role of the HNF1A-AS1/IGF2BP2 axis in CRC and carried out rescue assays. Subsequently, IGF2BP2 knockdown abolished proliferation and migration in HCT116 and LOVO cells elicited by over-expressing HNF1A-AS1, suggesting that IGF2BP2 mediated HNF1A-AS1-induced proliferation and migration in CRC cells (Figure S3A,B). IGF2BP2, as an m6A “reader” and conserved RNA binding protein (RBP), has been reported to stabilize a large number of target mRNAs. Therefore, we hypothesized that HNF1A-AS1 could cooperate with IGF2BP2 to stabilize CCND1 stability. According to the TCGA database, IGF2BP2 was higher expressed in CRC tumor tissues (Figure S3C). Then, we knocked down IGF2BP2 (Figure S3D) and found that the mRNA expression of CCND1 decreased based on RT-qPCR results (Figure S3E). Moreover, the over-expression of IGF2BP2 increased the downregulation of CCND1 induced by HNF1A-AS1 knockdown based on RT-qPCR and Western blot assays (Figure S3F). CCND1 mRNA could interact with IGF2BP2 as well in RIP assay results. The enrichment of CCND1 decreased when knocking down HNF1A-AS1, indicating that HNF1A-AS1 regulated CCND1 through combining with IGF2BP2 (Figure 5J). Then, we explored whether the HNF1A-AS1/IGF2BP2/CCND1 complex regulated CCND1 expression through stabilizing CCND1 mRNA stability. CCND1 mRNA stability decreased after silencing HNF1A-AS1 or IGF2BP2 (Figure 5K). IGF2BP2 knockdown attenuated the CCND1 mRNA stability mediated by over-expressing HNF1A-AS1 (Figure 5L). In conclusion, our result indicated that HNF1A-AS1 enhanced CCND1 mRNA stability by cooperating with IGF2BP2, ultimately promoting CCND1 expression.
m6A modification played critical roles in numerous biological processes, such as RNA stability, location, protein translation and so on. METTL3 and METTL14, the major ingredients of the “writer” complex, played an irreplaceable function in methylation dynamic progression; thus, we analyzed the expression of METTL3 and METTL14 in CRC from the TCGA dataset. METTL3 was shown to be much more highly expressed in CRC tumor tissues, while METTL14 was much more expressed in normal CRC tissues (Figure 6A). Meanwhile, METTL3 and METTL14 were both reported to regulate CRC progression; thus, we detected the expression of HNF1A-AS1 by silencing METTL3 or METTL14. HNF1A-AS1 was downregulated after silencing METTL3. However, there was no significant change in HNF1A-AS1 expression after knocking down METTL14 (Figure 6B). The m6A enrichment of HNF1A-AS1 was higher in HCT116 and LOVO cell lines than in the human normal colon epithelial cell (Figure 6C), showing that m6A methylation occurred in the HNF1A-AS1 transcript. Then, we knocked down METTL3 (Figure 6D), and the total m6A content of the two cell lines was decreased (Figure 6E). Meanwhile, METTL3 had a positive relation with HNF1A-AS1 based on the TCGA analysis (Figure 6F). Then, the MeRIP experiments were carried out, and the result revealed that the relative m6A methylation enrichment of HNF1A-AS1 was decreased after METTL3 knockdown (Figure 6G). There were five potential m6A modification sites in the HNF1A-AS1 sequence, two of which (position: 1469 and 1487) were assessed with high confidence predicted from the SRAMP website (Figure 6H). To explore the specific mechanism contributing to the m6A-mediated upregulation of HNF1A-AS1 in depth, we carried out the associated assays. The nucleus–cytoplasm fraction assay results suggested that the localization of HNF1A-AS1 in HCT116 and LOVO cell lines was not changed after knocking down METTL3 (Figure 6I). Then, we detected the influence of METTL3 knockdown on HNF1A-AS1 stability. The half-life of HNF1A-AS1 decreased significantly during 80 minutes after treatment with METTL3 shRNA (Figure 6J), indicating that METTL3 modulated HNF1A-AS1 expression by affecting HNF1A-AS1 stability. RIP analysis indicated that HNF1A-AS1 was enriched in the IGF2BP2 protein, and METTL3 knockdown decreased HNF1A-AS1 enrichment with IGF2BP2, suggesting that METTL3-induced m6A modification regulated the interaction of HNF1A-AS1 with IGF2BP2 (Figure 6K). To explore which binding sites played the main role in methylation, we designed five mutants based on the predicted binding sites (Figure 6L). Next, we performed the luciferase report assays. The results showed that the relative luciferase activity decreased obviously in WT after silencing METTL3, and the same change occurred in Mut1, Mut2 and Mut5. However, the luciferase activity of the control group decreased in Mut3 and Mut4 compared with WT, and luciferase activity had no significant change when we silenced METTL3, demonstrating that the most important binding sites were site3 and site4 (Figure 6M).
As a classical oncogene, CCND1 (cyclinD1) regulates the cell cycle to promote cancer progression and its role in colorectal cancer had been demonstrated in several studies. As a typical tumor suppressor, PDCD4 (programed cell death 4) promotes cell apoptosis and inhibits cell cycle through blocking the PI3K/AKT pathway, ultimately affecting the downstream genes, such as cyclinD1 and c-MYC. Thus, we investigated the influence of HNF1A-AS1 on the PI3K/AKT pathway. Western blot results suggested that silencing HNF1A-AS1 suppressed the activation of the PI3K/AKT pathway. CCND1 over-expression or PDCD4 knockdown rescued the inhibition mediated by HNF1A-AS1 knockdown (Figure S3G). The above results suggested that the influence of HNF1A-AS1 on the PI3K/AKT pathway was partly mediated by CCND1 and PDCD4. CCND1 acted as the downstream of PDCD4, indicating that PDCD4 could directly activate the PI3K/AKT pathway to regulate CCND1. Next, we analyzed our 52 CRC samples to further investigate the clinical relationship of the HNF1A-AS1–IGF2BP2–CCND1 axis in CRC progression. IHC and ISH assay results (Figure 7A) demonstrated that HNF1A-AS1-high patients were consistent, with high expression of METTL3, IGF2BP2, CCND1 and low expression of PDCD4, while HNF1A-AS1-low patients had the opposite outcomes (Figure 7B). Moreover, RT-qPCR analysis showed that HNF1A-AS1 had a positive correlation with METTL3, IGF2BP2, CCND1 and a negative relation with PDCD4 (Figure 7C and Figure S4A). METTL3 had a positive relation with IGF2BP2 and CCND1 (Figure 7D and Figure S4B). Meanwhile, IGF2BP2 was positively related with CCND1, and PDCD4 was negatively related with CCND1 both in our CRC samples and the TCGA database analysis (Figure S4C,D). Higher expression of IGF2BP2 or CCND1 was associated with unfavorable prognosis for CRC patients (Figure 7E,F). In a nutshell, METTL3-mediated m6A modification was attributed to the upregulation of HNF1A-AS1 in a IGF2BP2-dependent way, and HNF1A-AS1 modulated the cell cycle through multiple ways. Apart from suppressing PDCD4 or competitively sponging miR-93-5p, the HNF1A-AS1/IGF2BP2/CCND1 complex further stabilized CCND1 mRNA to promote cell cycle progression (Figure 7G).
Colorectal cancer (CRC) has become a serious challenge for human life, and its morbidity and mortality in China have been on the rise in recent years. Currently, chemotherapy combined with targeted treatment has become the main treatment for metastatic colorectal cancer. However, the median survival time for CRC patients has not been obviously extended. Therefore, exploring new biomarkers is urgently needed for the diagnosis and prognosis of CRC. Long non-coding RNAs, once defined as having no biological function in human life, have been studied extensively in cancers and regulated colorectal cancer progression. However, the exact mechanisms of long non-coding RNAs are still not very clear. In our research, by searching the TCGA database, we filtered the differentially expressed lncRNA HNF1A-AS1 in colorectal cancer, which was closely related with overall survival. Vivo and vitro experiments were carried out to confirm its biological role in colorectal cancer. Then, we used bioinformatics analysis and screened out CCND1 and PDCD4 as the downstream targets. CCND1 (CyclinD1) is an important regulatory protein for cell cycle, which can modulate cell cycle transition from the G1 to the S phase. Several studies have demonstrated that CCND1 is positively associated with progression of various tumors [22,23]. In CRC, the over-expression rate of CCND1 reaches 72%, and the expression level of CyclinD1 is related with poor prognosis [24]. The most widely studied mechanism of long non-coding RNAs was competitively sponging miRNAs to affect downstream genes. In our research, CyclinD1 was recognized as the direct target of miR-93-5p. The role of miR-93-5p had been studied in multiple malignancies, such as NCSLC, pancreatic ductal adenocarcinoma, ovarian carcinoma and so on [25,26,27,28,29]. It had been reported that miR-93-5p could downregulate FOXA1 and upregulate TGFB3 to confer radioresistance in CRC. It was also reported that miR-93-5p suppressed CRC progression via targeting PDL-1, and long non-coding RNA CTBP1-AS2 could modulate the miR-93-5P/TGF-beta/SMAD2/3 pathway in colorectal cancer [30,31]. HNF1A-AS1 had a negative relation with miR-93-5p in our clinical tumor tissues, and there were potential binding sites between them from the predicted website. Our further luciferase activity results confirmed the direct combination between CCND1 and miR-93-5p. However, there may be many other miRNAs interacting with HNF1A-AS1 and CCND1 to play biological roles, which required us to further study. N6-methyladenosine (m6A) modification, which occurred in nearly 90% of human mRNAs and ncRNAs at the post-transcriptional level, played biological roles during tumor initiation or progression [32,33]. METTL3 had been reported to promote CRC development through modulating the m6A–GLUT1–mTORC1 axis and the m6A–CRB3–Hippo axis [34,35]. Wang et al. found that METTL14 mediated by TCF4 and HuR suppressed colorectal cancer progression by silencing ARRDC4 in an m6A manner [36]. Similarly, our study demonstrated the function of m6A-modified lncRNA HNF1A-AS1 in colorectal cancer. Our result showed that m6A modification mediated the upregulation of HNF1A-AS1. Bioinformatic prediction and the MeRIP assay demonstrated m6A modification in HNF1A-AS1. During the dynamic m6A modification progress, METTL3 acted as an m6A writer, and HNF1A-AS1 was recognized by IGF2BP2, a member of the IGF2BPs family, which functioned to stabilize RNA stability. The study by Lang et al. suggested that METTL3-modified lncRNA PCAT6 promoted bone metastasis in prostate cancer via forming the IGF2BP2–IFG1R complex to stabilize IGF1R mRNA [37]. The study by Wu et al. suggested that lncRNA LINRIS promoted glycolysis in CRC by stabilizing IGF2BP2 [38]. Li et al. revealed that METTL3 maintained SOX2 expression in an m6A-IGF2BP2-dependent manner to facilitate CRC progression [39]. Our research revealed that the half-time of HNF1A-AS1 was significantly decreased after silencing METTL3 in an m6A-dependent way, and HNF1A-AS1 regulated the CCND1 mRNA stability through binding IGF2BP2 in an m6A-dependent way. Apart from affecting lncRNA attenuation, m6A modification could influence the interaction of lncRNA and RNA binding protein (RBP). Whether the secondary structure of HNF1A-AS1 was influenced by m6A modification was still unclear, and we would further investigate the structure change between the HNF1A-AS1 and IGF2BP2. As a classical tumor suppressor in multiple cancers, a recent study has revealed a certain regulatory relationship between PDCD4 and CCND1. PDCD4 could hinder the PI3K/AKT pathway and the downstream factors CCND1 and c-MYC to suppress the cell cycle. PDCD4 can regulate the expression of miR-374a by inhibiting the PI3K/AKT/c-JUN signaling pathway, thereby affecting the expression of CCND1 [40]. Our results are consistent with such regulatory relationship. HNF1A-AS1 suppressed the expression of PDCD4 to activate the PI3K/AKT pathway and ultimately promoted CCND1 expression to accelerate cell proliferation. However, whether HNF1A-AS1 could regulate PDCD4 through m6A modification is unclear. HNF1A-AS1 could interact with YTHDFs and YTHDCs family proteins as well in our predicted results from the RPISeq website. At the same time, PDCD4 mRNA had several potential m6A-modified sites from the SRAMP website. The precise molecular mechanism of their interaction needs further exploration. Long non-coding RNAs have been widely studied in multiple malignancies and have affected tumor progression. However, the definite biological mechanisms behind its dysregulation are still being researched. HNF1A-AS1 was first discovered and observed to be upregulated in human EACs. Silencing HNF1A-AS1 blocked the cell cycle and suppressed cell proliferation, which was partly mediated by chromatin and nucleosome assembly [41]. It was also reported that HNF1A-AS1 affected NSCLC radiosensitivity via competitively sponging miR-92a-3p and ultimately regulating the JNK pathway [42]. HNF1A-AS1 was studied extensively ingastrointestinal carcinomas, such as hepatocellular carcinoma, gastric cancer, colorectal cancer and so on. In gastric cancer, HNF1A-AS1 induced by EGR1 was shown to promote the cell cycle as well. Apart from EGR1, HNF1α could regulate the transcription of HNF1A-AS1 as well. HNF1A-AS1 activated SHP-1 via phosphorylation, demonstrating that the HNF1α/HNF1A-AS1/SHP-1 axis may become a new treatment in hepatocellular carcinoma [43]. Fang et al. reported its function in colon cancer, and HNF1A-AS1 suppressed the miR-34a/SIRT1/p53 feedback loop to facilitate tumor metastasis [20]. These studies revealed a correlation between HNF1A-AS1 and CCND1. However, it has not been elucidated clearly how HNF1A-AS1 regulates CCND1 to modulate the cell cycle. In our study, our results showed that HNF1A-AS1 could interact with IGF2BP2 to stabilize CCND1 mRNA by m6A modification. On the other hand, it could regulate CCND1 through competitively sponging miR-93-5p. It also suppressed PDCD4 to activate the PI3K/AKT pathway and ultimately activate CCND1 to accelerate the cell cycle. However, the silver staining and mass spectrometry demonstrated that there still exist other RNA binding proteins (RBPs), which could interact with HNF1A-AS1 and mediate the HNF1A-AS1 function. We will carry out further studies to investigate the relationship between these RBPs and HNF1A-AS1. Our results illustrated multiple mechanisms of HNF1A-AS1 modulating the cell cycle, showing that HNF1A-AS1 had the potential to become a biomarker in colorectal cancer prognosis.
In a nutshell, our study revealed that HNF1A-AS1 regulates the cell cycle in several ways. m6A-modified HNF1A-AS1 interacted with IGF2BP2 to stabilize CCND1 mRNA. HNF1A-AS1 could also upregulate CCND1 by sponging miR-93-5p or suppressing PDCD4 to promote cell cycle progression. Our study indicated that HNF1A-AS1 has the potential in CRC prognosis and could serve as a biomarker in colorectal cancer prognosis. | true | true | true |
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PMC9562673 | Yuan Xiang,Lingyun Feng,Hui Liu,Yuhuan Liu,Jiapeng Li,Li Su,Xinghua Liao | SIPA1 Regulates LINC01615 to Promote Metastasis in Triple-Negative Breast Cancer | 01-10-2022 | SIPA1,LINC01615,MMP9,breast cancer | Simple Summary Breast cancer is a malignant tumor that often endangers women. After undergoing surgery and supplementary chemotherapy, however, tumor recurrence has not been well researched. The primary cause is high metastatic rates. Hence, bioinformatic and functional analyses were performed to indicate the effect of LINC01615 on breast cancer. We revealed that LINC01615 is regulated by the transcription factor SIPA1 in promoting breast cancer cell malignancy. Abstract Long non-coding RNAs (lncRNAs) are reported to play an important regulatory effect in carcinogenesis and malignancy. We found by high-throughput sequencing that LINC01615 is upregulated in breast cancer patients and reduces patients’ overall survival. In vivo and in vitro experiments, we clarified that overexpression of LINC01615 can promote breast cancer cell metastasis ability. The expression of LINC01615 is regulated by the transcriptional activator SIPA1, thereby promoting carcinogenesis in breast cancer cells. Our research clarified that LINC01615 can act as an oncogenic factor in promoting the development of breast cancer. | SIPA1 Regulates LINC01615 to Promote Metastasis in Triple-Negative Breast Cancer
Breast cancer is a malignant tumor that often endangers women. After undergoing surgery and supplementary chemotherapy, however, tumor recurrence has not been well researched. The primary cause is high metastatic rates. Hence, bioinformatic and functional analyses were performed to indicate the effect of LINC01615 on breast cancer. We revealed that LINC01615 is regulated by the transcription factor SIPA1 in promoting breast cancer cell malignancy.
Long non-coding RNAs (lncRNAs) are reported to play an important regulatory effect in carcinogenesis and malignancy. We found by high-throughput sequencing that LINC01615 is upregulated in breast cancer patients and reduces patients’ overall survival. In vivo and in vitro experiments, we clarified that overexpression of LINC01615 can promote breast cancer cell metastasis ability. The expression of LINC01615 is regulated by the transcriptional activator SIPA1, thereby promoting carcinogenesis in breast cancer cells. Our research clarified that LINC01615 can act as an oncogenic factor in promoting the development of breast cancer.
Breast cancer is the commonest tumor type and the main cause of death in female cancer patients in female cancer patients worldwide [1,2], which has overtaken lung cancer for the first time, reported with 2.26 million cases in 2020 as the most common cancer worldwide (with 2.2 million cases of lung cancer) [3,4,5]. According to statistics, the cases of breast cancer in Europe, Asia, South America, and Africa are increasing year by year [1]. As a malignant tumor, breast cancer has been increasingly threatening women’s health in China in recent years. According to the statistics from the National Cancer Center of China, approximately 278,900 new breast cancer incidences in Chinese women in 2014 led to 16.51% of the incidence of female malignant tumors, which became the most common malignant tumors in females [6,7]. Although there have been significant advances in breast cancer therapy with the advancement of modern medicine, it remains deviation in diagnosis and failure in treatment, making it particularly important to explore the nosogenesis of breast cancer. LncRNA (long non-coding RNA) is one of the non-coding RNAs with more than 200 nucleotides and cannot encode peptides [8,9]. LncRNAs play important roles in organisms, including regulating oncogenes in translational, inactive in sex-chromosome and alternative splicing. LncRNAs perform these functions through a variety of different mechanisms, including acting as molecular scaffolders, “guiding” chromatin modifying enzymes such as HOTAIR and DLX6AS, acting as competing endogenous RNAs (ceRNAs), and acting as “sponges” to adsorb miRNAs or proteins [8,10]. They can also promote or inhibit a wide range of chromatin interactions (e.g., LUNAR1 and CCAT1) and even act through their own transcriptional behavior [11]. Other mechanisms are also being investigated, such as the coordination between lncrnas and nuclear structures, the formation of circular lncRNAs, as well as lncRNA-induced mRNA disorder. LncRNAs have become key regulators of cancer metastasis pathways and biomarkers of related diseases. Increasing founding indicated that dysregulated lncRNAs involve in cancer cell proliferation, cancer progression, and cancer metastasis [10,12]. In breast cancer, a variety of non-coding RNAs have been found to work as tumor suppressors or tumor-promoting effectors, such as XIST, HOTAIR, GAS5, MALAT1, etc. [13,14,15,16]. These studies indicate that the maladjusted lncRNAs caused clinicopathologic malignancy and poor prognosis in breast cancer patients. SIPA1 (signal-induced proliferation-associated 1) protein, a member of the RapGAP protein family, is a mitogen-induced GTPase containing 1042 amino acids [17]. SIPA1 protein is highly expressed in the spleen, bone marrow, thymus, and other lymphatic hematopoietic systems. Its first discovered function is as GTPase-activating protein (GAP) of RAS-related mediating protein Rap1. Catalyze the conversion of Rap1 from active form RAP1-GTP to inactivated form RAP1-GDP. SIPA1 protein showed specific GAP activity to RAS-related proteins (Rap1 and Rap2) [18,19,20] to inactivate the Rap protein from GTP binding to GDP binding and thus regulate cell proliferation and migration and other biological processes [21]. In mice, SIPA1 protein is mainly localized to the nucleus, and its highest expression is in the lymphatic hematopoietic system, such as the spleen, bone marrow, and thymus. Most studies focused on breast cancer with SIPA1 due to its migration and invasion promotion. Meanwhile, SIPA1 expresses the nuclear region, which can also be a predictor of lymph node metastatic status [22,23]. Previous studies confirmed that upregulated SIPA1 in breast cancer cell lines, SIPA1 activates the promoter activity of ITGB1 through transcription, which improves the adhesion ability of breast cancer cells, thereby improving the malignancy of breast cancer cells [23]. Further cell function experiments proved that knockdown of SIPA1 expression could reduce the adhesion, migration, and invasion of breast cancer cells. SIPA1 knocked down in breast cancer cells significantly reduced FAK and Akt phosphorylation and inhibited MMP9 extracellular secretion through the integrin-mediated FAK/AKT-MMP9 signaling pathway. Therefore, the mechanism causing breast cancer cell adhesion, migration, and invasion can be explained by SIPA1, which may be achieved by regulating the ITGB1/FAK/Akt-MMP9 signaling pathway. Current research has also found that SIPA1 protein can prove breast cancer cell stemness by targeting the CD44 gene, and enhance aerobic glycolysis of cancer cells by targeting the EPAS1 gene to promote cancer cell metastasis [21,24]. However, other ways of regulating the metastasis of breast cancer cells by SIPA1 remain to be explored [21,25]. In this study, we found a significant correlation between SIPA1-regulated lncRNA and tumor metastasis. The key SIPA1-regulated lncRNA molecule LINC01615 was screeded out from lncRNA sequencing data mining. Decreasing the expression of LINC01615 was used to decrease the migration and invasion in breast cancer cells. The results reveal a new mechanism that SIPA1 regulates breast cancer cell EMT and then promotes metastasis by up-regulating the expression of LINC01615, which provides a new way to clarify the process of metastasis in cancer.
Human breast cancer cell lines BT549 and MDA-MB-231 were purchased from the Cell Bank of the Chinese Academy of Medical Science (Shanghai, China). The MDA-MB-231 cells were cultured with RPMI-1640 medium containing 10% FBS, and BT549 cells were cultured with DMEM medium containing 10% FBS. All cells were cultured in a 5% CO2 atmosphere at 37 °C.
Animal experiments were approved by the ethics committee of Wuhan University of Science and Technology. Containing 5 × 106 cells, MDA-MB-231 in PBS were subcutaneously injected into 4-week-old female nude mice for 27. Then mice were euthanasia, and the in vivo tumor tissues were fixed with 4% paraformaldehyde at 4 °C for 48 h after excision and weighed. The tumor volume was measured by using a digital caliper and algorithm using the volume (mm3) = [width (mm)]2 × [length (mm)]/2. After fixation, tumor tissue slides were stained with hematoxylin and eosin (H&E) or used for immunohistochemistry.
Lentiviral particles were produced in HEK293T cells cotransfected with shSIPA1, shLINC01615, LV-LINC01615, or the corresponding empty vectors, and pMD2.G and psPAX2 plasmids to construct stabilized overexpression or knockdown cell lines. Then, 2 × 105 MDA-MB-231 or BT549 cells were infected with 1 × 106 lentivirus at 8 μg/mL puromycin.
Total RNA from cells and tissues was extracted with TRIzol reagent (Thermo Fisher Scientific, Waltham, MA, USA). Then, 1 μg RNA was reverse transcribed into cDNA using the HiScript III 1st Strand cDNA Synthesis Kit (Vazyme Biotech, Nanjing, China). Real-time quantitative PCR was conducted using Taq Pro Universal SYBR qPCR Master Mix (Vazyme Biotech, Nanjing, China) on a CFX96 Real-Time quantitative PCR Detection System (Bio-Rad Laboratories, Hercules, CA, USA). The primer sequences were as follows: LINC01615: 5′-GAAGACAGGGGATCCCGAAG-3′ and 5′-AATGAAAGTCCAGCAGGAGGG-3′; MIR100HG: 5′-CCCAGTGCAAGGACAAAGA-3′ and 5′-GCAGAGGAGGTGTCTTCAGG-3′; LINC00702: 5′-GCAGTGGCATGATCTCGGCT-3′ and 5′-GGCCGAGGCAGGTGGATAAC-3′; LINC02544: 5′-TCTCATTCGTGGCTGGATCA-3′ and 5′-ACGCTCTCGAAATCGTGTCC-3′; SERTAD4-AS1: 5′-CCTATTCCCTGCTTCTGCGA-3′ and 5′-AGCCAGAGGTCTGGTTTTTCA-3′; FENDRR: 5′-CCACATGGATGGTTGCCACTCTC-3′ and 5′-GCTGGTACTCGGCCTTCTAATTGG-3′; GAPDH: 5′-TGAACGGGAAGCTCACTGG -3′ and 5′-TCCACCACCCTGTTGCTGTA-3′.
The cells were inoculated in 6-well plates, and 12 h later, a 200 µL tip was used to gently scratch the cell surface, and then the scratches were washed with PBS. The scratches were photographed and analyzed under the microscope at 0, 12, and 24 h, respectively.
Briefly, 5 × 104 cells were seeded in the upper chamber of Corning chambers, and the lower chamber was placed in a medium containing 10% FBS. After 24 h, the cells in the upper chamber were gently wiped off with a cotton swab, and the cells in the lower chamber were fixed with paraformaldehyde for 20 min, then stained with 0.1% crystal violet, and finally photographed and analyzed under a microscope.
Using R language DESeq2 package in the filtered and then the lncRNA and mRNA expression level in the form of differential expression analysis, according to |log2FC| ≥ 2, q-value < 0.05 standard filtered set parameters.
For immunohistochemistry, the sections were incubated with the primary antibodies at 4 °C overnight and then with secondary antibodies at 25 °C for 1 h. The signals were visualized by a DAB kit and counterstained with hematoxylin.
The resulting raw data are called raw reads. The raw data are first filtered, and the high-quality data after filtering are called clean reads. High-quality data were then compared with the reference genome and transcriptome.
All experimental data were statistically analyzed and plotted using GraphPad Prism 8 software. The comparison between treatment and control groups was tested by unpaired Student’s t-test and Wilcox test, and the statistical results were the results of 3 or more independent replicates. For multiple comparisons, the one-way ANOVA plus two-sided Tukey test was applied. The two-way ANOVA was applied for the comparison of tumor volume data. All values are expressed as the mean ± SD unless otherwise indicated.
To investigate the SIPA1prognostic valuable in generalized cancer, gene expression data in breast cancer tissues and normal breast tissues were obtained from the TCGA database. The results showed that SIPA1 was significantly upregulated in breast cancer tissues. Indicating the occurrence and development of breast cancer could be blamed for overexpressed SIPA1 (Figure 1A). To further verify the correlation between SIPA1 and breast cancer metastasis, the gene expression data of breast cancer in situ tumor tissues (M0) and metastatic tumor tissues (M1) were obtained from the TCGA database, and their differential expression was analyzed. SIPA1 expression in metastatic tumor tissues was significantly upregulated than that in orthotopic tumor tissues, suggesting SIPA1 might be correlated with breast cancer metastasis (Figure 1B). To verify the biological function of SIPA1 in breast cancer cells, SIPA1 was knocked down in BT549 and MDA-MB-231 cells. The wound-healing and Transwell assay performed that the migration and invasion ability of cells was inhibited after SIPA1 knockdown (Figure 1C,D). These results suggest that SIPA1 may promote the occurrence and development of breast cancer by promoting the proliferation and migration of breast cancer cells.
Previous studies have shown that SIPA1 can promote metastasis by regulating adhesion, drug resistance, and stem ability of breast cancer cells. Other research showed that lncRNAs can regulate tumor cell metastasis, but the mechanism of whether SIPA1 can regulate lncRNA to promote metastasis of breast cancer cells remains unclear. To understand whether SIPA1 can promote breast cancer cell metastasis by regulating the lncRNA expression in breast cancer cells, we performed high-throughput sequencing on MDA-MB-231 cells and MDA-MB-231 cells with stable knockdown of SIPA1 (Figure S1). Through differential analysis of sequencing data, we found that 385 overexpressed lncRNAs and 468 were down-regulated (Figure 2A,B). The results of GO analysis, KEGG analysis, and MsigDB gene set alignment analysis showed that the biological function of differential lncRNAs might be related to cancer cell metastasis, and the comparison results with MsigDB marker genome suggested that differential lncRNAs might be related to cell EMT process (Figure 2C–E). Suggesting that SIPA1 may regulate breast cancer cell metastasis by regulating the expression of this lncRNA and then the EMT process. According to the expression level of differential lncRNAs and the correlation between differential lncRNAs and migration function, six candidate lncRNAs were screened out: MIR100HG, LINC00702, LINC01615, LINC02544, Sertad4-AS1, and FENDRR for subsequent experiments. The expression levels of candidate lncRNAs in breast cancer cell lines were verified by RT-qPCR, and only LINC01615 was found to meet expectations (Figure S2). The gene expression data and clinical information of breast cancer tissue samples were downloaded from TCGA database. The samples were divided into high and low expression group according to the differential lncRNA expression level, and the survival prognosis discrepancy of patients in these groups was analyzed for candidate lncRNA. Only LINC01615 was significantly correlated with the survival prognosis of breast cancer patients, and the prognosis of patients with upregulated LINC01615 expression was significantly lower than that with low LINC01615 expression (Figure S3). At the same time, the breast cancer gene expression samples were downloaded from the TCGA database and analyzed the candidate lncRNAs expression in tumor tissues (n = 1090) and normal adjacent tissues (n = 113). The results showed that the expression level of LINC01615 in tumor tissues was higher than that in normal breast tissues (Figure S4).
Furthermore, the LINC01615 knocked down in BT549 and MDA-MB-231 cells were made. Performing that, the cell migration and invasion were suppressed (Figure 3A,B). Meanwhile, stably knocked down LINC01615 MDA-MB-231 cells were constructed, and 5×106 cells were injected into 4-week-old female nude mice subcutaneously. Tumor volumes were measured weekly. After 28 days, all mice were euthanized for tumor dissection. The tumor samples were then photographed for measurement. The result showed that the tumorigenic ability of LINC01615 knockdown MDA-MB-231 cells was significantly reduced, as well as the tumor volume and weight (Figure 3C–F). This further indicates that LINC01615 can promote breast cancer cell migration and invasion.
To further verify that SIPA1 promotes the malignancy of breast cancer by inducing LINC01615 expression, we knocked down SIPA1 in BT549 and MDA-MB-231 cells and simultaneously overexpressed LINC01615. Indicating that overexpression of LINC01615 could counteract cell migration and invasion inhibited by SIPA1 knockdown (Figure 4A,B). We constructed MDA-MB-231 cells with simultaneous knockdown of SIPA1 and overexpression of LINC01615, and 5 × 106 cells were subcutaneously injected into 4-week-old female nude mice. After 28 days, all mice were euthanized for tumor dissection. We found that the decreased tumor volume caused by SIPA1 knockdown was offset by overexpression of LINC01615 (Figure 4C–F). These data fully proved that LINC01615 was subjected to SIPA1.
Through bioinformatics website analysis, it was found that LINC01615 could bind to MMP9 to stabilize its structure (Figure 5A). After overexpression of LNC01619, we found that the expression of MMP9 was also increased (Figure 5B).To further verify this hypothesis, we knocked down MMP9 after overexpression of LINC01615 in BT549 and MDA-MB-231 cells and found that migration and invasion induced by overexpression of LINC01615 were inhibited by knockdown MMP9 (Figure 5C,D). These results further confirm the molecular mechanism by which SIPA1 and LINC01615 promote migration and invasion.
In clinical practice, surgery is the first choice for breast cancer treatment, and endocrine therapy and chemoradiotherapy are selected according to individual differences. Clinically, there is an urgent need for new diagnostic methods and treatment programs so as to improve the early detection rate of breast cancer, reduce the treatment damage and side effects as much as possible, and achieve “precision treatment” has become the research direction of the majority of scholars [1,26]. In recent years, more and more scholars have focused on cancer-related molecular markers and gene targets, such as PAK1 and SOX8 [27,28]. At present, a variety of breast-cancer-related targets and targeted drugs have emerged, which provide a new means for the early diagnosis and treatment of breast cancer. Our study clarified that LINC01615 can be used as an oncogenic factor to promote the development of breast cancer, which will provide new ideas for the diagnosis and treatment of breast cancer. SIPA1 has been studied for nearly 30 years since it was first discovered in 1995. In almost all tumor types studied, the expression level of SIPA1 is correlated with lymph node metastasis, indicating that SIPA1 may be a molecule related to tumor development and patient prognosis [17,19]. Whether SIPA1 can be used as a reliable prognostic marker molecule or even a tumor therapeutic target still needs more laboratory and clinical studies. Studies have reported that the SIPA1 protein can accelerate the development of tumors by regulating the adhesion and infiltration of various tumor cells [29,30]. In this study, overexpressed SIPA1 was found in breast cancer tissues by pan-cancer analysis, and the migration assay and fluorescence quantitative PCR assay were used to verify that the SIPA1 protein could promote the EMT process of breast cancer cells to regulate metastasis. In order to determine whether SIPA1 can affect metastasis by regulating the EMT process through lncRNA, high-throughput RNA sequencing was performed on MDA-MB-231 and MDA-MB-231/SH-SIPA1 breast cancer cells with knockdown of SIPA1 expression level, and RNA expression data of the two cells were obtained. Subsequently, the data were filtered for quality control, and the differential expression analysis was performed to screen out the lncRNAs with significant differences, suggesting that SIPA1 could regulate the expression of lncRNAs. Subsequently, the effect of LINC01615 on the metastasis of triple-negative breast cancer cells was studied in MDA-MB-231 cells. Through scratch test and Transwell invasion test, it was proved that overexpression of LINC01615 expression could promote the migration and invasion ability of breast cancer cells. Then the effect of LINC01615 on regulating MMP9 was performed by western blot. The results indicated that the high expression of LINC01615 could promote the expression of MMP9 in breast cancer. LncRNAs are involved in various cellular functions and physiological processes in the nucleus and cytoplasm [31,32]. In the nucleus, lncRNAs can be involved in chromatin remodeling, chromatin modification, or pre-transcriptional gene expression regulation. In the cytoplasm, lncRNAs are mainly involved in post-transcriptional regulation and post-transcriptional modification [33,34]. At present, studies on the biological functions of lncRNA in breast cancer mainly focus on the influence of lncRNA on drug resistance, apoptosis, proliferation, and metastasis of breast cancer cells, etc. However, there are few reports on the expression of lncRNA and its biological role in triple-negative breast cancer [35,36]. This study explored the expression of lncRNA regulated by SIPA1 protein in triple-negative breast cancer cells and studied its biological function, which is of great significance for exploring the potential diagnostic and therapeutic value of lncRNA in breast cancer and promoting the treatment of tumor metastasis in triple-negative breast cancer patients. LINC01615 can potentially become a target molecule in the cancer metastasis therapy of breast cancer patients. Previous studies have shown that LINC01615 promotes tumorigenesis and progression in hepatocellular carcinoma, colon cancer, and clear cell renal cell carcinoma [37,38,39]. Moreover, the expression of LINC01615 is elevated in breast cancer patients, and overexpressed LINC01615 was associated with a poor prognosis. Further studies proved that LINC01615 could promote malignancy in breast cancer cells. Western blot results showed that LINC01615 could promote the expression of migration marker protein MMP9. Previous studies have shown that the interaction between SIPA1 and several molecules is known to regulate cell proliferation and migration and can provide potential models for studying the process of tumor metastasis, such as BRD4. More and more evidence shows that SIPA1 not only regulates tumor occurrence and development through intermolecular interaction but also regulates gene transcription in the nucleus. Known target genes include CD44 and ITGB1, and SIPA1 protein can regulate Smad2/3 molecular mRNA level [24,40]. This study shows that SIPA1 regulates one of the downstream pathways of breast cancer metastasis; namely, SIPA1 can regulate the expression of the corresponding lncRNA to regulate metastasis. However, how SIPA1 regulates the expression of lncRNA needs to be further studied. Subsequent studies can be carried out by analyzing the sequence of SIPA1 and lncRNA and proving whether SIPA1 can directly bind to lncRNA. On the other hand, the role of lncRNA in cell proliferation was only preliminarily studied in this study, and the role of lncRNA in cell proliferation and autophagy could be further studied in the future. Later, the downstream mechanism of lncRNA can be further studied. In summary, we confirmed the regulatory effect of SIPA1 on LINC01615 in breast cancer cell lines, which is ultimately reflected in cell migration and invasion and tumor metastasis in vivo. This study provides a better understanding of the molecular mechanisms behind breast cancer metastasis, which is a major cause of poor prognosis. Therefore, clarifying the specific biological mechanism of this phenomenon can better diagnose and treat the disease process.
In conclusion, our study found that the up-regulation of SIPA1 can promote the expression of LINC01615, and the up-regulation of LINC01615 can promote the expression of MMP9 to promote the migration and invasion of triple-negative breast cancer. Our experimental results will provide a new theoretical basis for the diagnosis and treatment of triple-negative breast cancer. | true | true | true |
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PMC9562694 | Hongzhou Cai,Haifei Xu,Hongcheng Lu,Weizhang Xu,Haofeng Liu,Xinwei Wang,Guoren Zhou,Xuejian Yang | LncRNA SNHG1 Facilitates Tumor Proliferation and Represses Apoptosis by Regulating PPARγ Ubiquitination in Bladder Cancer | 28-09-2022 | bladder cancer,SNHG1,microRNA-9-3p,MDM2,PPARγ | Simple Summary Our study elucidated that SNHG1 promotes MDM2 expression by binding to miR-9-3p to promote PPARγ ubiquitination and downregulate PPARγ expression and that SNHG1 plays an important role in bladder cancer and provides a potential therapeutic target for bladder cancer. Abstract Background: Long noncoding RNAs regulate various biological effects in the progression of cancers. We found that the expression of SNHG1 was significantly up-regulated in bladder cancer after analyzing data obtained from TCGA and GEO. However, the potential role of SNHG1 remains to be investigated in bladder cancer. It was validated that SNHG1 was overexpressed in bladder cancer tissues detected by qRT-PCR and FISH, which was also associated with poor clinical outcome. Additionally, SNHG1 was verified to facilitate tumor proliferation and repress apoptosis in vitro and in vivo. Results: SNHG1 could act as a competitive endogenous RNA and decrease the expression of murine double minute 2 (MDM2) by sponging microRNA-9-3p. Furthermore, MDM2 induced ubiquitination and degradation of PPARγ that contributed to the development of bladder cancer. Conclusions: the study elucidated that SNHG1 played an important role in bladder cancer and provided a potential therapeutic target for bladder cancer. | LncRNA SNHG1 Facilitates Tumor Proliferation and Represses Apoptosis by Regulating PPARγ Ubiquitination in Bladder Cancer
Our study elucidated that SNHG1 promotes MDM2 expression by binding to miR-9-3p to promote PPARγ ubiquitination and downregulate PPARγ expression and that SNHG1 plays an important role in bladder cancer and provides a potential therapeutic target for bladder cancer.
Background: Long noncoding RNAs regulate various biological effects in the progression of cancers. We found that the expression of SNHG1 was significantly up-regulated in bladder cancer after analyzing data obtained from TCGA and GEO. However, the potential role of SNHG1 remains to be investigated in bladder cancer. It was validated that SNHG1 was overexpressed in bladder cancer tissues detected by qRT-PCR and FISH, which was also associated with poor clinical outcome. Additionally, SNHG1 was verified to facilitate tumor proliferation and repress apoptosis in vitro and in vivo. Results: SNHG1 could act as a competitive endogenous RNA and decrease the expression of murine double minute 2 (MDM2) by sponging microRNA-9-3p. Furthermore, MDM2 induced ubiquitination and degradation of PPARγ that contributed to the development of bladder cancer. Conclusions: the study elucidated that SNHG1 played an important role in bladder cancer and provided a potential therapeutic target for bladder cancer.
Bladder cancer (BCa) ranks 12th in cancer incidence globally, with nearly 570,000 new cases each year and 13th in terms of deaths [1]. A strong male predominance is observed in bladder cancer, where three-fourths of cases occur in men [2]. The increased risk for bladder cancer correlates to factors including age, smoking, exposure to some industrial chemicals and hormonal differences, particularly androgens [3]. The treatment of bladder cancer depends on stage and grade to a great extent, which are also strongly associated with the prognosis of patients: the treatment of non-muscle invasive bladder cancer is usually through resection and immunotherapy with intravesical drugs such as Bacillus Calmette-Guerin, whilst more aggressive methods, such as radical cystectomy coupled with chemotherapy, are necessary for muscle invasive bladder cancer [4]. Unfortunately, little improvement has been achieved in the treatment for bladder cancer with a flat 5-year survival rate until recently [5]. Therefore, it is urgent to get a deeper understanding of molecular mechanisms underlying bladder cancer, thus exploring novel targets for bladder cancer treatment. It is well-established that long noncoding RNA small nucleolar RNA host gene 1 (lncRNA SNHG1) is involved in tumor stage, size and overall survival [6]. The oncogenic role of SNHG1 has been elucidated in various cancers. For instance, a prior study also reported the tumor-promoting potential of SNHG1 in pancreatic cancer with the results that SNHG1 silencing triggered repression of cell proliferative, metastatic, and invasive capacities by inactivating Notch-1 pathway [7]. In addition, Li et al. observed the suppressive effect of SNHG1 on prostate cancer development by promoting cell proliferation [8]. These findings indirectly support the possibility that SNHG1 might promote development of bladder cancer. Moreover, the starBase website used in our study predicted a binding relationship between SNHG1 and microRNA-9-3p (miR-9-3p). MiR-9-3p (previously known as miR-9) is widely known for its altered expression and function in multiple diseases, such as Huntington’s disease and cancers [9]. Interestingly, it was detected that ectopically expressed miR-9-3p possessed antitumor potential in bladder cancer by diminishing cell invasion, migration, and proliferation [10]. In our study, the binding sites between miR-9-3p and 3′ untranslated region (UTR) of murine double minute 2 (MDM2) were predicted by TargetScan. Overexpression of MDM2 could reportedly neutralize the depressive effect of miR-379-5p on bladder cancer cell proliferative, migratory and invasive capacities [11]. In the presence of EGFR, MDM2 can bind to peroxisome proliferator-activated receptor-gamma (PPARγ) and regulate the ubiquitination of PPARγ protein in colon cancer cells [12]. More importantly, it was elaborated in a prior study that an antagonist of PPARγ promoted cell cycle entry and decreased cell apoptosis in bladder cancer [13]. Taken these findings into account, we hypothesized that the SNHG1/miR-9-3p/MDM2/PPARγ axis correlated to the progression of bladder cancer. Therefore, the present study was implemented by focusing on the alteration in SNHG1 expression and function in bladder cancer. Moreover, we investigated the underlying mechanism of SNHG1 in the bladder cancer process via miR-9-3p/MDM2/PPARγ axis.
The experiments involving 67 human being samples were approved with ratification of the Ethics Committee of Nanjing Medical University (NO. 402, 2021) by conforming to the principles outlined in the Declaration of Helsinki. Ethical agreements were obtained from the donors or their families through written informed consent. Animal experiments (20 healthy nude mice aged 6–8 weeks) were ratified by the Animal Ethics Committee of Nanjing Medical University (No. 402, 2021) and concurred with the Guidelines for Animal Experiments of Peking University Health Science Center.
Sixty-seven patients diagnosed with bladder cancer undergoing radical cystectomy in Suqian First Hospital and Jiangsu Cancer Hospital from June 2016 to June 2017 were enrolled. Fresh bladder cancer tissues and corresponding adjacent normal tissues were preserved in liquid nitrogen immediately after resection. None of patients received preoperative radiotherapy, chemotherapy or immunotherapy. Follow-up information was obtained from outpatient clinics and regular telephone interviews.
Gene Expression Profiling Interactive Analysis (GEPIA) was adopted to analyze the BLCA dataset of The Cancer Genome Atlas (TCGA) database to obtain the genes with significant differences (p < 0.05), from which the genes with |logFC| > 0.5 were screened out. The Gene Expression Omnibus (GEO) database: https://www.ncbi.nlm.nih.gov/gds (accessed on 6 March 2021) was also analyzed by using “limma” package: http://www.bioconductor.org/packages/release/bioc/html/limma.html (accessed on 6 March 2021) of the R language with |logFC| > 0.5 and p < 0.05 as thresholds for differential analysis of bladder cancer microarray data GSE65635 and GSE40355. There were 12 samples in microarray data GSE65635, including 4 normal samples and 8 bladder cancer samples. There were 24 samples in microarray data GSE40355, including 8 normal samples and 16 bladder cancer samples. Human lncRNA names were obtained from GENCODE, followed by finding the intersection of significantly differential genes and lncRNA names. A Venn diagram was drawn to screen out the lncRNAs from intersection. LncRNA expression trends were collected in Ualcan, and the key lncRNA was determined by comparing the expression trends and combining with the existing literature. The possible downstream miR of the key lncRNA was discovered by starBase and their binding sites were obtained. The databases TargetScan (cumulative weighted context++ score < 0), DIANA TOOLS (miTG score > 0.6), microRNA (conservation > 0.65, energy < −14, Mirsvr_score < −0.65), and mirDIP (integrated score > 0.1) was applied to predict downstream genes of miR. Intersection of downstream genes with significantly differential genes was taken to find critical downstream genes. The relevant genes of the critical downstream gene were predicted in GeneMANIA: http://genemania.org/ (3 April 2021), followed by construction of a protein-protein interaction (PPI) network. The most core genes in PPI network (Table 1) were chosen as the key gene, and the binding sites of the miR to the gene were predicted by TargetScan.
SNHG1 cDNA fragments were amplified from the SNHG1 plasmid as templates by utilizing high fidelity DNA polymerase (Takara, Kyoto, Japan). Based on this template, fluorescein-labeled lncTCF7 FISH probe DNA was prepared with fluorescein-12-dUTP (Roche, Mannheim, Germany) and Klenow DNA polymerase (Vazyme, Nanjing, China) as per the manufacturer’s protocol. Then, 4-µm frozen sections were made from bladder cancer tissues and adjacent normal tissues. Subsequent to 5-min immersion in proteinase K (MCE, NJ, USA), the slides were washed twice in 2× saline sodium citrate (SSC) (Merck KGaA, Darmstadt, Germany). The FISH hybridization solution encompassing 30 ng/µL lncTCF7 FISH probe DNA (Beijing Dingguo Changsheng Biotechnology Co., Ltd., Beijing, China) was dripped onto the tissue sections before 16-h incubation at 37 °C. The slides were then washed in 0.4 × SSC/0.001% NP-40 (Merck KGaA, Darmstadt, Germany) for 5 min at 56 °C, followed by another 2-min washing in 0.4 × SSC/0.001% NP-40. After being dripped with 4′,6-Diamidino-2-Phenylindole (DAPI)-encompassing sealing agent, the slide was mounted and observed under a fluorescence microscope (Olympus, Tokyo, Japan).
Human normal urothelial cell line SV-HUC-1 (ATCC® CRL-9520), and bladder cancer cell lines [5637 (ATCC® HTB-9), T24 (ATCC® HTB-4™), SW780 (ATCC® CRL-2169™), and UM-UC-3 (ATCC® CRL-1749™) were obtained from American Type Culture Collection (ATCC, Manassas, VA, USA). The medium used for SV-HUC-1 was ATCC-formulated F-12K (Gibco, Thermo Fisher Scientific, Waltham, MD, USA) Medium (Catalog No. 30-2004) encompassing 10% fetal bovine serum (FBS, ATCC 30-2020). The medium used for 5637 was ATCC-formulated RPMI-1640 Medium (Gibco, Thermo Fisher Scientific, Waltham, MD, USA) (ATCC 30-2001) encompassing 10% FBS. The medium for T24 was ATCC-formulated McCoy’s 5A Medium Modified (Gibco, Thermo Fisher Scientific, Waltham, MD, USA) (Catalog No. 30-2007) with 10% FBS. The medium for SW780 was ATCC-formulated Leibovitz’s L-15 Medium (Gibco, Thermo Fisher Scientific, Waltham, MD, USA) (Catalog No. 30-2008) with 10% FBS. The medium for UM-UC-3 was ATCC-formulated Eagle’s Minimum Essential Medium (Gibco, Thermo Fisher Scientific, Waltham, MD, USA) (Catalog No. 30-2003) with 10% FBS. All media for cell lines encompassed 100 μg/mL streptomycin (MCE, N.J, USA) and 100 U/mL penicillin (MCE, NJ, USA). Cell culture was performed at 37 °C with 5% CO2. The media were positioned in humid air and replaced every 2–3 days according to the growth of cells. Cells were subcultured when 80–90% of the culture plate was covered by cells. Cells were utilized when they reached the logarithmic growth stage.
Lentiviruses expressing specific targeted knockdown SNHG1 [short hairpin-SNHG1 (sh-SNHG1)] and MDM2 (sh-MDM2) sequences and a scramble shRNA (sh-NC; control shRNA) were constructed by GenePharma (Shanghai, China) (Table 2). Lentiviruses overexpressing SNHG1 (oe-SNHG1), MDM2 (oe-MDM2), and PPARγ (oe-PPARγ), oe-NC, Inhibitor NC, and miR-9-3p inhibitor were obtained from GenePharma. Transfection was implemented using Lipofectamine 3000 (Invitrogen, Carlsbad, CA, USA).
Subsequent to isolation using RNeasy Mini Kit (Qiagen, Valencia, CA, USA), total RNA underwent reverse transcription to generate cDNA using First Strand cDNA Synthesis Kit (RR047A, Takara). For the detection of miR, the cDNA was obtained by reverse transcription using the miRNA First Strand cDNA Synthesis (Tailing Reaction) kit (B532451-0020, Sangon, Shanghai, China). qRT-PCR reactions were performed using SYBR® Premix Ex TaqTM II (Perfect Real Time) kit (DRR081, Takara) on real-time fluorescence quantitative PCR instrument (ABI 7500, Applied Biosystems, Foster City, CA, USA). The universal reverse primers for miR and the upstream primers for U6 internal reference were provided in the miRNA First Strand cDNA Synthesis (Tailing Reaction) kit, and the other primers were synthesized by Sangon (Table 3). After recording the Ct value of each well, the relative expression of mRNAs or miR was calculated using the 2−ΔΔCt method by normalizing to U6 expression.
The transfected T24 and 5367 cells (the expression of SNHG1 was clearly highest in T24 and compared with sw780 cells, 5637 cells had better culture characteristics in our experiment) were resuspended and seeded in 96-well plates at 2 × 103/100 µL/well. Cell viability was evaluated by CCK-8 (Dojindo Laboratories, Kumamoto, Japan) method at 0, 24, 48, 72 and 96 h after seeding. The 10 µL CCK-8 solution was supplemented in each test for 4-h incubation before absorbance measurement at 450 nm with a microplate reader.
The cells to be tested were seeded in 24-well plates with three duplicated wells set for cells in each group. EdU (Invitrogen) was supplemented to the medium to achieve a concentration of 10 µmol/L. The medium was discarded subsequent to 2-h culture. Cells received 15-min phosphate buffer saline (PBS) encompassing 4% paraformaldehyde fixing at ambient temperature before 20-min incubation at ambient temperature with PBS encompassing 0.5% Triton-100. Each well was supplemented with 100 µL dye solution before 30-min culture in the dark at ambient temperature. DAPI was added for 5-min nuclear staining. After sealing, 6–10 fields of view were randomly observed under a fluorescence microscope (FM-600, Shanghai Pudan Optical Instrument Co., Ltd., Shanghai, China), and the number of positive cells in each field was recorded.
Subsequent to 48-h transfection, the cell concentration was changed to 1 × 106 cells/mL. After cell fixing with 70% precooled ethanol solution at 4 °C, 100 μL cell suspension (no less than 1 × 106 cells/mL) was resuspended in 200 μL binding buffer. Subsequently, 15-min cells staining was implemented with 10 μL Annexin V-fluoresceinisothiocyanat and 5 μL propidium iodide at ambient temperature under dark conditions. After 300 μL of binding buffer was added, apoptosis (T24 and 5367 cell lines) was assessed on a flow cytometer at excitation wavelength of 488 nm (2 × 104 cells each time).
Subsequent to trypsin treatment, cells were lysed with enhanced radio-immunoprecipitation assay (RIPA) lysis encompassing protease inhibitors (BOSTER, Wuhan, Hubei, China), followed by estimation of protein concentration using Bicinchoninic Acid (BCA) Protein Quantification Kit (BOSTER). Proteins underwent separation by 10% sodium dodecyl sulfate polyacrylamide gel electropheresis (SDS-PAGE). Then, the separated proteins were electroblotted into a polyvinylidene fluoride (PVDF) membrane which was sealed by 5% bovine serum albumin to block nonspecific binding. Overnight cell incubation was conducted at 4 °C after supplementation with primary rabbit antibodies (Abcam, Cambridge, UK) to Cleaved caspase-3 (ab49822, 1:500), Bcl-2-Associated X (Bax, ab32503, 1:1000), B-cell lymphoma-2 (Bcl-2, ab196495, 1:500), MDM2 (ab226939, 1:3000), PPARγ (ab45036, 1:500), Ubiquitin (ab7780, 1:2000), and β-actin (ab8227, 1:500). Then, horseradish peroxidase-tagged goat anti-rabbit secondary antibodies (ab205719, 1:2000, Abcam) were supplemented for 1-h membrane incubation at 4 °C. After development in ECL working fluid (EMD Millipore Corporation, Billerica, MA, USA), the bands in Western blot images were quantified by Image J analysis software by normalizing to β-actin.
Cells were transfected with biotinylated wild type (WT) miR-9-3p and mutant type (MUT) miR-9-3p (50 nM each). After 48 h of transfection, 10-min cell incubation was implemented with specific cell lysis (Ambion, Austin, Texas, TX, USA). Then, 3-h lysate incubation was conducted with M-280 streptavidin magnetic beads (Sigma, St. Louis, MO, USA) pre-coated with RNase-free and yeast tRNA at 4 °C before two cell washes in cold lysis and qRT-PCR detection of SNHG1 expression.
The binding of miR-9-3p to MDM2 was detected by RIP kit (Millipore, Temecula, CA, USA). Briefly, 5-min cell lysing was implemented in an ice bath with equal volume of RIPA lysis (P0013B, Beyotime, Shanghai, China), and supernatant was removed subsequent to 10-min centrifugation at 14,000× g rpm and 4 °C. A portion of the cell extract was applied as input, and a portion was co-precipitated with antibody. RNA extraction was implemented by treating samples with proteinase K for subsequent qRT-PCR detection of MDM2. Antibodies used for RIP were as follows: rabbit anti-Argonaute 2 (AGO2) (1:100, ab32381, Abcam) was mixed at ambient temperature for 30 min, and rabbit anti-human Immunoglobulin G (IgG; 1:100, ab109489, Abcam) was applied as a normal control (NC).
The synthesized MDM2 3′ untranslated region (UTR) gene fragment MDM2-WT and the MDM2-MUT mutated at the binding site were constructed into a pMIR-reporter plasmid (Beijing Huayueyang Biotechnology, Beijing, China). Luciferase reporter plasmids were co-transfected with miR-9-3p into HEK293T cells (Shanghai Beinuo Biotechnology, Shanghai, China). Then 48 h subsequent to transfection, cells were lysed, and detected using a luciferase detection kit (K801-200; Biovision, Mountain View, CA, USA).
T24 cells were lysed in lysis buffer [mixture of 50 mM Tris-HCl (pH 7.4), 150 mM NaCl, 10% glycerol, 1 mM ethylene diamine tetraacetic acid, 0.5% NP-40, and protease inhibitor], and cell debris was cleared by centrifugation. After the concentration of lysis was measured by BCA, the same amount of protein was taken from oe-NC/OE-MDM2 group and replenished to the same volume with cell lysate. Afterwards, 1 μg anti-MDM2 (ab226939, 1:100, Abcam), PPARγ (ab45036, 1:100, Abcam) and 15 μL protein A/G beads (Santa Cruz Biotechnology, Santa Cruz, CA, USA) were added for 2-h incubation. Subsequent to three washes with cell lysis, beads were collected by centrifugation, added into an equal volume of reductive loading buffer, and boiled at 100 °C for 5 min. Subsequent to SDS-PAGE, samples were electroblotted to PVDF membranes (Millipore), and then analyzed by immunoblotting.
Healthy nude mice aged 6–8 weeks (Beijing Institute of Pharmacology, Chinese Academy of Medical Sciences, Beijing, China) were bred in a specific pathogen-free animal laboratory with 60–65% humidity at 22–25 °C. They were fed in separate cages under 12:12-h light-dark cycle with food and water available ad libitum. The experiment was started one week after acclimation, and the health status of nude mice was observed before the experiment. Approximately 2 × 106 5637 cells were suspended in 200 μL PBS, and then subcutaneously injected into the left or right hindlimbs of nude mice (antagomir used). At 28 days subsequent to injection, mice were euthanized, followed by measurement and weighing of tumors.
All measurement data were manifested as mean ± standard deviation and analyzed by SPSS 21.0 software (IBM, Armonk, NY, USA), with p < 0.05 as a level of statistical significance. If data conformed to normal distribution and homogeneity of variance, data within groups were compared by paired t test, while data between two groups were compared by unpaired t test. Comparisons among multiple groups were performed using one-way analysis of variance (ANOVA) or repeated measures ANOVA. Intra-group pairwise comparison was performed using a post-hoc test. Rank sum test was performed if data did not conform to normal distribution or homogeneity of variance. Kaplan–Meier was adopted to calculate patient survival curves, and log-rank was utilized to analyze patient survival differences.
The BLCA data of TCGA database were analyzed by GEPIA to obtain 6597 significantly differential genes (|logFC| > 0.5, p < 0.05) (Figure 1A). Then, R language was employed for difference analysis of microarray data GSE65635 and GSE40355 in GEO database to obtain 4283 and 8065 significantly differential genes, respectively (|logFC| > 0.5, p < 0.05). Then, 17,937 human lncRNA names were obtained from GENCODE, which were intersected with differential genes. It was found that only DIO3OS and SNHG1 were significantly differential lncRNAs in bladder cancer (Figure 1B). Analysis of TCGA database data by Ualcan revealed that DIO3OS was significantly underexpressed in bladder cancer (p = 1.949 × 10−5; Figure 1C), while SNHG1 was significantly overexpressed in bladder cancer (p = 3.889 × 10−11; Figure 1C). Moreover, the difference of SNHG1 was significantly higher than that of DIO3OS. There was literature indicating the upregulation of SNHG1 in thyroid cancer [14], non-small cell lung cancer (NSCLC) [15], colorectal cancer [16,17], but SNHG1 was not studied in bladder cancer. Further detection by qRT-PCR assay also found that SNHG1 was highly expressed in bladder cancer tissues (Figure 1D). RNA-FISH showed high SNHG1 expression in bladder cancer tissues compared with adjacent normal tissues as well (Figure 1E). It was also observed that patients with high expression of SNHG1 had worse prognosis (Figure 1F). Therefore, high SNHG1 expression was associated with poor prognosis of patients with bladder cancer.
To further examine the regulatory role of SNHG1 in bladder cancer, we selected one normal urothelial cell line SV-HUC-1 and four bladder cancer cell lines (5637, T24, SW780, and UM-UC-3). As shown in Figure 2A, SNHG1 expression was increased in cancer cells compared with SV-HUC-1 cells. Subsequent experiments were conducted on T24 cells with higher SNHG1 expression and 5637 cells with lower SNHG1 expression. After silencing SNHG1 in T24 cells (Figure 2B), the shRNA with the highest silencing efficiency was selected for subsequent experiments. CCK-8 and EdU assays showed clearly that the viability and proliferation of T24 cells were inhibited by treatment with sh-SNHG1 (Figure 2C,D). The apoptotic rate of T24 cells elevated significantly (Figure 2E), accompanied by prominent increase of Cleaved caspase-3 and Bax expression and remarkable decline of Bcl-2 expression (Figure 2F), after silencing SNHG1. This suggested that silencing SNHG1 could trigger the inhibition of cell proliferation and promotion of cell apoptosis in bladder cancer. Further experiments in 5637 cells manifested that overexpression of SNHG1 in these cells (Figure 3A), noteworthy enhanced viability (Figure 3B), and proliferation (Figure 3C), diminished apoptosis (Figure 3D), and reduced the expression of Cleaved caspase-3 and Bax but elevated Bcl-2 expression (Figure 3E). Collectively, SNHG1 upregulation promoted the proliferation of bladder cancer cells.
Furthermore, a subcutaneous tumorigenic model was established in nude mice to detect the tumorigenic ability of bladder cancer cells in vivo. qRT-PCR depicted that SNHG1 expression was appreciably decreased in mice treated with sh-SNHG1 (Figure 4A). In addition, the growth rate and weight of tumors were appreciably decreased after silencing SNHG1 (Figure 4B). FISH experiment illustrated that SNHG1-silenced mice had distinct decline of SNHG1 expression (Figure 4C). On the contrary, overexpression of SNHG1 (Figure 4D) contributed to the appreciable elevation of the growth rate and weight of tumors (Figure 4E) and SNHG1 expression in tumors (Figure 4F). In summary, SNHG1 overexpression promoted bladder cancer cell tumorigenesis in vivo.
Then, we explored the downstream miR of SNHG1 in bladder cancer. RNA-FISH (Figure 1E) showed that SNHG1 was localized in the cytoplasm, suggesting that SNHG1 may be involved in the process of bladder cancer by affecting miR. The starBase website predicted that SNHG1 could bind to miR-9-3p (Figure 5A). A previous study has reported that miR-9-3p expression is down-regulated in bladder cancer [10], but the potential regulatory mechanisms need further detecting. qRT-PCR revealed that miR-9-3p expression in bladder cancer tissues was significantly lower than that in their matched nontumor adjacent tissues (Figure 5B). The expression of miR-9-3p was negatively correlated to the expression of SNHG1 in bladder cancer tissues (Figure 5C). Meanwhile, it was verified by RNA pull-down that SNHG1 indeed bound to miR-9-3p (Figure 5D). In addition, silencing SNHG1 in T24 cells prominently increased miR-9-3p expression (Figure 5E), while overexpressing SNHG1 in 5637 cells severely declined miR-9-3p expression (Figure 5F). The effect of SNHG1 binding to miR-9-3p on bladder cancer cells was further examined. Silencing SNHG1 alone resulted in decrease of SNHG1 expression. Besides, silencing SNHG1 alone reduced cell proliferation, increased apoptotic rate, elevated Cleaved caspase-3 and Bax expression, and caused a decline in Bcl-2 expression in T24 cells; this contrasted with treatment with miR-9-3p inhibitor alone. However, co-treatment with sh-SNHG1 and miR-9-3p inhibitor reversed the effect of sh-SNHG1 or miR-9-3p inhibitor alone, when the miR-9-3p inhibitor was used in T24 cells. However, co-treatment with sh-SNHG1 and miR-9-3p inhibitor reversed the effect of sh-SNHG1 or miR-9-3p inhibitor alone in cck-8 assay (Figure 6A–E). Simultaneously, in vivo experiments showed that the tumorigenic ability of bladder cancer cells in vivo was diminished by treatment with sh-SNHG1 alone and elevated by treatment with miR-9-3p inhibitor alone, which was neutralized by co-treatment with sh-SNHG1 and miR-9-3p antagomir (Figure 6F,G). Conclusively, silencing SNHG1 bound to miR-9-3p can inhibit bladder cancer cell proliferation and tumorigenesis.
Subsequently, the downstream target genes of miR-9-3p were investigated. The 3615, 2399, 270 and 2387 downstream genes of miR-9-3p were respectively predicted in TargetScan, DIANATOOLS, microRNA and mirDIP, and then were intersected. The intersecting results were compared with the differential genes in bladder cancer obtained by GEPIA, which screened out 21 significantly differential downstream genes of miR-9-3p (Figure 7A). By constructing the PPI network through GeneMANIA, we found that MDM2 had the highest core degree in the PPI network and was double the core degree of second-ranked genes (Figure 7B, Table 1). The binding site of miR-9-3p in MDM2 3′UTR was predicted using TargetScan (Figure 7C). Nevertheless, previous studies detected that MDM2 was highly expressed as a proto-oncogene in bladder cancer [11,18]. miR-9-3p may be involved in the progression of bladder cancer by inhibiting the expression of MDM2, which was further verified by experiments. Firstly, AGO2 pulled down MDM2 in RIP experiments (Figure 7D). Dual luciferase reporter assay manifested that miR-9-3p mimic markedly inhibited the luciferase activity of MDM2 WT but had no obvious effect on the luciferase activity of MDM2 MUT, suggesting that miR-9-3p bound to the 3′UTR of MDM2 (Figure 7E). After sh-SNHG1 and miR-9-3p inhibitor were co-transfected into T24 cells, MDM2 expression was evaluated by qRT-PCR and Western blot analysis. As displayed in Figure 7F, G, MDM2 expression was noticeably decreased after silencing SNHG1 alone, and observably increased after transfection with miR-9-3p inhibitor alone, which was normalized by co-treatment with sh-SNHG1 and miR-9-3p inhibitor. It was suggested that silencing of SNHG1 inhibited MDM2 expression through binding to miR-9-3p.
We observed that the expression of MDM2 was overexpressed in SNHG1-silenced T24 cells. From qRT-PCR results, the expression of SNHG1 and MDM2 was substantially diminished and miR-9-3p expression was significantly enhanced after silencing SNHG1 alone. MDM2 expression was appreciably increased after overexpressing MDM2 alone, and silencing SNHG1 negated the effect of overexpressing MDM2 (Figure 7H). As described in Figure 7I,J, CCK-8 and EdU assays exhibited that silencing SNHG1 appreciably reduced but overexpressing MDM2 increased cell proliferation, and overexpressing MDM2 could reverse the effect of silencing SNHG1 on cell proliferation (Figure 7I–J). To sum up, SNHG1 silencing suppressed the proliferation of bladder cancer cells by decreasing MDM2 expression through miR-9-3p. Similar results were confirmed in vivo. The expression of SNHG1, miR-9-3p, and MDM2 was detected by qRT-PCR. As presented in Figure, SNHG1 and MDM2 expression was strikingly declined and miR-9-3p expression was remarkably elevated after silencing SNHG1. MDM2 expression was prominently promoted after overexpressing MDM2, and overexpressing MDM2 could reverse the effect of silencing SNHG1 on MDM2 expression (Figure 7K). Moreover, after silencing SNHG1 alone, tumor growth was repressed, and after overexpressing MDM2 alone, tumor growth was promoted. Overexpression of MDM2 abrogated the effect of silencing SNHG1 on tumor growth (Figure 7L). In summary, silencing SNHG1 decreased the tumorigenesis of bladder cancer cells in vivo by decreasing MDM2 expression through miR-9-3p.
It has been documented that after addition of EGFR, MDM2 can bind to PPARγ and regulate the ubiquitination of PPARγ protein in colon cancer, and that MDM2 silencing can increase the level of PPARγ [12], which is further verified in bladder cancer. Firstly, through IP experiments in T24 cells, it was found that MDM2 combined with PPARγ. Meanwhile, the combination of PPARγ to MDM2 can also be proved (Figure 8A). Further, after screening out the MDM2 silencing sequence (Figure 8B, sh-MDM2-3 was selected for subsequent experiments), we found that PPARγ ubiquitination decreased and PPARγ expression increased after silencing MDM2 with the addition of EGFR (Figure 8C), which was opposite after overexpressing MDM2 (Figure 8D). MDM2 was overexpressed after silencing SNHG1 in T24 cells with the addition of EGFR. Western blot analysis showed that MDM2 expression was prominently decreased and PPARγ expression was strongly elevated after silencing SNHG1 alone, which was an opposite effect to overexpressing MDM2 alone. Silencing SNHG1 annulled the effect of overexpressing MDM2 on MDM2 and PPARγ expression (Figure 8E). The above results suggested that MDM2 reduced PPARγ expression by inducing PPARγ ubiquitination, while silencing of SNHG1 elevated PPARγ expression through downregulating MDM2.
As one of the most prevalent genitourinary cancers with high mortality on a global scale, bladder cancer currently can be treated by local or systemic immunotherapy, radiotherapy, chemotherapy, and endoscopic and open surgery [19]. However, the curative effect of such therapies is limited because of recurrence or distant spread [20]. Moreover, lncRNAs has emerged as a modulator in the complexity of bladder cancer [21]. Consequently, this research investigated the mechanism of SNHG1 in bladder cancer with the involvement of miR-9-3p. Notably, the present study provided evidence that SNHG1 promotes MDM2 expression by binding to miR-9-3p to promote PPARγ ubiquitination and downregulate PPARγ expression, thereby resulting in elevation of bladder cancer cell proliferation in vitro and tumorigenesis in vivo. Initially, data from our project and online database unraveled that SNHG1 was highly expressed in bladder cancer tissues and cells. Additionally, when SNHG1 was silenced in bladder cancer cells and mice, cell proliferative capacity was depressed but cell apoptosis was accelerated in vitro, and tumorigenesis was inhibited in vivo. Importantly, SNHG1 has emerged as a novel oncogenic lncRNA in various cancers, including esophageal, colorectal, prostate, gastric, liver, and lung cancers, inducing cell proliferative, metastatic, migratory and invasive capacities of cancer cells [6]. Consistently, Lu et al. observed that SNHG1 expression was strikingly high in NSCLC tissues and cells, and that SNHG1 silencing decreased tumor volumes in mice and reduced NSCLC cell proliferation, invasion and migration [22]. Meanwhile, data collected by Bai et al. found that SNHG1 expression was upregulated in colorectal cancer cells, and that ectopically expressed SNHG1 could enhance cell migratory, proliferative, and invasive capacities in vitro and led to tumor growth [23,24]. Another study uncovered that SNHG1 silencing contributed to decline of tumor growth of breast cancer in vivo [25]. These findings indirectly supported the tumor-promoting potential of SNHG1 in bladder cancer by enhancing cell proliferation and tumor growth and reducing apoptosis. It is well-recognized that lncRNAs may function as endogenous sponges to regulate miRNA function in diseases [26]. For example, prior research showed that SNHG1 could bind to miR-204 to inhibit it, thus promoting migratory, and invasive abilities but repressing apoptosis in esophageal squamous cell cancer [27]. These findings indirectly confirmed the binding relationship between SNHG1 and miR-9-3p in bladder cancer cells which was observed by our study. Further investigations of our study identified that miR-9-3p inhibition led to increase of cell proliferation and decrease of apoptosis in vitro and promotion of tumorigenesis in vivo and reversed the effect of SNHG1 silencing in bladder cancer. Similarly, the research conducted by Cai et al. clarified that in bladder cancer, miR-9-3p overexpression triggered repression of cell viability, migration, and invasion, induction of cell apoptosis in vitro, and inhibition in vivo tumor growth and metastasis [10]. Notably, another study illustrated that miR-9-3p exerted tumor-suppressive effect on hepatocellular carcinoma by depressing hepatocellular carcinoma cell proliferation [28], which was in line with our results. Hence, these results confirmed that SNHG1 overexpression promoted bladder cancer progression by binding to miR-9-3p. It is well-established that miRs inhibit expression of target genes at post-transcriptional level by targeting the 3′UTR of mRNA [29]. As previously reported, miR-9-3p targeted HBGF-5 to function as a tumor suppressor in hepatocellular carcinoma [30]. Moreover, in our study, TargetScan website predicted the binding sites between miR-9-3p and MDM2 3′UTR, and then the targeting relationship between miR-9-3p and MDM2 was verified by dual luciferase reporter gene assay. In the subsequent experiments, we found that MDM2 bound to PPARγ and downregulated PPARγ by inducing PPARγ ubiquitination, which was similar to the results observed by Xu et al. [12]. Our experiments show that Bcl-2 and Bax were also related to a certain extent, which is worth further in-depth study. Furthermore, our data elaborated that MDM2 ectopic expression neutralized the inhibitory effect of SNHG1 silencing on cell proliferation in vitro and tumor growth in vivo and the promoting effect of SNHG1 silencing on cell apoptosis in vitro in bladder cancer, suggesting the oncogenic role of MDM2 in bladder cancer. Similarly, a prior study uncovered that inhibition of MDM2 exerted tumor-suppressive effects on bladder cancer by decreasing cell invasive, proliferative, and migratory capacities [11]. Accordingly, PPARγ activation gave rise to inhibition of proliferation of 9 bladder cancer cell lines [31] All in all, the SNHG1/miR-9-3p/MDM2/PPARγ axis was involved in bladder cancer progression. Collectively, this study provides evidence that SNHG1 upregulation promoted cell proliferation but depressed cell apoptosis in bladder cancer via MDM2-inhibited PPARγ by binding to miR-9-3p (Figure 9). Thus, this finding offers a fresh molecular insight that might be utilized in new therapy development for bladder cancer. However, further studies are required on the mechanism of PPARγ in bladder cancer. | true | true | true |
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PMC9562834 | 35920132 | Gaëlle Robertson,Johan Burger,Manuela Campa | CRISPR /Cas‐based tools for the targeted control of plant viruses | 03-08-2022 | CRISPR/Cas,crop,genome editing,plant viruses | Abstract Plant viruses are known to infect most economically important crops and pose a major threat to global food security. Currently, few resistant host phenotypes have been delineated, and while chemicals are used for crop protection against insect pests and bacterial or fungal diseases, these are inefficient against viral diseases. Genetic engineering emerged as a way of modifying the plant genome by introducing functional genes in plants to improve crop productivity under adverse environmental conditions. Recently, new breeding technologies, and in particular the exciting CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR‐associated proteins) technology, was shown to be a powerful alternative to engineer resistance against plant viruses, thus has great potential for reducing crop losses and improving plant productivity to directly contribute to food security. Indeed, it could circumvent the “Genetic modification” issues because it allows for genome editing without the integration of foreign DNA or RNA into the genome of the host plant, and it is simpler and more versatile than other new breeding technologies. In this review, we describe the predominant features of the major CRISPR/Cas systems and outline strategies for the delivery of CRISPR/Cas reagents to plant cells. We also provide an overview of recent advances that have engineered CRISPR/Cas‐based resistance against DNA and RNA viruses in plants through the targeted manipulation of either the viral genome or susceptibility factors of the host plant genome. Finally, we provide insight into the limitations and challenges that CRISPR/Cas technology currently faces and discuss a few alternative applications of the technology in virus research. | CRISPR /Cas‐based tools for the targeted control of plant viruses
Plant viruses are known to infect most economically important crops and pose a major threat to global food security. Currently, few resistant host phenotypes have been delineated, and while chemicals are used for crop protection against insect pests and bacterial or fungal diseases, these are inefficient against viral diseases. Genetic engineering emerged as a way of modifying the plant genome by introducing functional genes in plants to improve crop productivity under adverse environmental conditions. Recently, new breeding technologies, and in particular the exciting CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR‐associated proteins) technology, was shown to be a powerful alternative to engineer resistance against plant viruses, thus has great potential for reducing crop losses and improving plant productivity to directly contribute to food security. Indeed, it could circumvent the “Genetic modification” issues because it allows for genome editing without the integration of foreign DNA or RNA into the genome of the host plant, and it is simpler and more versatile than other new breeding technologies. In this review, we describe the predominant features of the major CRISPR/Cas systems and outline strategies for the delivery of CRISPR/Cas reagents to plant cells. We also provide an overview of recent advances that have engineered CRISPR/Cas‐based resistance against DNA and RNA viruses in plants through the targeted manipulation of either the viral genome or susceptibility factors of the host plant genome. Finally, we provide insight into the limitations and challenges that CRISPR/Cas technology currently faces and discuss a few alternative applications of the technology in virus research.
Plant viruses are nucleoprotein complexes that rely mostly on host cells for their propagation. A large fraction of emerging plant diseases is caused by viruses, mostly because of their ability to adapt to changing environmental conditions and their effective dissemination facilitated by vector transmission (Anderson et al., 2004). Most economically important crops get infected with viruses, causing serious viral diseases that are responsible for significant decreases in both the yield and quality of harvests worldwide. It is estimated that 15% of global crop production is lost due to plant diseases, of which one‐third is accounted for by viruses (Boualem et al., 2016; Yadav & Chhibbar, 2018). Plant viruses therefore threaten global food security and agricultural productivity for the ever‐increasing world population. Plant viruses have small genomes (4–20 kb) composed of DNA or RNA that encode conserved essential proteins such as the coat protein, movement protein, and replication‐associated enzymes, as well as a number of additional less‐conserved proteins (Awasthi et al., 2016). Viral replication and transcription are dependent on the host's cellular machinery, making plant viruses obligate parasites. Plant viruses are transmitted by exposure to wounds, seeds, and pollen or by a diverse range of vectors including insects, nematodes, soil fungi or mites (Bragard et al., 2013; Lefeuvre et al., 2019). Unlike other plant pathogens, viruses cannot be controlled directly by chemical applications on infected material, making preventative sanitary measures the only approach to manage infections. Currently, control measures include planting virus‐free material, the eradication of infected material that was detected early enough, crop rotation, and pesticides to control transmission vectors (Fereres & Raccah, 2015; Tavazza et al., 2017). While agricultural practices often depend on pesticides, the extensive use of these has been shown to have many adverse effects on the environment and has given rise to insecticide resistance in virus‐vector populations (Bragard et al., 2013). The use of plant varieties that have natural genetic resistance factors constitutes the most efficient and sustainable approach to control viral infections. The first virus resistance gene was cloned and isolated from Nicotiana glutinosa. Named the N gene of tobacco, it confers a gene‐for‐gene resistance to the viral pathogen tobacco mosaic virus (TMV) in both tobacco and tomato transgenic plants (Whitham et al., 1994, 1996). Its cloning ultimately led to a better understanding of plant virus immune systems. By the introgression of resistance genes from wild to cultivated plants, a number of these plants were improved over the past decades and made commercially available. Unfortunately, for many plant–virus combinations the transfer of a resistance trait to a desired cultivar faces complex genetic constraints, such as linkage drag and high levels of heterozygosity (Kang et al., 2005). In addition, this approach requires a long generation time and is not cost‐effective for most breeding programmes. Viruses, like other pathogens, are able to evolve rapidly through recombination, mutations, and reassortment, making molecular advances in providing new tools for crop improvement and durable resistance vital. In the 1980s, when alternative transgenic approaches were being explored, it was discovered that the inhibition of gene expression could be engineered by the expression of antisense RNA in plant cells, a phenomenon named pathogen‐derived resistance (PDR) (Sanford & Johnston, 1985). As further studies were conducted, resistance was obtained through the expression of partial or noncoding virus sequences, leading to successful developments of virus‐resistant crops (Lomonossoff, 1995; Wilson, 1993), even though the mechanisms behind PDR were not completely understood (Baulcombe, 1996). The RNA‐mediated mechanism behind PDR was later shown to be an antivirus response from plants, a strategy termed RNA silencing (Tenllado, 2004). By means of regulating gene expression, the RNA silencing strategy was a breakthrough for antiviral breeding and has for more than a decade been used to engineer resistance in several crops against more than 60 different viruses (Zhao et al., 2019). More recently, genome‐editing technology has emerged and can be used for virus resistance following two broad strategies: the first approach targets the virus directly, as with RNA silencing; while the second approach targets endogenous host plant susceptibility (S) factors (van Schie & Takken, 2014). S factors are host factors that viruses use to replicate and complete their lifecycle in the plant. By modifying these S factors with genome editing, we can limit their availability and therefore mitigate the pathogenicity of viruses in plants (Dong & Ronald, 2019).
Since the emergence of genome‐editing technology, the achievements using this approach have revolutionized the fields of functional genomics and crop improvement. Essentially, genome‐editing technology is the use of sequence‐specific nucleases for recognizing specific DNA sequences and producing DNA double‐stranded breaks (DSBs) at targeted sites in chromosomal loci (Yin & Qiu, 2019). In almost all cell and organism types, a nuclease‐induced break is repaired via either nonhomologous end‐joining (NHEJ) or homology‐directed repair (HDR) (Sonoda et al., 2006). These two pathways differ in their efficiency and the mechanisms they require to repair the chromosome. If a repair template is absent, the error‐prone NHEJ operates, resulting in the introduction of a single or multiple insertion/deletion (indel) mutations after a DSB (Figure 1). These indels can cause a frameshift mutation as they disrupt either a translational reading frame or the binding sites of trans‐acting factors. Therefore, gene knockouts are created (Song et al., 2016). Alternatively, the high‐fidelity HDR method uses an intact homologous sequence as a donor template to enable sequence insertions or introduce point mutations by means of loci recombination (Belhaj et al., 2013). Previously, the leading genome‐editing tools available were zinc finger nucleases (ZFNs) and transcription activator‐like effector nucleases (TALENs) (Boch et al., 2009; Kim et al., 1996). Both of these nucleases are chimeric proteins created by fusing their respective DNA‐binding domains (DBD) with the DNA cleavage domain of the FokI restriction enzyme. Sequence specificity of the target DNA is conferred by the DBD, while the FokI cleavage domain produces the DSBs in the targeted site (Christian et al., 2010; Kim et al., 1996). ZFN‐ and TALENS‐based genome editing has been used with variable success in several plant species (Cai et al., 2009; Curtin et al., 2011; Shan et al., 2013; Zhang et al., 2012). Although the use of ZFNs and TALENs led to important advances, the customization of these two genome‐editing platforms requires protein engineering for each new target, making it a time‐consuming and resource‐intensive process (Gaj et al., 2013). During the last decade, a new genome‐editing platform naturally surpassed ZFNs and TALENs and their applications in plants.
Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR‐associated (Cas) proteins form the CRISPR/Cas system, which evolved in archaea and bacteria as an adaptive immune system against invading foreign nucleic acids originating from viral or plasmid pathogens (Barrangou et al., 2007; Barrangou & Marraffini, 2014; Brouns et al., 2008). While reported for the first time in 1987 by Ishino et al. (1987), it was only in 2012 that the potential of this system was realized by the fusion of the CRISPR‐RNA (crRNA) and trans‐acting CRISPR‐RNA (tracrRNA) to form guide‐RNA, an invention that would earn Jennifer Doudna and Emmanuelle Charpentier a Nobel prize in 2020 (Jinek et al., 2012). The mechanism of CRISPR/Cas‐mediated immunity (Figure S1) has been the topic of a multitude of research and review papers over the last decade (for recent reviews, see Nussenzweig & Marraffini (2020) and Nidhi et al. (2021)). Since the discovery of the CRISPR/Cas9 system in Streptococcus pyogenes, related systems in many different bacterial and archaeal species have been discovered. These have been classified in different classes, types and subtypes, based mainly on the functionality of the effector molecules (Koonin et al., 2017; Shmakov et al., 2015, 2017). The knowledge of all aspects of CRISPR/Cas systems is constantly expanding. In this review application of the better‐known members in the CRISPR toolbox are described, especially in the context of their use in virus interference.
The class 2 type II endonuclease Cas9 from Streptococcus pyogenes (SpCas9) was the first Cas effector to be adapted as a genome engineering tool. In the natural system, the pre‐crRNA is processed into mature crRNAs by a tracrRNA and the bacterial RNase III. An RNA complex comprising a crRNA and tracrRNA then directs a cluster of Cas9 nuclease proteins to cleave invading double‐stranded DNA (dsDNA), which essentially gives rise to a target interference (Van Der Oost et al., 2014). For most applications in genome editing, the crRNA and tracrRNA are fused into a single guide RNA (sgRNA) with a specific 20 nucleotide (nt) spacer sequence complementary to a DNA target (Figure 2a). A prerequisite for Cas9 cleavage is the presence of a short G‐rich protospacer adjacent motif (PAM), found immediately downstream of a DNA target sequence. The Cas9 protein comprises two nuclease domains, RuvC and HNH, each responsible for the cleavage of one strand of the dsDNA target, generating either a blunt DSB (Ran et al., 2013; Sander & Joung, 2014) or a staggered DSB, as more recently discovered (Molla & Yang, 2020). Several online bioinformatic software tools have been developed to predict the effectiveness of sgRNAs from whole‐genome information. A well‐designed sgRNA should be specific to the DNA target, meaning it should tolerate as few mismatches as possible, and none in the 8–12 nt seed region adjacent to the PAM, to reduce the possible off‐target activity of the attached Cas nuclease (Zhang et al., 2015). Both on‐target efficiency and off‐target activity are affected by the unique nucleotide sequence as well as possible secondary structure of a sgRNA (Uniyal et al., 2019). When applying the CRISPR/Cas9 system, it is still a concern that high frequencies of off‐target mutations may cause genomic instability (Wolt et al., 2016). The cleavage action of the Cas9 protein is a crucial step in targeted genome editing because this introduces a DSB in the genomic sequence of interest. Owing to its higher mutation efficiency and design simplicity, the CRISPR/Cas9 system dominates applications in plants compared to ZFNs and TALENs. Initially, CRISPR/Cas9‐mediated genome editing was typically used to target one or two gene loci at the same time. To target multiple genomic loci simultaneously, multiplex CRISPR/Cas9 systems were designed to allow the co‐expression of several sgRNAs (Mushtaq et al., 2018). This multiplex genome‐editing approach is valuable for functional gene knockouts in plants. In an alternative application called base editing, an inactivated CRISPR–Cas9 effector (Cas9 variants, dCas9 or Cas9 nickase) is fused to a cytosine or adenosine deaminase, and the CRISPR‐Cas9 system can be used to introduce point mutations in the target sequence without generating a DSB. The change of one base to another has the potential of generating new crop varieties, thereby enhancing crop improvement processes (Azameti & Dauda, 2021). A recent evolution of Cas9 applications is prime editing, which allows for the insertion of a desired sequence at a target site without making use of HDR. The technology relies on a novel CRISPR/Cas9 complex, which is composed of a protein consisting of a Cas9 nickase (H840A) fused to a reverse transcriptase and a prime editing guide RNA (pegRNA). The pegRNA consists of a reverse transcriptase template and a primer‐binding site at the 3′ end of the sgRNA. This primes the reverse transcription and incorporates the genetic information from the reverse transcriptase template into the genome (Azameti & Dauda, 2021). Prime editing, although very promising and versatile, still suffers from low efficiency in plants.
A second class 2 effector, Cas12a (formerly Cpf1), was later identified and categorized as a type V CRISPR/Cas. In contrast to Cas9, Cas12a contains an RuvC domain but not an HNH domain and generates a staggered DSB distal from a T‐rich PAM located upstream from the guide sequence (Makarova et al., 2015; Zetsche et al., 2015). The staggered DSB is situated close to the 3′‐end of the complementary target sequence, creating a 5′‐overhang. The production of DSBs with staggered ends by Cas12a may be advantageous for knock‐in applications, indeed being able to programme the exact sequence of a sticky end would allow researchers to design the DNA insert such that it integrates into the genome in the proper orientation and at precise positions by using complementary DNA ends through HDR (Zetsche et al., 2015). Furthermore, Cas12a requires a shorter crRNA than Cas9 and there is no evidence that a tracrRNA is required (Fonfara et al., 2016). Guided by a single crRNA and the presence of a T‐rich PAM sequence (5′‐TTN‐3′), the Cas12a effector can target either ssDNA or dsDNA. As shown in Figure 2b, the crRNA scaffold is located on the 5′‐end, as opposed to the 3′‐end in type II CRISPR/Cas systems. The Cas12a proteins also have RNase activity, used to process pre‐crRNAs into mature crRNAs (Jeon et al., 2018). This crRNA processing feature can be exploited to simplify multiplexed genome editing through the use of a single customized crRNA array. The potential of Cas12a as an alternative to the Cas9 endonuclease has been demonstrated in mammalian, plant, and microbial cells (Yan et al., 2017; Zaidi et al., 2017; Zetsche et al., 2015). Another interesting characteristic of Cas12a (and a few other type V Cas nucleases) is that specific cis‐cleavage of the target DNA induces collateral trans‐cleavage of nontarget ssDNA, a feature that has been exploited in the development of highly specific and sensitive nucleic acid detection systems. Recently, another Cas12‐variant was discovered in the genomes of some archaea (Harrington et al., 2018). This nuclease, named Cas14, is small (40–70 kDa) compared to Cas9 and Cas12, cleaves ssDNA, and also demonstrates indiscriminate trans‐cleaving of ssDNA.
The Cas9 effector derived from Streptococcus pyogenes (SpCas9) has been extensively utilized for dsDNA genome editing and has shown that it can be easily reprogrammed for efficient cleavage, making it a suitable candidate to be repurposed for ssRNA targeting and manipulation. This was shown by O'Connell et al., who demonstrated the SpCas9 binding and cleavage of ssRNA in vivo (O'Connell et al., 2014). In contrast to the native dependence of SpCas9 for a PAM sequence, when synthetic PAM sequences (PAMmers) were supplied exogenously, the SpCas9 was successfully redirected to target the ssRNA sequence complementary to the PAMmers (O'Connell et al., 2014). This indication of RNA targeting was further tested by including dsDNA with the ssRNA targets and PAMmers. Interestingly, the SpCas9 and its crRNA targeting counterpart exclusively targeted the ssRNA, avoiding the corresponding DNA in vitro. Thereafter denoted as an RNA targeting Cas9 (RCas9), this effector can be used as a programmable RNA binding platform. While RCas9 shows promise for further applications, a concern to consider is the costly synthesis of PAMmers, as well as the chemical modifications required to stabilize them in living cells (Nelles et al., 2016).
Previously shown to mediate DNA cleavage, a Cas9 effector encoded from Francisella novicida (FnCas9) was identified and applied for targeted RNA cleavage in vivo (Price et al., 2015; Sampson et al., 2013; Zhang, Zheng et al., 2018b). Discovered in 2013 (Sampson et al., 2013), the enzyme was shown to target bacterial mRNA and target gene expression. This novel feature of FnCas9 led to its use for the targeting of several eukaryotic viruses such as the human hepatitis C virus (HCV), and cucumber mosaic virus (CMV) and TMV in plants, with different degrees of successful interference (Price et al., 2015; Zhang, Zheng, et al., 2018b). In addition to the crRNA and tracrRNA, the CRISPR/FnCas9 system also requires a small CRISPR/Cas‐associated RNA (scaRNA) that hybridizes with tracrRNA, forming a duplex that promotes RNA targeting. Unlike the RCas9 system, the RNA targeting action of FnCas9 does not depend on a PAM. While some studies highlight the potential that the CRISPR/FnCas9 system holds for specific RNA targeting, there are still underlying mechanisms of FnCas9 that remain unknown. Due to its dual DNA and RNA targeting ability, like the RCas9 system, FnCas9 is less likely to be selected for RNA manipulation in the nucleus (Price et al., 2015).
Using data mining and bioinformatic approaches, three novel class 2 CRISPR systems besides the common Cas9 effector were discovered, namely C2c1, C2c2, and C2c3 (Shmakov et al., 2015). Similar to Cas12a, C2c1 and C2c3 contained RuvC‐like endonucleases and were therefore classified as type V‐B Cas12b and type V‐C Cas12c, respectively. Notably, C2c2 was shown to have unique properties compared to all other Cas proteins. Thereafter designated as Cas13, the putative effector was assigned to a novel type, class 2 type VI (Shmakov et al., 2017). Cas13a was the first class 2 effector found to solely function as a single RNA‐guided RNA‐targeting protein. Analysis of the Cas13a protein sequence resulted in the detection of two “higher eukaryotes and prokaryotes nucleotide‐binding” (HEPN) domains, which are exclusively associated with RNase activity (Anantharaman et al., 2013). The two structurally different HEPN domains, HEPN1 and HEPN2, are located on the outer surface and when activated lead to the cleavage of the target RNA outside of the binding region (Figure 2c). The exposed catalytic site of HEPN is available to all RNAs in a solution, thus explaining why unspecific cleavage of RNA was detected in bacterial cells (Liu et al., 2017). Further characterization of the RNA cleavage activity of Cas13a elucidated that Cas13a is guided by a crRNA containing a 28‐nt spacer sequence, an interaction maintained by the presence of a protospacer flanking sequence (PFS) of A, C, or U (Abudayyeh et al., 2016). As shown by the Cas12 system, Cas13a proteins can autonomously process their own pre‐crRNAs without the involvement of tracrRNA. This crRNA maturation activity is catalysed by a domain called Helical1 and can be harnessed for multiplexed processing (Abudayyeh et al., 2017; East‐Seletsky et al., 2016). The sensitivity of the Cas13a system to single and double mismatches was analysed and revealed that a central mismatch sensitive “seed” region is present in the crRNA, opposed to the 5′‐seed regions found in type I and II systems (Abudayyeh et al., 2016; Liu et al., 2017; O'Connell, 2019). Consistent with other type V Cas nucleases, Cas13 has nonspecific collateral trans‐cleaving activity, but in this case on ssRNA molecules. The Cas13 nuclease family was shown to contain three experimentally characterized subtypes, Cas13a, Cas13b, and Cas13d (Table 1).
In its native form, Cas13 can be used for targeted RNA cleavage such as down‐regulation of a specific transcript. The pioneer study that characterized the functionality of the first Cas13 family representative, Leptotrichia shahii Cas13a (LshCas13a), later confirmed that Cas13a solely cleaves ssRNA (Abudayyeh et al., 2016). It was shown that LshCas13a could provide interference against an MS2 lytic ssRNA phage in Escherichia coli. Interestingly, this study also identified that once activation by the target RNA was completed, nonspecific cleavage of RNAs other than the target RNA occurred. This suggests that LshCas13a elicits programmed cell death or dormancy in the natural system. Fortunately, this type of “collateral activity” was not detected in eukaryotic cells (Abudayyeh et al., 2017; Cox et al., 2017). Subsequently, a screening of various Cas13a proteins identified LwaCas13a from Leptotrichia wadei and the knockdown ability of LwaCas13a was demonstrated in mammalian cells with no evidence of collateral RNA cleavage (Abudayyeh et al., 2017). Abudayyeh et al. also verified the functionality of RNA knockdown by LwaCas13a in plants, with almost all guides exceeding 50% RNA knockdown in rice protoplasts, suggesting that a wide range of organisms can be edited using this system (Abudayyeh et al., 2017). Although the LshCas13a orthologue requires a biochemical PFS, analogous to the PAM for Cas9, LwaCas13a was shown to be exempt from this restriction in mammalian cells (Abudayyeh et al., 2017; Cox et al., 2017). Another recently categorized CRISPR/Cas13 system identified from computational sequence data mining is Cas13b (previously C2c6), assigned to class 2 and type VI‐B (Smargon et al., 2017). Although Cas13b also contains two HEPN domains and actively targets ssRNA, it has a novel protein sequence that differs significantly from Cas13a. In an E. coli essential gene screen, RNA cleavage by Cas13b was shown to be dependent on a double‐sided PFS, one on each of the 5′‐ and 3′‐ends of the protospacer target sequence (Smargon et al., 2017). Another interesting finding indicated that Cas13b interacts with two novel proteins, Csx27 and Csx28, of which Csx27 can repress RNA targeting and Csx28 can enhance RNA cleavage (Smargon et al., 2017). A study by Cox et al. evaluated a subset of Cas13 enzymes and found that the Cas13b orthologue from a Prevotella sp. P5‐125 (PspCas13b) exhibited a higher level of knockdown efficiency and specificity than the previously characterized LwaCas13a (Cox et al., 2017). Similar to LwaCas13a, however, PspCas13b showed no collateral RNase activity or PFS preference in mammalian cells (Cox et al., 2017). The most recent addition to the Cas13 subtypes is type VI‐D, which appears to be more distantly related on a primary sequence level to previous Cas13 effectors (Yan et al., 2018). Cas13d enzymes are about 20–30% smaller than all the previously reported subtypes Cas13a to Cas13c, and the orthologues from Eubacterium siraeum (Es) and Ruminococcus spp. (Rsp) possess associated WYL‐domain‐containing accessory proteins for enhanced binding and cleavage activity (Konermann et al., 2018; Yan et al., 2018; Zhang, Konermann, et al., 2018a). Similar to the Cas13 subtypes LwaCas13a and PspCas13b, Cas13d shares many commonalities, such as the lack of PFS requirements for target sequence selection and the innate ability to process pre‐crRNAs (Zhang, Ye, et al., 2019a). Notably, the high RNase activity of the Cas13d orthologue from Ruminococcus flavefaciens (CasRx) was shown to provide specificity and robust activity in both mammalian and plant cells when compared to other Cas13 proteins, such as LwaCas13a and PspCas13b (Konermann et al., 2018; Mahas et al., 2019). In addition, while a seed region was previously not reported for Cas13d, researchers found a critical seed region for optimal Cas13d knockdown efficiency between nucleotides 15 and 21 of the gRNA. By performing a set of pooled screens for CRISPR/Cas13d, they identified optimal gRNA design rules for Cas13d and developed a predictive model to select gRNAs with optimal efficiency (Guo et al., 2021; Wessels et al., 2020). With reports of favourable RNA targeting efficiency, this enzyme will enable a wide scope of RNA manipulations in plants. Already, a CRISPR/CasRx activity prediction tool for gRNA target design has been developed for mammalian cell culture applications (Wessels et al., 2020).
Plant viruses infect a wide range of plant species and are responsible for substantial losses in the yield and quality of staple crops (Nicaise, 2014; Oerke & Dehne, 2004). The first studies that looked at using the genome‐editing tool CRISPR/Cas for plant viruses were designed to target DNA viruses. However, the majority of plant viruses have RNA genomes and often plant DNA viruses have an intermediate RNA stage in their life cycle (Roossinck, 2003), making effectors with RNA specificity the systems of choice for this application (Figure 3).
It has been demonstrated that CRISPR/Cas9‐mediated DNA editing can be used as a successful defence mechanism against plant DNA viruses (Ali, Abulfaraj, Idris, et al., 2015a). The members of the plant virus family Geminiviridae are composed of ssDNA genomes but also contain replicative intermediates of dsDNA, making them suitable candidates for CRISPR/Cas9 targeting. Three previous studies reported the successful use of CRISPR/Cas9 to generate geminivirus resistance in the model plants Nicotiana benthamiana and Arabidopsis thaliana (Table 2; Ali, Abul‐faraj, Li, et al., 2015b; Baltes et al., 2015; Ji et al., 2015). In these, target regions within the virus genomes, such as the replicase, coat protein, or intergenic region, were selected to design sgRNAs. As expected, all of these studies showed that the transgenic plants that expressed the CRISPR/Cas9 components and were challenged with the respective virus had reduced virus loads and symptoms (Ali, Abul‐faraj, Li, et al., 2015b; Baltes et al., 2015; Ji et al., 2015). In another approach targeting a monopartite geminivirus, Yin et al. used transgenic N. benthamiana plants expressing Cas9 and sgRNAs that simultaneously targeted two different sequences in the genome of cotton leaf curl Multan virus (CLCuMuV). This led to the plants being completely resistant to CLCuMuV (Yin et al., 2019). The effectiveness of using a multiplexed gRNA approach to minimize mutant escape formation as much as possible was also confirmed by successful attenuation of chilli leaf curl virus (ChiLCV) (Roy et al., 2019). In addition to the Geminiviridae family, strong virus resistance was achieved against cauliflower mosaic virus (CaMV), a plant pararetrovirus with a dsDNA genome. Here, the expression of multiple sgRNAs, targeting the coat protein region, conferred successful resistance in transgenic Arabidopsis plants (Liu et al., 2018). There are some pararetroviruses, such as banana streak virus (BSV), that may integrate their DNA into the nuclear genome of the plant host, forming an endogenous virus (eBSV) that can also induce infections under stress conditions. By generating transgenic banana plants expressing Cas9 and sgRNAs targeting integrated regions of the eBSV genome, Tripathi et al. demonstrated the inactivation of the virus. When the transgenic plants were challenged under water stress conditions, they were resistant to reactivation of the virus when compared to the nontransgenic control plants (Tripathi et al., 2019). Recently, some studies have translated CRISPR/Cas‐mediated resistance against geminiviruses from model plants to crop plants. For example, Tashkandi et al. engineered the CRISPR/Cas9 machinery in tomato plants to target tomato yellow leaf curl virus (TYLCV) genomic sequences, resulting in robust interference of TYLCV in all tomato plants from the T2 to the homozygous T3 generation (Tashkandi et al., 2018). Later, another study showed effective resistance against wheat dwarf virus (WDV) in the monocot plant barley. The sgRNA‐Cas9 construct was developed to introduce mutations at multiple sites within conserved regions of two WDV strains (Kis et al., 2019). In contrast, Mehta et al. attempted to engineer resistance to an important geminivirus using CRISPR/Cas9 in cassava, but failed to induce effective resistance against African cassava mosaic virus (ACMV) in transgenic cassava plants expressing Cas9 and sgRNAs that targeted regions of the virus genome (Mehta et al., 2019). The probable reason for this is the fact that ACMV replication was more efficient than CRISPR‐cleavage, and that this potentially leads to the emergence of novel virus mutants that cannot be cleaved by the original CRISPR/Cas9 system again. In an interesting commentary, Rybicki suggested that the conclusion by these authors may be premature, because the study lacked a number of important controls, such as lower concentrations of the challenging virus and the use of multiple sgRNAs (Rybicki, 2019). However, the Mehta et al. study highlights the risks surrounding transgenic CRISPR/Cas9 plants, given that they may accelerate the evolution of novel virus genomes that can escape engineered resistance if they are not monitored correctly (Mehta et al., 2019).
The majority (more than 60%) of plant‐infecting viruses have RNA genomes and pose a serious threat to agricultural production (Lefkowitz et al., 2017). The discovery of CRISPR/Cas variants from various bacterial strains such as RCas9, FnCas9, and Cas13a/b/d have led to these being used to target RNA in vivo (Abudayyeh et al., 2017; O'Connell et al., 2014; Sampson et al., 2013). The first report of CRISPR/Cas9‐engineered plant immunity for an RNA virus was performed by a group that targeted CMV and TMV using FnCas9 and observed a reduction in virus accumulation in both transgenic tobacco and Arabidopsis plants (Table 2) (Zhang, Zheng, et al., 2018b). Applications of RNA virus interference by CRISPR/Cas13 in plants have been described in recent literature. Aman et al. first demonstrated the RNA targeting ability of CRISPR/Cas13 as a tool to combat viruses in plants (Aman, Ali et al., 2018a). The study used LshCas13a for engineered interference against a green fluorescent protein (GFP)‐expressing turnip mosaic virus (TuMV), a member of the Potyvirus genus, in N. benthamiana. Leaves of plants stably transformed with a codon‐optimized LshCas13a were infiltrated with mixed Agrobacterium cultures carrying TuMV‐GFP and crRNAs that target different regions of the virus genome. After infiltration, a c.50% reduction in GFP signal was detected in the leaves for two of the tested crRNAs targets. These initial results indicated the functional capacity for CRISPR/Cas13 in plants. The same group conducted a study with the same objectives in A. thaliana (Aman, Mahas et al., 2018b). RNA interference against TuMV‐GFP virus replication was successful in A. thaliana too. A preliminary study demonstrated that the LshCas13a system can target and degrade viral RNA genomes and confer resistance to an RNA virus in a monocot grain plant (Zhang, Zhao, et al., 2019b). Transgenic rice plants harbouring the CRISPR/Cas13a system were generated, with three crRNAs each targeting the RNA genomes of southern rice black‐streaked dwarf virus (SRBSDV) and rice stripe mosaic virus (RSMV). Inhibition of viral infection was confirmed in the transgenic rice plants, indicating that CRISPR/Cas13a can effectively target viral RNA in monocot plants too. Zhan et al. verified that the CRISPR/Cas13a system can be engineered to deliver broad‐spectrum resistance to transgenic potato plants against multiple potato virus Y (PVY) strains (Zhan et al., 2019). Confirmed by enzyme‐linked immunosorbent assays (ELISA) and reverse transcription quantitative polymerase chain reaction (RT‐qPCR), the transgenic potato plants expressing Cas13/sgRNA showed a significant reduction in PVY accumulation. In a recent study in grapevine, Jiao et al. compared FnCas9 and LshCas13a for efficacy against grapevine leafroll‐associated virus 3 (GLRaV‐3) and demonstrated that while both systems could confer resistance, the latter provided better interference efficiency against this virus (Jiao et al., 2022). In another study, Mahas et al. characterized multiple Cas13 proteins from three different Cas13 subtypes (a, b, and d) for their efficiency to target viral RNA in N. benthamiana (Mahas et al., 2019). To improve cellular localization, each Cas13 orthologue was fused to either a nuclear localization signal or a nuclear export signal. Transient and stable overexpression assays were conducted using a TMV‐RNA‐based overexpression (TRBO‐G) system expressing GFP, as well as a GFP‐expressing TuMV, as interference targets. The TRBO‐GFP construct served as a reporter system that is not capable of systemic movement, while the TuMV‐GFP virus was used to test whether the variants could limit systemic spread efficiently (Lindbo, 2007). Overall, while the variants LwaCas13a, PspCas13b, and CasRx all showed high interference activities (over c.50% virus reduction), CasRx mediated the most robust interference in both stable and transient assays (Mahas et al., 2019). In addition, it was shown that CasRx can target either one or two RNA viruses simultaneously, making CasRx a variant that is potentially amenable to multiplex targeting of RNA plant viruses. Likewise, Cao et al. recently expanded on the applicability of CasRx and was able to show a CRISPR/CasRx‐mediated RNA interference against an array of RNA viruses (Cao et al., 2021). For viral interference applications, these reports are encouraging for future multiplex strategies that can simultaneously either target multiple species of viruses within the same family to provide broad virus protection or target multiple regions of a single virus genome to evade the possibility of evolutionary resistance to the CRISPR/Cas system from occurring. A recent study showed that single polyvalent gRNAs (pgRNAs), designed for one spacer to be able to target multiple viral target sequences, in complex with the CasRx effector can effectively suppress virus spread and gene expression in planta, better than those with a monovalent gRNA counterpart (Bagchi et al., 2022). This observation of enhanced antiviral suppression is related to improvements reported by CRISPR antiviral treatments with multiple gRNAs, and future studies could now also use multiple pgRNAs to further increase the number of target sites. The impressive catalytic activity and high specificity of CasRx therefore enables diverse RNA manipulations in plants and it appears that it will continue to be favoured for viral RNA genome degradation. In a recent surprising finding, Sharma et al. reported a system that they termed “Cas13‐independent guide‐induced gene silencing (GIGS)”. Using a CRISPR/Cas13 system, they demonstrated effective gene silencing in three plant species when multiple gRNAs were expressed in the absence of Cas13 (Sharma et al., 2022).
As mentioned earlier, another approach to obtain virus resistance in plants is the targeting of the so‐called susceptibility (S) genes. Indeed, the success of viral infection depends on the deployment of host cell machinery, including host‐encoded virus‐compatible proteins or S factors, and whose modification may cause loss of susceptibility, passive resistance, or recessive resistance (Kan et al., 2022). A well‐known S factor is the eukaryotic translation initiation factor 4E (eIF4E). As shown in Table 3, there are a number of examples in literature where the gene(s) encoding eIF4E have been edited and subsequent resistance to viruses observed. For example, Chandrasekaran et al. (2016) used the CRISPR/Cas9 system to induce mutations in the elF4E gene of cucumber and reported the effective resistance of these cucumber plants against three different potyviruses, which have RNA genomes, namely zucchini yellow mosaic virus (ZYMV), cucumber vein yellowing virus (CVYV), and papaya ringspot mosaic virus‐W (PRSV‐W) (Chandrasekaran et al., 2016). After three generations of backcrossing, homozygous nontransgenic cucumber plants showed broad virus resistance. Similarly, by introducing site‐specific mutations in the A. thaliana eIF(iso)4E locus using CRISPR/Cas9, resistance to the potyvirus TuMV was conferred (Pyott et al., 2016). An investigation by Macovei et al. (2018) demonstrated novel sources of resistance against rice tungro spherical virus (RTSV) in rice (Oryza sativa) through biomimicking of eIF4G alleles (Macovei et al., 2018). T2 plants selected from this study were resistant to RSTV and tested negative for the presence of Cas9. More recently, the CRISPR/Cas9‐based targeting of two of the five cassava eIF4E isoforms (nCBP‐1 and nCBP‐2), found to interact with the viral genome‐linked protein of cassava brown streak virus (CBSV), significantly suppressed the symptoms of the disease in cassava plants (Gomez et al., 2019). In addition to this, these plants did not exhibit any observed mutations in potential off‐target sites. In barley, thanks to the rym4 and rym5 allelic variants of the HveIF4E gene, more than two‐thirds of current European winter barley cultivars are resistant to the bymoviruses barley yellow mosaic virus (BaYMV) and barley mild mosaic virus (BaMMV). However, several strains of BaYMV and BaMMV have already overcome rym4‐ and rym5‐mediated resistance. For this reason, Hoffie and colleagues saw the need to generate new resistance alleles using CRISPR/Cas9 (Hoffie et al., 2021). In this work, a homozygous mutation in the first exon generated a premature stop codon and presumably a nonfunctional protein, and the plants showed resistance to mechanical inoculation with BaMMV. Surprisingly, the plant yield was not affected in greenhouse conditions. The editing of eIF4E in tomato has been reported in four different publications in the last two years (Table 3), with all results demonstrating resistance to viruses. It is interesting to note that tomato contains three eIF4E genes, eIF4E1, eIF4E2, and eIF(iso)4E, and from these studies it is evident that the level of susceptibility to a virus is related to the specific eIF4E gene editing. For example, the editing of eIF4E1 reduced susceptibility to the pepper mottle virus (PepMoV) (Yoon et al., 2020), potato virus Y N strain (PVYN), and cucumber mosaic virus (CMV) (Atarashi et al., 2020), while the knockout of eIF4E2 produced full resistance to one isolate of pepper veinal mottle virus (PVMV) but only partial resistance to another isolate (Kuroiwa et al., 2022). A double knockout of eIF4E1 and eIF4E2, as well as the single mutants for these genes, was further analysed in a study by Kumar et al. (2022) and it was confirmed that eIF4E1 is responsible for resistance to PVY and that the editing of both genes affected plant growth (Kumar et al., 2022). The mutants were also challenged with CMV, eggplant mild leaf mottle virus (EMLMV), pepino mosaic virus (PepMV), and tomato brown rugose fruit virus (ToBRFV) to verify if a broad‐spectrum resistance was obtained, but the edited plants did not show reduced susceptibility to these viruses. Surprisingly, the authors noticed a higher accumulation of the coat proteins of CMV and PepMV in the mutants compared to wild‐type plants. These findings link to a previous study by Zafirov et al. (2021) in which it was found that the loss of function of eIF4E1 in A. thaliana led to higher susceptibility to turnip mosaic virus (TuMV). The authors suggest that knockout of eIF4E genes could expose the plant to the severe threat of potyviruses able to recruit alternative eIF4E copies and that a better strategy could be the use of CRISPR base‐editing technology to create functional alleles. A nice example of this type of approach was given by Bastet et al. (2019) in A. thaliana where CRISPR‐Cas9 cytidine deaminase was successfully used to introduce the N176K mutation in the eIF4E gene to confer transgene‐free resistance to clover yellow vein virus (ClYVV). Using base editing to create additional mutations in a resistance allele can lead to resistance pyramiding against several viruses, thus expanding the resistance spectrum and/or increasing resistance durability (Bastet et al., 2019). In addition to elF4E, other host S genes have been edited. For example, coilin encodes a major structural scaffolding protein necessary for Cajal body formation and mediates plant–virus interactions. By deploying CRISPR/Cas9‐based ribonucleoprotein (RNP) complexes to the apical meristematic tissue of potato plants using biolistic bombardment, the editing of at least a single allele of coilin in the tetraploid potato genome resulted in successful resistance against PVY (Makhotenko et al., 2019). Isoflavonoids are an essential group of secondary metabolites in leguminous plants and also play an important role in the regulation of plant–environment interactions. The multiplexed CRISPR/Cas9 targeting of GmF3H1, GmF3H2, and GmFNSII‐1 from the phenylpropanoid pathway resulted in both increased isoflavone content and enhanced resistance to soybean mosaic virus (SMV) in soybean plants (Zhang et al., 2020). A recent addition to the list of S genes targeted with genome editing is TOBAMOVIRUS MULTIPLICATION1 (TOM1). TOM1 is necessary for efficient multiplication of tobamoviruses in Arabidopsis (Ishikawa et al., 2022). The authors described how the simultaneous knockout of the four TOM1 homologues in tomato confers strong resistance to ToBRFV and that obvious defects in growth or fruit production were not observed. Importantly, it was noticed that when only three of the four TOM1 homologues were disrupted, ToBRFV coat protein accumulation was detectable but greatly reduced, but this led to the emergence of mutant viruses capable of more efficient multiplication. Ishikawa and colleagues hypothesized that the emergence and spread of resistance‐breaking mutants as observed in Sltom1acd triple mutant plants is caused by the low rate of viral accumulation in these plants, and that can be avoided with the complete knockout of all functional TOM1 homologues. In barley, the protein disulphide isomerase‐like 5–1 (HvPDIL5‐1) gene encodes a chaperone protein involved in the quality check system of correct protein folding. Indeed, the loss of HvPDIL5‐1 confers broad‐spectrum resistance to multiple strains of bymoviruses, including BaMMV and BaYMV. Kan et al. (2022) edited the wheat orthologues TaPDIL5‐1‐4A, TaPDIL5‐1‐4B, and TaPDIL5‐1‐4D, and demonstrated that triple editing of the three TaPDIL5‐1 homoeoalleles was sufficient to achieve reliable resistance against wheat yellow mosaic virus (WYMV) in hexaploid wheat and that it did not affect agronomic performance, thus providing another option for genome editing with CRISPR/Cas9 to achieve virus resistance in crops (Kan et al., 2022). To advance the practical applications of this CRISPR technology approach for plant virus resistance, there is an urgent demand for the identification of novel virus S genes from our understanding of plant–virus interactions, as is well illustrated in the reviews by Mäkinen (2020) and Hashimoto et al. (2016).
The effective delivery and subsequent expression of CRISPR/Cas components in plant cells are crucially important for successful editing in plants. The three primary methods for delivery are Agrobacterium‐mediated transformation, a physical means such as biolistic bombardment, or protoplast transfection. These all depend on plasmids, viruses, or RNPs to carry the required coding sequences or the functional proteins into cells (Kuluev et al., 2019). Agrobacterium‐mediated delivery of CRISPR/Cas components is the most common approach, but generates transgenic plants because desired sequences are integrated into the host genome. Likewise, biolistic bombardment of microprojectiles coated with a plasmid vector encoding the CRISPR components allows for the random integration of these sequences in the plant genome, potentially leading to multiple copies of the introduced genes (Sandhya et al., 2020). The negative perceptions and onerous regulatory processes associated with transgenic plants has led to the development of a number of effective transgene‐free (or DNA‐free) delivery methods. The most widely used is the transient expression of the CRISPR‐related transgenes, which can be achieved by agroinfiltration of plasmids containing these sequences (Nester, 2015). In one such application, Agrobacterium‐mediated transient expression of a base editor targeting specific genes allowed for the regeneration of T‐DNA‐free edited tomato and potato plants (Veillet et al., 2019). Moreover, DNA‐free genome‐editing approaches based on the biolistic delivery of an RNP complex have been developed. These RNPs comprise a Cas nuclease complexed with one or more sgRNA(s), and have shown significantly improved editing efficiency (Kuluev et al., 2019). Yet another approach is the direct transformation of protoplasts, using a transfecting agent like polyethylene glycol (PEG) or by electroporation. The transfection of the CRISPR/Cas components, either a plasmid or a pre‐assembled Cas/sgRNA RNP, into protoplasts and the subsequent regeneration of transgenic or nontransgenic plants, respectively, has allowed for the successful introduction of desired mutations in several plant species such as rice, tobacco, and lettuce (Woo et al., 2015; Xie & Yang, 2013). Protoplast transfection with RNPs is a relatively quick process, making it useful to validate the mutagenesis efficiency of a CRISPR/Cas system (Yue et al., 2020). However, protoplast isolation and whole‐plant regeneration from protoplasts remains a challenge for many plant species, especially crop plants (Sandhya et al., 2020). Harnessing plant viruses to act as delivery vectors is a promising approach to obtain CRISPR/Cas‐edited plants without the challenges that accompany transgene delivery. When viruses infect plants, they replicate and move systemically in their hosts, making them excellent vehicles for the delivery, high‐level expression, and distribution of CRISPR components in plants, leading to overall improved genome‐editing efficiency (Varanda et al., 2021). Recently, a number of viral vectors for the delivery of genome‐editing components to plant cells have been developed (Zaidi & Mansoor, 2017). Among these are the RNA viruses tobacco rattle virus (TRV) (Ali, Abul‐faraj, Li, et al., 2015b; Ghoshal et al., 2020), TMV (Cody et al., 2017), pea early‐browning virus (PEBV) (Ali et al., 2018), and beet necrotic yellow vein virus (BNYVV) (Jiang et al., 2019); all these have been shown to be efficient vectors in delivering CRISPR/Cas components to N. benthamiana, A. thaliana, and Beta macrocarpa plants. Virus‐mediated gRNA delivery provides a number of advantages compared to the conventional promoter‐driven expression of gRNAs, such as the rapid replication and systemic spread of the virus, which ensures effective amplification of the gRNA, while the small genome size allows for multiplexing and simple cloning strategies (Ali, Abul‐Faraj, Piatek, et al., 2015c). Single‐stranded DNA viruses, typically geminiviruses, have also been modified to carry heterologous coding sequences for increased protein expression in plants (Gil‐Humanes et al., 2017; Yin et al., 2015). Interestingly, a recent study found that a geminiviral replicon‐based expression vector was more efficient at LwaCas13a‐mediated RNA targeting than a regular binary vector in N. benthamiana (Yu et al., 2020). It is therefore clear that the method employed to deliver and express CRISPR/Cas components can significantly affect the efficiency of CRISPR/Cas‐based genome editing. Notably, the success of a delivery method in plants is dependent on the species, the tissue type, and its totipotency.
Despite the many technological advantages and an impressive track record in terms of applications in modern commercial agriculture, CRISPR/Cas technology still has a number of limitations and concerns, specifically for the development of disease‐resistant crop plants and especially for virus resistance. Mutation and recombination are the main driving forces in the evolution of plant DNA and RNA viruses, therefore the deliberate direct targeting and mutating of virus genomes may contribute to accelerated virus evolution, as demonstrated in a study by Mehta et al. that reported the failure of African cassava mosaic virus (ACMV) resistance in transgenic cassava plants expressing Cas9 and an sgRNA targeting a genome region of the virus (Mehta et al., 2019). The study suggested that between 33% and 48% of the edited ACMV genomes evolved a conserved single‐nucleotide mutation that protected the virus against CRISPR/Cas9 cleavage. In a subsequent analysis of this work, Rybicki commented on the novel aspects of this study, but also highlighted several shortcomings and limitations, among others the fact that only Cas9 was tested and also a single gRNA. He suggested that the conclusions of the Mehta study probably only hold true for single‐stranded DNA viruses and specifically for geminiviruses (Rybicki, 2019). Strategies to avoid the occurrence of new viruses, like the targeting of multiple viral genome regions, the deletion of larger genome stretches using CRISPR‐based nickases, or the use of alternative RNA‐targeting nucleases, should be investigated in both DNA and RNA viruses. Multiplexing of gRNAs has the further potential to establish resistance to multiple viruses in crops. Moreover, current strategies to introduce CRISPR/Cas‐based virus resistance by directly targeting the virus DNA or RNA genomes requires constitutive maintenance and expression of CRISPR components in plants. Such approaches not only pose the risk of subsequent unwanted mutations, but also potentially add a “GMO” label to the plant. Finally, the effectivity and durability of CRISPR/Cas‐based engineered virus resistance remains to be evaluated, especially under natural conditions in field trials.
The targeting of host factors like S genes may have a fitness cost because these are often involved in essential endogenous processes like plant growth and development. In the case of elF4E, the gene product is an essential eukaryotic translation initiation factor (also known as a cap‐binding protein), responsible for directing ribosomes to the 7‐methyl‐guanosine cap of mRNAs for subsequent translation. In this case, the potentially lethal scenario is mitigated by the presence of an eIF(iso)4E paralogue in the genomes of many crop plants. Exclusively mutating only one of the elF4E isoforms has been shown to be an efficient way to introduce virus resistance without incurring a fitness penalty to the host plant (Pyott et al., 2016). It is generally accepted that the recessive resistance acquired by knocking down a host susceptibility factor is more durable than dominant resistance genes because of lower selective pressures on the pathogen to evolve counterdefence strategies (de Ronde et al., 2014). The elF4E gene is by far the best characterized virus‐related S gene, and while several other host factors have been identified (Garcia‐Ruiz, 2018), an urgent need for the identification of novel virus‐related S genes remains. An alternative approach may be the identification of host susceptibility genes for insect vectors of plant viruses. CRISPR/Cas‐based inhibition of such S genes may be an effective strategy to prevent the spread and dissemination of economically important viruses.
One of the biggest concerns regarding genome editing by CRISPR/Cas is the occurrence of off‐target mutations (Hahn & Nekrasov, 2019). These are DNA edits at unintended and nonspecific genomic sites as a result of the tolerance of gRNA sequence mismatches (Tsai & Joung, 2016) or even modifications in a gRNA‐independent manner (Jin et al., 2019). Off‐target editing is also a critical factor for the CRISPR/Cas13 system, although it has been shown to produce significantly lower off‐target effects compared to the existing RNA‐targeting method, RNAi (Abudayyeh et al., 2017; Cox et al., 2017). It is suspected that minimal off‐target modifications to a host plant's transcriptome occur when the RNA cleavage activity of the CRISPR/Cas13 system is engineered for the specific targeting of RNA viruses or RNA intermediates of DNA viruses. At present, the extent to which CRISPR/Cas13‐based RNA editing can give rise to transcriptomic irregularities is not completely understood and further research into this is required. Efforts to improve the design rules for the generation of gRNAs with higher fidelity comprise both experimental and computational approaches. Experimental techniques include methods to detect Cas binding to its target, the detection of Cas‐induced DSBs, and the detection of repair products that result from Cas‐induced DSBs (Bao et al., 2021). Numerous bioinformatic tools have been developed to identify potential CRISPR/Cas off‐target sites (for a comprehensive review of these, see Bao et al., 2021). These authors concluded that in their experience, none of the bioinformatic tools was able to accurately predict low‐frequency off‐target editing and recommended the use of at least one bioinformatic tool in tandem with an experimental approach for the prediction of potential off‐target sites (Bao et al., 2021).
As stated, if the viral targeting activity of Cas nucleases is intended for heritable purposes, the permanent expression of the CRISPR/Cas components would be required, which can only be achieved through the generation of transgenic plants (Taliansky et al., 2021). Due to current regulation of genetically modified organisms (GMOs), the practical application of this technology may therefore be challenged by these regulatory constraints and thus be a limitation for the development of commercial crop varieties (Kalinina et al., 2020; Khatodia et al., 2017). However, by opting for RNA targeting over DNA targeting in plants, it is possible to confer a temporary or reversible modulation of gene expression, rather than knockout mutagenesis, which can often be lethal or have pleiotropic effects (Zhu et al., 2020). Without permanently editing the genome, CRISPR/Cas13 allows researchers to investigate gene function more systematically and could rather be harnessed as a “treatment” application for the transient inhibition of viruses in important crops. Therefore, the temporary nature of RNA editing overcomes major limitations relating to DNA targeting and its broad application in plant virology could potentially help overcome GMO regulatory hurdles. Despite this, the failure of genome‐edited food crops to gain acceptance by the general public, as well as to appease the regulators globally, is preventing this technology from reaping the fruits of success that it deserves. While the lay public in general are uninformed about the technology, a direct connotation with first‐generation genetic engineering persists, a situation that sadly has been “vindicated” by instances like the EU's decision to declare genome‐edited crops as GMOs. Fortunately, a few progressive‐thinking governments have relaxed regulation of genome‐edited crops significantly, with the result that the first genome‐edited crops, including mushroom, rice, maize, soybean, bristle grass, flax, wheat, and tomato, have been or are on their way to be commercialized (Menz et al., 2020). The early detection of plant viruses in combination with virus prevention strategies is of major economic importance in any crop production system.
Some features of the CRISPR/Cas systems have exciting potential for pathogen detection and the development of reliable diagnostic systems, none more than the so‐called “collateral activity” of the Cas12, ‐13 and ‐14 nucleases. As mentioned previously, after the recognition of its cognate target (dsDNA for Cas12, RNA for Cas13, ssDNA for Cas14a), the nuclease is activated, resulting in target cleavage and subsequent indiscriminate cleavage of nearby nucleic acids (ssRNA for Cas13, ssDNA for Cas12 and Cas14). Interestingly, this collateral cleavage is only seen in bacterial cells (Abudayyeh et al., 2016). This feature has since been combined with different preamplification technologies, like different versions of PCR, recombinase polymerase amplification (RPA), or loop‐mediated isothermal amplification (LAMP) to develop detection systems such as specific high‐sensitivity enzymatic reporter unlocking (SHERLOCK) (Gootenberg et al., 2017), DNA endonuclease‐targeted CRISPR trans reporter (DETECTR) (Chen et al., 2018), and the 1‐h low‐cost multipurpose highly efficient system (HOLMES) (Li et al., 2018). These detection systems can employ different read‐out formats, like colourimetric visual display, fluorescent detection, or lateral flow dipstick display, with limit‐of‐detection sensitivities reaching attomolar (DETECTR and HOLMES) to zeptomolar (SHERLOCK) levels (Kaminski et al., 2021), demonstrating that CRISPR‐based detection systems have evolved in a few years from experimental nucleic acid sensing tools to a dominant diagnostic technology for the fast, affordable, and ultrasensitive detection of pathogens, including RNA and DNA viruses in the clinical and agricultural sectors. Another exciting example of a very recent alternative application of CRISPR/Cas technology is that of “live” molecular imaging of macromolecules in cells. By fusing a catalytically inactive Cas9 (dCas9), complexed with gRNAs, to three different fluorescent proteins, Ma et al. were able to image multiple genomic loci in live human cells (Ma et al., 2016). Likewise, Abudayyeh et al. deactivated the two catalytic residues in the HEPN domains of Cas13 to create a dCas13, which, complexed to gRNAs, was fused to fluorescent proteins to image RNA transcripts in live cells (Abudayyeh et al., 2017). For applications in plant virology, this approach can allow the direct visualization of viral replication with high precision.
In less than a decade, CRISPR/Cas systems have demonstrated their immense potential as a genome‐editing technology to overcome the limitations of conventional breeding for the development of resistance to both biotic and abiotic stresses in crop plants. Moreover, the fact that Cas nucleases are guided by RNA rather than protein circumvents the major limitations of TALENs and ZFNs. Collectively, the CRISPR/Cas systems present much promise as simple, robust, precise, and scalable DNA and RNA targeting platforms and can be efficiently exploited to achieve virus resistance in plants. The ability for multiplex targeting at both the DNA and RNA level to create one‐off mutations in a transgene‐free manner is a huge added bonus. CRISPR/Cas13 systems can target specific endogenous RNAs, viral RNAs, and RNA intermediates of DNA viruses in plants and thus increase possibilities for their application in agriculture. It is our belief that CRISPR/Cas technology will play a major role in the creation of disease‐resistant food crops in the near future, thereby contributing significantly to securing the sustainable food supplies urgently needed to support the world population expansion towards the middle of this century.
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PMC9562873 | Danielle E. Frodyma,Thomas C. Troia,Chaitra Rao,Robert A. Svoboda,Jordan A. Berg,Dhananjay D. Shinde,Vinai C. Thomas,Robert E. Lewis,Kurt W. Fisher | PGC-1β and ERRα Promote Glutamine Metabolism and Colorectal Cancer Survival via Transcriptional Upregulation of PCK2 | 05-10-2022 | PGC-1β,colorectal cancer,ERRα,PCK2,metabolism,K-Ras,precision medicine | Simple Summary Peroxisome Proliferator-Activated Receptor Gamma, Coactivator 1 Beta (PGC-1β) and Estrogen-Related Receptor Alpha (ERRα) are proteins that are over-expressed to support the survival of colorectal cancer (CRC) cells, but the details of how they promote the growth of CRC has not been defined. In this article, we determine that PGC-1β and ERRα work together to increase the transcription of mitochondrial Phosphoenolpyruvate Carboxykinase 2 (PCK2). We show that PCK2 is required by CRC cells to optimally use amino acid L-glutamine to generate energy through the TCA cycle to support tumor cell survival and this is one mechanism used by PGC-1β and ERRα to promote the growth of CRC. Abstract Background: Previous studies have shown that Peroxisome Proliferator-Activated Receptor Gamma, Coactivator 1 Beta (PGC-1β) and Estrogen-Related Receptor Alpha (ERRα) are over-expressed in colorectal cancer and promote tumor survival. Methods: In this study, we use immunoprecipitation of epitope tagged endogenous PGC-1β and inducible PGC-1β mutants to show that amino acid motif LRELL on PGC-1β is responsible for the physical interaction with ERRα and promotes ERRα mRNA and protein expression. We use RNAsequencing to determine the genes regulated by both PGC-1β & ERRα and find that mitochondrial Phosphoenolpyruvate Carboxykinase 2 (PCK2) is the gene that decreased most significantly after depletion of both genes. Results: Depletion of PCK2 in colorectal cancer cells was sufficient to reduce anchorage-independent growth and inhibit glutamine utilization by the TCA cycle. Lastly, shRNA-mediated depletion of ERRα decreased anchorage-independent growth and glutamine metabolism, which could not be rescued by plasmid derived expression of PCK2. Discussion: These findings suggest that transcriptional control of PCK2 is one mechanism used by PGC-1β and ERRα to promote glutamine metabolism and colorectal cancer cell survival. | PGC-1β and ERRα Promote Glutamine Metabolism and Colorectal Cancer Survival via Transcriptional Upregulation of PCK2
Peroxisome Proliferator-Activated Receptor Gamma, Coactivator 1 Beta (PGC-1β) and Estrogen-Related Receptor Alpha (ERRα) are proteins that are over-expressed to support the survival of colorectal cancer (CRC) cells, but the details of how they promote the growth of CRC has not been defined. In this article, we determine that PGC-1β and ERRα work together to increase the transcription of mitochondrial Phosphoenolpyruvate Carboxykinase 2 (PCK2). We show that PCK2 is required by CRC cells to optimally use amino acid L-glutamine to generate energy through the TCA cycle to support tumor cell survival and this is one mechanism used by PGC-1β and ERRα to promote the growth of CRC.
Background: Previous studies have shown that Peroxisome Proliferator-Activated Receptor Gamma, Coactivator 1 Beta (PGC-1β) and Estrogen-Related Receptor Alpha (ERRα) are over-expressed in colorectal cancer and promote tumor survival. Methods: In this study, we use immunoprecipitation of epitope tagged endogenous PGC-1β and inducible PGC-1β mutants to show that amino acid motif LRELL on PGC-1β is responsible for the physical interaction with ERRα and promotes ERRα mRNA and protein expression. We use RNAsequencing to determine the genes regulated by both PGC-1β & ERRα and find that mitochondrial Phosphoenolpyruvate Carboxykinase 2 (PCK2) is the gene that decreased most significantly after depletion of both genes. Results: Depletion of PCK2 in colorectal cancer cells was sufficient to reduce anchorage-independent growth and inhibit glutamine utilization by the TCA cycle. Lastly, shRNA-mediated depletion of ERRα decreased anchorage-independent growth and glutamine metabolism, which could not be rescued by plasmid derived expression of PCK2. Discussion: These findings suggest that transcriptional control of PCK2 is one mechanism used by PGC-1β and ERRα to promote glutamine metabolism and colorectal cancer cell survival.
PGC-1 family proteins (PGC-1α, PGC-1β, and PPRC1) are transcriptional co-activators that bind a diverse array of transcription factors to promote the transcription of genes that regulate metabolism [1]. The combinations of PGC-1 family members and transcription factors are highly context dependent. In the context of colon cancer, intestinal specific genetic deletion of Peroxisome Proliferator-Activated Receptor Gamma, Coactivator 1 Beta (PGC-1β) in mice does not harm normal colon epithelium, and makes the mice resistant to genetic and chemically induced carcinogenesis [2]. We have previously shown that PGC-1βand the transcription factor, Estrogen-Related Receptor Alpha (ERRα), are upregulated in colorectal cancer (CRC) in response to K-Ras mutations and that depletion of either protein decreases growth in vitro and in vivo [3,4]. However, the nature of the association between PGC-1β and ERRα and the genes they regulate in CRC has not been elucidated. In this study, we first sought to confirm the interaction between PGC-1β and ERRα and subsequently identify the specific motif on PGC-1β required for the interaction with ERRα. Next, we identified the genes that are regulated by both PGC-1β and ERRα and found that mitochondrial Phosphoenolpyruvate Carboxykinase 2 (PCK2) was the gene most significantly decreased after depletion of either protein. Then, we explored the role of PCK2 in TCA cycle metabolism, glutamine utilization, and cell survival. Lastly, we determined if PCK2 can rescue the loss of ERRα on L-glutamine utilization and anchorage-independent growth.
Colorectal cancer cell lines HCT116, T84, SW620, HT-29, SW480, and HCT15 were purchased from American Type Culture Collection (ATCC) and cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) with 10% Fetal Bovine Serum (FBS), 2 mM L-glutamine and 1 mM sodium pyruvate at 37 °C with ambient oxygen (O2) and 5% CO2.
For virus production, a 15-cm plate of HEK-293T cells at a confluence of 75% was transfected with 3 μg of pMD2.G, 6 μg of pPAX-2, and 12 μg of pLKO-shRNA-puro using 63 μL of polyethylenimine (PEI—1 μg/μL; Polysciences—24765) mixed in 750 μL of 10 mM HEPES pH 7.4 and 150 mM NaCl in water. The viral supernatant was cleared at 2000 RPM for five minutes before being filtered through a 0.45 μM membrane filter then centrifuged at 12,000 RPM for two hours in a Sorval Lynx6000 with a F14 rotor. The resulting pellet was resuspended in four mL of media and 8 μL of polybrene (8 μg/μL) was added. 1 mL of the virus-polybrene solution was mixed with 1 mL of media containing 500,000 colorectal cancer cells and plated in one well of a six well plate. DNA sequences are listed in Supplementary Supplementary File S1.
The homology directed repair (HDR) template for epitope tagging of endogenous PGC-1β was prepared by Gibson assembly of 3 pieces: (1) A 5′ prime homology arm containing approximately 750 base pairs of the genomic DNA upstream of the PGC-1β stop codon, a tobacco etch virus (TEV) cleavage site, and a twin strep 2 epitope tag; (2) a central region containing a triple FLAG epitope and P2A-neomycin resistance cassette acquired via restriction endonuclease digestion of pFETCH_Donor (Addgene: 63934); and (3) a 3′ prime homology arm containing approximately 750 base pairs of the 3′ untranslated regions. Homology arms were ordered as gBlocks (Integrated DNA Technologies) and PCR-amplified. The three fragments were assembled with a Gibson Assembly Kit (New England Biolabs). Then, HCT116 cells were transfected with the HDR template and pCAG-SpCas9-GFP-U6-gRNA (Addgene: 79144) expressing a gRNA targeted near the stop codon of PGC-1β. After two days, cells were moved to larger dishes, neomycin-selected, and clones were screened by PCR for correct genomic insertion. DNA sequences are listed in Supplemental File S2.
Sample Preparation: Twenty 15-cm cell culture dishes of HCT116 or T84 cells expressing epitope tagged PGC-1β with 75% confluence were washed with PBS and each dish was lysed in 300 μL of RIPA lysis buffer (1% Triton X-100) with protease and phosphatase inhibitors (Halt Cocktail). Cells were sonicated and cleared in a centrifuge at 4 °C for 20 min at 13,000 RPM in Thermo-Scientific Sorvall Lynx 6000 Centrifuge with F14 fixed angle rotor. Protein concentration was determined by BCA and samples were normalized to the same volume and concentration with additional RIPA buffer. FLAG Immunoprecipitation: 200 μL of 50:50 magnetic FLAG bead slurry (Millipore-Simga, Burlington, MA, USA; M8823) were washed twice with Tris Buffer Saline (TBS) and added to each sample and rotated overnight at 4 °C. The beads were collected on a magnet and washed four times in 1 mL of TBS and eluted for three hours in 100 μL of 3X-FLAG peptide (100 ng/µL) in water. Strep2 Immunoprecipitation: 100 μL of a slurry of MagStrep “type3” XT beads (IBA biosciences, 2-4090-010) were washed in TBS and added to each sample and rotated overnight at 4°. The beads were collected on a magnet and washed four times in 1 mL of Tris Buffer Saline (TBS) and eluted for three hours in 100 μL of Buffer BXT (0.1 M Tris-Cl, 150 mM NaCl, 1 mM EDTA, 50 mM biotin, pH 8).
A full length human PGC-1β cDNA (Kind gift of Donald McDonnell, Duke) was PCR-amplified, digested, and ligated into AAVS1_Puro_Tet3G_3xFLAG_Twin_Strep (Addgene: 92099), and verified with bidirectional Sanger sequencing. Site directed mutagenesis was performed with the QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent; 210513). Plasmids were integrated via dual transfection with pCAG-SpCas9-GFP-U6-gRNA (Addgene: 79144) expressing a gRNA targeting the AAVS1 T2 site. DNA sequences for mutagenesis reactions are listed in Supplemental File S3.
The siRNA oligos (Dharmacon, Lafayette, CO, USA) targeting PGC-1β, ERRα, PCK2 or non-targeting controls were used for targeted depletion of the colorectal cancer cells. For pooled transfections, two validated, individual ON-TARGET PLUS siRNAs were used at a final RNAi concentration of 40 nM and were added to 5 µL of RNAiMAX (ThermoFisher, Waltham, MA, USA, 13778150) and 500 µL Hank Buffer Salt Solution without sodium bicarb. The mixture was added to 300,000 cells in 1.5–2 mL of media without antibiotics in a 6-well plate. All transfections were conducted for 72-h before analysis. RNA sequences for transfections are listed in Supplemental File S4.
RNA sequencing (RNA-seq) analysis was conducted by the UNMC Genomics Core. Cells were harvested using 0.5 mL TRIzol (ThermoFisher Scientific) and stored at −80 °C until RNA extraction was performed. RNA was extracted using RNeasy spin columns (Qiagen, Hilden, Germany) per manufacturer’s protocol. Final RNA was eluted with nuclease-free water and quantified using the NanoDrop 2000 (ThermoFisher Scientific). Three biological replicates of non-targeting control, PGC-1𝛽, or ERR𝛼 knockdown were completed using two separate siRNA oligos for each condition. Unstranded (poly A only) RNA sequencing libraries and 500 ng of total RNA for each of the samples were prepared per manufacturer’s suggested protocol using the TrueSeq mRNA Protocol Kit (Illumina, San Diego, CA, USA). Purified libraries were pooled at a 0.9 pM concentration and sequenced on an Illumina NextSeq550 instrument and 75 bp paired end sequencing was performed. Libraries were normalized and equal volumes were pooled in preparation for sequence analysis. Raw sequence data has been deposited as GSE147905 in the National Center for Biotechnology Information Gene Expression Omnibus. Sequence reads were preprocessed using XPRESSpipe (v0.4.1) [5], with adapter sequences AGATCGGAAGAGCACACGTCTGAACTCCAGTCA and AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT. Reads were processed using H. sapiens GRCh38.13 Ensembl release 99. Differential expression analysis was performed using XPRESSpipe wrapper for DESeq2 (v1.22.1) [6]. Differentially expressed genes were further visualized using XPRESSplot. Isoform abundance analysis was performed using XPRESSpipe wrapper for Cufflinks (v2.1.1) [7] and IGV (v2.4.19) [8]. Scripts used to perform these analyses can be found at https://github.com/j-berg/frodyma_2020 (accessed on 31 March 2020).
Whole cell lysate extracts were prepared in radioimmunoprecipitation assay (RIPA) buffer that was comprised of 50 mM Tris-HCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% sodium dodecyl sulfate, 150 mM NaCl, 2 mM EDTA, 2 mM EGTA, and addition of a protease and phosphatase inhibitor cocktail (Halt, ThermoFisher Scientific). A BCA protein assay (Promega) was used to determine protein concentration. An 8% Acrylamide SDS-PAGE was used to separate out the protein and nitrocellulose membranes were blocked in Odyssey TBS blocking buffer (LI-COR Biosciences) for at least 30 min at room temperature. The primary antibody was allowed to hybridize at least overnight at 4 °C. The PCK2 (8565) antibody was obtained from Cell Signaling Technologies and used at a concentration of 1:2000. The PGC-1β (NBP1-28722) antibody was purchased from NovusBio and used at a concentration of 1:1000. The ERRα (ab76228) antibody was purchased from Abcam and used at a concentration of 1:1000. The FLAG epitope (F1804) antibody was purchased from Millipore-Sigma and used at a concentration of 1:5000. The Strep2 epitope (Ab02208-1.1) antibody was purchased from Absolute Antibody and used at a concentration of 1:2000. The β-actin (sc-47778) and α-tubulin (sc-5286) antibodies were purchased from Santa Cruz Biotechnology and used at a concentration of 1:2000. The anti-ALFA recombinant nanobody-rabbit Fc fusion (N1583) was obtained for NanoTag Biotechnologies and used at a concentration of 1:2000. IRDye 800CW and 680RD secondary antibodies (LI-COR Biosciences, Lincoln, NE, USA) were diluted 1:10,000 in 0.1% TBS-Tween and imaged on an Odyssey Scanner (LI-COR Biosciences). Original images for Western Blot figures are provided in Supplemental File S5.
The Seahorse XFe96 Metabolic Flux Analyzer (Agilent) was used to measure Oxygen Consumption Rate (OCR) in the presence of only 2 mM L-glutamine as a substrate. The day before the experiment, the FluxPak plates were hydrated in water and incubated at 37 °C with ambient CO2. The afternoon before the assay, 40,000 cells were plated in each well of a 96 well assay plate in 12 replicates in regular media. On the day of the experiment, the media was removed and the cells were washed twice with 1 mL of PBS and then covered in 180 µL of XF DMEM medium pH 7.4, (Agilent 103575-100) with 2 mM glutamine (Agilent 103579-100). The cells were incubated in this media at 37 °C with ambient CO2 for 1 h prior to beginning the experiment. The water was removed from the FluxPak and calibration media was added and incubated at 37 °C with the ambient atmosphere for an hour prior to the experiment. Basal OCR was measured four times for three minutes with mixing between measurements to ensure stability and the last measurement was used for statistical evaluation.
HCT116 cells were transfected in five biological replicates, as previously described. 72-h after transfection, the cells were harvested and counted. After washing in saline solution, the cell pellet was resuspended into 1 mL of ice-cold 2:2:1 MeOH: ACN: H2O (v/v/v) containing 10 μM stable isotope-labeled canonical amino acid mix (Cambridge Isotope Laboratories, Inc., Tewksbury, MA, USA) as internal standards. The cells were subsequently lysed in a reciprocal shaker with 0.1 mm glass beads and the samples were centrifuged for 15 min at 13,000 rpm at 4 °C. The supernatant was removed and evaporated to dryness in the SpeedVac. The samples were reconstituted in 100 µL of resuspension buffer containing 20% ACN and 10 mM ammonium acetate, before LC-MS/MS analysis. Chromatographic separation and mass Spectrometry detection were performed using a Shimadzu Nexera ultra-high-performance liquid chromatography (UHPLC) and triple-quadrupole-ion trap hybrid Mass spectrometer (QTRAP 6500 from Sciex, Framingham, MA, USA), equipped with an ESI source. The chromatographic separation of metabolites was achieved on a XSelect (150 × 2.0 mm id; particle size 1.7 µm) analytical column maintained at 40 °C. The optimum mobile phase consisted of 10 mM tributylamine with 5 mM acetic acid in LC-MS grade water containing 2% isopropanol as buffer A and isopropanol as solvent B. The gradient elution is performed as: time zero to five min, 0% solvent B; next 4 min, 2% solvent B; 0.5 min, 6% solvent B; 2 min, 6% solvent B; for next 0.5 min, solvent B was increased to 11% and maintained for 1.5 min; at 35 min, solvent B was increased to 28% for next 2 min and then to 53% in 1 min and maintained for next 6.5 min. Solvent B was reduced to 0% and maintained to equilibrate column till the next injection. The flow rate was 0.4 mL/min, and the total run time was 33 min, and the autosampler temperature was 10 °C. The data acquisition was under the control of MultiQuant software (Sciex, USA). The mass spectrometer was operated in positive as well as negative ion mode using polarity switching. Ions were acquired in multiple reaction monitoring (MRM) mode. MRM details for the selected metabolites were as follows: Oxaloacetate, 131.0/87.0; Phosphoenolpyruvate, 167.0/79.0; Citrate/Isocitrate pool, 191.0/111.0; Fumarate, 115.0/71.0; Succinate, 117.0/99.0. The retention time of each metabolite was confirmed by the 13C-labelled yeast metabolite extract, which was used as the qualitative standard (Cambridge Isotope Laboratories, Inc.). Optimized spray voltage was at 5.5 kV for positive and 4.2 kV for negative mode, ESI source temperature was at 400 °C, nitrogen was used as curtain gas, gas 1 and gas 2 at pressure 30, 40 and 40 arbitrary units, respectively. Declustering potential in positive and negative modes was optimized at 65 and −65 volts.
A full length PCK2 cDNA was obtained through Addgene (plasmid: 23715) and was PCR amplified with a 3′ primer containing a single ALFA tag. The resulting PCR product was digested and ligated into pcDNA-hEF-1α-neomycin resistance. The final product was verified with Sanger sequencing from both directions and incorporated into cells using PEI transfection and selection with G418 (InvivoGen, San Diego, CA, USA, ant-gn-5).
Approximately 200,000 cells with PCK2-ALFA expression were plated in 6-well plates containing 2 glass cover slips (12 mm; Deckglaser) in DMEM medium with 10% FBS. The following day, they were stained with 100 nM MitoTracker Deep Red (Invitrogen, Waltham, MA, USA) for 30 min before washing and formalin fixation. Cells were then stained with a 1:3000 dilution of FluoTag®-X2 anti-ALFA conjugated to Atto-488 (NanoTag Biotechnologies, Göttingen, Germany; N1502-At488) per the manufacturer’s directions. Cells were mounted to glass slides using Fluoromeount G DAPI (SouthernBiotech, Birmingham, AL, USA; 0100-20) and imaged on a Zeiss 800 CLSM with Airyscan at the UNMC Advanced Microscopy Core Facility.
p values were calculated using Prism Software (GraphPad, v8.4.2, La Jolla, CA, USA). A p value of less than 0.05 was considered statistically significant. The statistical significance of these results was evaluated using one way ANOVA with multiple comparisons to knockdown in each cell line. The cell metabolic capacity assays were statistically evaluated using an unpaired, two-sided t-test to compare the effects of PCK2 depletion to control cells. Data are shown as mean +/– standard deviation (SD) unless otherwise noted.
We have previously shown that shRNA-mediated depletion of PGC-1β caused ERRα protein levels to decrease in human CRC cell line, HCT116 [3]. Here, we determined how robust this observation is by using lentiviral-mediated delivery of shRNAs to decrease PGC-1β expression in a panel of human CRC cell lines and immunoblotted for PGC-1β, ERRα, and measured anchorage-independent growth by colony formation in soft agar. Depletion of PGC-1β caused a decrease in ERRα protein levels and anchorage independent growth in a panel of K-Ras mutant CRC cell lines (Figure 1A,B). PGC-1 proteins are known to bind transcription factors, but the physical interaction between the PGC-1β and ERRα has not been explored in detail. To investigate the physical interaction between PGC-1β and ERRα, we generated a vector for epitope-tagging of endogenous PGC-1β using homology directed repair (HDR). Using CRISPR-Cas9, we generated a double stranded break adjacent to the stop codon of PGC-1β and used our plasmid as a template for HDR to eliminate the stop codon and incorporate twin Strep2 triple FLAG epitopes and a neomycin resistance cassette (Figure 1C). After neomycin selection, clones were screened by PCR to confirm the correct genomic insertion (Figure 1D). Endogenous PGC-1β was immunoprecipitated by its FLAG epitopes and eluted with the 3X-FLAG peptide or immunoprecipitated by the Strep2 epitopes and eluted with biotin. Immunoblotting of the eluates showed both PGC-1β and ERRα, confirming their interaction (Figure 1E). These findings suggest PGC-1β binds ERRα to promote ERRα protein levels.
PGC-1 family proteins have been shown to use LxxLL amino acid motifs to bind transcription factors [9,10,11,12,13]. To determine the motif(s) required by PGC-1β to bind ERRα, we developed cell lines with inducible expression of N-terminus twin Strep2 triple FLAG epitope-tagged PGC-1β under doxycycline inducible expression from the AAVS1 safe harbor locus and found the increased levels of PGC-1β also causes a modest induction of ERRα protein levels (Figure 2A). We then made a series of PGC-1β mutant proteins to assess the role of each LxxLL motif in binding ERRα. To be in accordance with the previous labeling from the literature [14] we maintained the same labeling system: Motif 1 LLAEL (amino acids 92–96), Motif 2 LKQLL (amino acids 156–160), Motif 3 LRELL (amino acids 343–347), and Motif 4 LLSHL (amino acids 664–668). Technically, motifs 1 and 4 are reversed but we wanted to directly assess their role in ERRα binding since there is literature evidence to suggest these motifs may be functional in other PGC-1 family members [15]. Motifs were inactivated by mutating all leucines to alanines (LxxLL → AxxAA or LLxxL → AAxxA). Using this strategy, we created one quadruple PGC-1β mutant where all four motifs were inactivated (zero LxxLL motifs) and four triple mutants where only one LxxLL motif was left non-mutated (Only LxxLL motif #1, Only LxxLL motif #2, Only LxxLL motif #3, and Only LxxLL motif #4). The five mutant and wild type PGC-1β cDNAs were integrated into the AAVS1 safe harbor locus of HCT116 cells and the expressed proteins were immunoprecipitated using the FLAG or Strep2 epitopes in separate experiments. The eluates were immunoblotted for PGC-1β and ERRα and showed that the mutant PGC-1β that was functional at only the LxxLL motif #3 (LRELL) immunoprecipitated the same amount of ERRα as wild type PGC-1β (Figure 2B). To test the role of the LRELL motif, we made two additional mutants that had all three leucines mutated to alanines (LRELL → AREAA mutant) or the RE mutated to alanines (LRELL → LAALL mutant). The PGC-1β AREAA mutant cDNA was integrated into both HCT116 and T84 cells and tested against wild type PGC-1β. Loss of the leucines in motif #3 eliminated ERRα binding in both cell lines (Figure 2C). To test the role of amino acids RE in motif #3 on ERRα binding we generated a PGC-1β LAALL mutant cDNA that was integrated into HCT116 cells and tested against wild type PGC-1β. Mutation of amino acids RE showed only a partial loss of ERRα binding (Figure 2D). Lastly, we tested if the PGC-1β mutant that cannot bind ERRα could induce ERRα expression and found that the PGC-1β AREAA mutant was unable to induce ERRα expression compared to wild type PGC-1β (Figure 2E). Overall, these findings suggest that all five amino acids of the PGC-1β LRELL motif are required for optimal ERRα protein binding, which caused increased levels of ERRα protein.
The genes regulated by PGC-1β and ERRα have only been examined in detail in breast cancer and normal liver tissue [16,17,18], but not in CRC. To determine which genes were regulated by PGC-1β and ERRα in CRC, we validated two siRNAs that targeted either protein (Figure 3A) and that loss of PGC-1β caused decreased levels of ERRα, but decreased levels of ERRα did not alter PGC-1β expression. To determine the genes regulated by PGC-1β and ERRα, we transfected HCT116 cells with siRNAs targeting either PGC-1β, ERRα, or non-targeting controls and collected total RNA after 72 h for RNA sequencing (Supplemental File S6). First, depletion of endogenous PGC-1β led to a dramatic decrease in ERRα mRNA, consistent with the model in the literature that binding of PGC-1 proteins to ERRα increases ERRα transcriptional activity by decreases inhibitory phosphorylation and that ERRα can bind to its own promoter to increase ERRα mRNA and protein levels (Figure 2E and 3B) [18,19,20,21]. Secondly, mitochondrial Phosphoenolpyruvate Carboxykinase 2 (PCK2) decreased the most after depletion of both PGC-1β and ERRα (Figure 3B,C). PCK2 is localized to the mitochondria and catalyzes the irreversible conversion of oxaloacetate (OAA) to phosphoenolpyruvate (PEP). Lastly, several other genes that regulate amino acid metabolism decreased after depletion of both PGC-1β and ERRα, suggesting that these two proteins cooperate to promote amino acid incorporation and metabolism to increase survival of colorectal cancer cells. To confirm that the mRNA changes seen after depletion of PGC-1β and ERRα lead to changes in PCK2 protein expression we performed transient knockdown of either protein in two CRCcell lines and observed decreased levels of PCK2 by Western blot (Figure 3D). Lastly, we used lentiviral mediated delivery of shRNA targeting ERRα to reduce ERRα expression in three CRC cell lines and observed decreased levels of PCK2 by Western blot (Figure 3E). These findings suggest the transcriptional control of PCK2 levels by PGC-1β and ERRα is a mechanism to control amino acid metabolism in CRC.
PCK2 mRNA has been shown to be upregulated by mutant K-Ras [22], but its functional role has not been explored in CRC. We have previously shown that PGC-1β expression is dependent on mutant K-Ras signaling [3], suggesting that transcriptional control of PCK2 by PGC-1β is part of oncogenic K-Ras mediated metabolic reprogramming. To assess the role of PCK2 in CRC survival we used lentiviral-mediated delivery of shRNAs targeting PCK2 to deplete PCK2 protein (Figure 4A) and performed anchorage-independent growth studies. We found that depletion of PCK2 caused a significant decrease in soft agar colony formation in a panel of K-Ras mutated CRC cell lines (Figure 4B,C). To determine how depletion of PCK2 alters metabolism, we transiently depleted PCK2 in HCT116 cells and measured intracellular metabolites using liquid chromatography and tandem mass spectrometry (Figure 4D). PCK2 is responsible for the irreversible conversion of oxaloacetate (OAA) to phosphoenolpyruvate (PEP) within the mitochondria. As expected, depletion of PCK2 caused a six-fold increase in total oxaloacetate (OAA) levels and a 55% decrease in total phosphoenolpyruvate (PEP) levels. Unexpectedly, elevated levels of OAA did not appear to be converted into citrate and isocitrate, as the pool of citrate/isocitrate was lower in cells with PCK2 depletion. Depletion of PCK2 also caused an accumulation of upstream TCA metabolites fumarate, succinate, glutamate, and glutamine, suggesting that glutamine flux through the TCA cycle was diminished in the absence of PCK2 activity. To assess L-glutamine utilization, we used shRNAs to deplete PCK2 in a panel of CRC cell lines and measured their oxygen consumption rate using a Seahorse Metabolic Analyzer using only L-glutamine as a substrate. Depletion of PCK2 caused a significant decrease in L-glutamine oxidation in four K-Ras mutant CRC cell lines (Figure 4E). Overall, these findings suggest that PCK2 can control glutamine flux through the TCA cycle to promote CRC cell survival.
To assess if PCK2 can rescue the loss of ERRα activity, we developed a novel plasmid for stable PCK2 expression. PCK2 is anchored to the mitochondrial membrane at its N-terminus so we added an ALFA epitope tag [23] to the C-terminus and expressed it via a human EF-1α promoter in two CRC cell lines using neomycin selection (Figure 5A). We confirmed that the PCK2-ALFA protein was successfully localized to the mitochondria by performing direct immunofluorescence for the ALFA epitope using an ALFA epitope recognizing nanobody conjugated to Atto-488 and compared it to MitoTracker Far Red staining (Figure 5B). To determine if over-expression of PCK2 could rescue the loss of ERRα, we used lentiviral mediated delivery of shRNAs targeting ERRα in two cell lines stably expressing PCK2-ALFA or an empty vector and performed anchorage-independent growth and L-glutamine utilization assays. Loss of ERRα caused a significant loss of colony formation and L-glutamine metabolism that was not rescued by the over-expression of PCK2 (Figure 5C–E). These findings suggest that transcriptional control of PCK2 expression is one mechanism used PGC-1β and ERRα to promote glutamine metabolism and CRC cell survival, but that other PGC-1β and ERRα target genes are also important to CRC metabolism and survival.
Here, we show that PGC-1β and ERRα physically interact and promote genes that increase amino acid metabolism. PGC-1β has been shown to regulate several metabolic processes in other model systems [2,19,24,25,26], but the regulation of PCK2 and amino acid metabolism is a novel observation in CRC that differs from previous studies. Our study is the first to examine the role of PCK2 in CRC metabolism and survival and our observations suggest that PCK2 maximizes flux through the TCA cycle by converting OAA to PEP to promote cell survival. Our finding that elevated levels of OAA after siRNA-mediated depletion of PCK2 were not converted to citrate and isocitrate suggests that there are insufficient levels of either citrate synthetase or its other substrate Acetyl-CoA. Using Western blot, we were able to easily detect citrate synthetase in all CRC cell lines tested. We did not measure levels of Acetyl-CoA in the mitochondria. These data are consistent with reports that the mitochondrial pyruvate complex is down-regulated in colorectal cancer [27,28], which would limit the import of pyruvate into the mitochondria for conversion into Acetyl-CoA. These findings suggest intramitochondrial levels of Acetyl-CoA are insufficient to convert excess OAA to citrate and that conversion of OAA to PEP, presumably for mitochondrial export, is the most efficient method for utilizing L-glutamine by the TCA cycle in CRC. Our data show that PGC-1β uses all five amino acids of its LRELL motif to bind ERRα protein, but no other LxxLL or LLxxL motif appears to bind ERRα, which suggests to us that PGC-1β can only bind one ERRα molecule at a time. ERRα has been shown to directly bind DNA at Estrogen-Related Receptor Response Elements (ERRE) (TNAAGGTCA) to increase transcription [18,29]. However, ERRα has over 800,000 predicted binding sites in the human genome, raising the possibility that additional transcription factors are required for gene selection by PGC-1β. Additionally, mapping of the ERREs shows several near the PCK2 core promoter, but many are greater than several kilobases from the transcriptional start site (TSS) suggesting again that additional factors are required to bring the PGC-1β/ERRα complex to the TSS of target genes to increase transcription. Here, we have created several novel PGC-1β mutant proteins that can be used to assess the role of each LxxLL and LLxxL motif alone or in combination to determine their role in transcription factor binding and to discover new components of PGC-1β signaling. Additionally, PGC-1 family proteins have been shown to bind Host Cell Factor proteins through a DHDY motif [30], which represents another potential mechanism that PGC-1β may use for gene selection. Host Cell Factor 1 and 2 have been proposed to bridge transcriptional co-activators, such as PGC-1 family proteins, to DNA binding via transcription factor binding at their N-terminus Kelch repeat domains, but this process has not been fully explored. Our study has clinical implications for patients with K-Ras mutations. In patients with liver metastases of CRC, K-Ras mutations have been shown to be a negative prognostic marker of overall survival [31,32,33,34]. We have previously shown that PGC-1β expression is dependent on mutant K-Ras [3,4] and that targeting the PGC-1β signaling pathway would represent a novel target for precision medicine in tumors with K-Ras mutations. Currently, there are no treatments that directly inhibit PGC-1β. Our data suggest that targeting ERRα or PCK2 could act as a treatment strategy in K-Ras mutant tumors. Several groups have developed inverse agonists that bind the ERRα ligand binding pocket and force it into an inactive conformation [35,36,37,38,39,40,41]. Our data from (Figure 2E and 3B) show that the binding of PGC-1β to ERRα dramatically increases ERRα activity and expression and suggest that preventing the interaction between PGC-1β and ERRα would inhibit ERRα signaling through an alternate mechanism to inhibitors of the ligand binding pocket. Defining the domain on PGC-1β that is required to bind ERRα represents the first step toward developing inhibitors that would block the PGC-1β/ERRα interaction. Similar efforts are underway to identify selective inhibitors of PCK2, but current inhibitors also target PCK1 with minimal selectivity between the two paralogs [42,43,44,45]. Inhibition of either ERRα or PCK2 would represent a novel treatment strategy that should be tested in pre-clinical models of CRC. Lastly, our study is limited in the following ways: (1) All the experiments were performed in the human CRC cell lines with K-Ras mutations. Although K-Ras mutated tumors represent approximately 40% of all CRC, additional testing is required to see if our results translate to tumors with either wild type K-Ras, mutant BRAF, or HER-2/neu over-expression. (2) We identified several genes regulated by both PGC-1β and ERRα, but only focused on the role of PCK2 in glutamine metabolism. Over-expression of PCK2 was unable to rescue the loss of ERRα, suggesting that additional PGC-1β/ERRα target genes are required for K-Ras induced metabolic change. Further studies to define the role of additional PGC-1β/ERRα target genes will further elucidate the scope of these metabolic changes. (3) Our metabolite analysis of CRC cells with and without PCK2 was limited to whole cell extracts and measured by LC-MS/MS. However, metabolite concentrations can vary across different subcellular compartments. For example, the depletion of PCK2 caused decreased levels of total levels of PEP, which consists of the PEP generated by PCK2 in the mitochondria combined with PEP from other sources. Advancements in methodology will be needed to more precisely define how metabolites change within the mitochondria after the depletion of PCK2. (4) PGC-1α is the PGC-1β paralog with the most amino acid similarity to PGC-1β and has been more intensively studied. The literature has shown that PGC-1α and ERRα directly interact, and multiple reports have characterized the interacting alpha helices by solving the crystal structure of this critical interaction [11,12,13]. Based on the literature, we assume that PGC-1β and ERRα directly interact, but we did not directly test this. (5) We did not directly map the binding of ERRα to the PCK2 gene as we felt this would be best interpreted in the context of a more complex understanding of the PGC-1β/Host Cell Factor proteins interaction.
Inhibiting amino acid metabolism in CRC with K-Ras mutations by targeting PGC-1β signaling has the potential to provide cancer cell specific therapy without subjecting the patient to the stresses of global metabolic restriction. | true | true | true |
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PMC9562881 | Sina Dadafarin,Tomás C. Rodríguez,Michelle A. Carnazza,Raj K. Tiwari,Augustine Moscatello,Jan Geliebter | MEG3 Expression Indicates Lymph Node Metastasis and Presence of Cancer-Associated Fibroblasts in Papillary Thyroid Cancer | 10-10-2022 | thyroid cancer,long-noncoding RNA,biomarker | Papillary thyroid cancer is the most common endocrine malignancy, occurring at an incidence rate of 12.9 per 100,000 in the US adult population. While the overall 10-year survival of PTC nears 95%, the presence of lymph node metastasis (LNM) or capsular invasion indicates the need for extensive neck dissection with possible adjuvant radioactive iodine therapy. While imaging modalities such as ultrasound and CT are currently in use for the detection of suspicious cervical lymph nodes, their sensitivities for tumor-positive nodes are low. Therefore, advancements in preoperative detection of LNM may optimize the surgical and medical management of patients with thyroid cancer. To this end, we analyzed bulk RNA-sequencing datasets to identify candidate markers highly predictive of LNM. We identified MEG3, a long-noncoding RNA previously described as a tumor suppressor when expressed in malignant cells, as highly associated with LNM tissue. Furthermore, the expression of MEG3 was highly predictive of tumor infiltration with cancer-associated fibroblasts, and single-cell RNA-sequencing data revealed the expression of MEG3 was isolated to cancer-associated fibroblasts (CAFs) in the most aggressive form of thyroid cancers. Our findings suggest that MEG3 expression, specifically in CAFs, is highly associated with LNM and may be a driver of aggressive disease. | MEG3 Expression Indicates Lymph Node Metastasis and Presence of Cancer-Associated Fibroblasts in Papillary Thyroid Cancer
Papillary thyroid cancer is the most common endocrine malignancy, occurring at an incidence rate of 12.9 per 100,000 in the US adult population. While the overall 10-year survival of PTC nears 95%, the presence of lymph node metastasis (LNM) or capsular invasion indicates the need for extensive neck dissection with possible adjuvant radioactive iodine therapy. While imaging modalities such as ultrasound and CT are currently in use for the detection of suspicious cervical lymph nodes, their sensitivities for tumor-positive nodes are low. Therefore, advancements in preoperative detection of LNM may optimize the surgical and medical management of patients with thyroid cancer. To this end, we analyzed bulk RNA-sequencing datasets to identify candidate markers highly predictive of LNM. We identified MEG3, a long-noncoding RNA previously described as a tumor suppressor when expressed in malignant cells, as highly associated with LNM tissue. Furthermore, the expression of MEG3 was highly predictive of tumor infiltration with cancer-associated fibroblasts, and single-cell RNA-sequencing data revealed the expression of MEG3 was isolated to cancer-associated fibroblasts (CAFs) in the most aggressive form of thyroid cancers. Our findings suggest that MEG3 expression, specifically in CAFs, is highly associated with LNM and may be a driver of aggressive disease.
Papillary thyroid cancer (PTC) is the most common endocrine malignancy and is the primary contributor to increasing thyroid cancer incidence [1]. While most PTC subtypes are definitively treated with thyroidectomy or lobectomy alone, more aggressive phenotypes require adjuvant radioactive iodine (RAI) therapy and/or subsequent lymph node dissection. Gene expression profiling has already demonstrated the ability to characterize nodules with indeterminate cytology [2,3,4], and ongoing research aims to identify predictive molecular signatures for clinically aggressive disease [5]. Indeed, a major direction for future research is the discovery of cellular factors that serve as both prognostic markers and targets for personalized therapy [5]. Lymph node metastasis occurs in approximately 40% of adult PTC cases and is associated with higher rates of recurrence and reduced survival [6,7,8]. Current imaging modalities, including ultrasound, CT, and FDG-PET/CT, have low sensitivities for detecting tumor-positive lymph nodes in the lateral and central compartments [9,10]. Molecular markers used as adjuvants to current imaging modalities may improve the detection of metastatic lymph nodes and better guide clinical and surgical management for these patients [11]. However, the use of single-gene mutation profiles (e.g., BRAF) to direct surgical management toward prophylactic cervical lymph node dissection remains controversial and is not recommended in routine practice [5,12,13]. Preoperative biomarkers that can better predict lymph node metastasis may yet define the subset of PTC patients who would benefit most from node dissection. Despite well-described effects on cellular function and oncogenesis, long-noncoding RNAs (lncRNAs) are relatively underutilized as biomarkers and therapeutic targets [14,15]. These transcripts of >200 nucleotides do not code for protein but have diverse regulatory potential in gene expression, alternative splicing, post-transcriptional mRNA modification, and epigenomic alterations [16,17,18]. Thoroughly researched lncRNAs such as MALAT1 and HOTAIR [19,20,21] establish important roles in cancer biology and early prognostication. lncRNAs dysregulation in thyroid cancer [22] is associated with aggressive phenotypes [23,24] and stable enough to be detected in serum [25]. Thus, comprehensive identification of differentially expressed lncRNAs may expand our existing toolkit for PTC detection, grading, and staging. Genome-wide investigations of patient PTCs have identified many lncRNAs that have potential diagnostic and therapeutic implications. The bulk of published PTC transcriptomic studies utilizes microarray and quantitative reverse transcription followed by PCR (qRT-PCR), revealing lncRNA dysregulation in cancerous tissue [26,27,28,29]. However, these methods screen for predetermined RNA variants and therefore probe only a fraction of the non-coding transcriptome [30,31]. More recently, RNA-Sequencing of small patient cohorts has associated select lncRNAs with molecular and clinical PTC subtypes [32,33]. The Cancer Genome Atlas Thyroid Carcinoma (TCGA THCA) project has reinforced these associations with larger datasets [24,34,35]; however, RNA-sequencing by TCGA was performed on polyA-purified RNA, which may not capture lncRNAs lacking poly-adenylated tails [36,37]. To maximize the detection of differentially expressed (DE) lncRNAs in PTC, we utilized our previously reported RNA-sequencing dataset of 44 matched-paired tumor and normal adjacent tissue samples using rRNA-depleted total RNA [38]. lncRNAs associated with lymph node metastasis were identified by examining modules of co-expressed genes that were associated with patients who had LNM. We found that MEG3, a lncRNA previously described as a tumor suppressor [39,40], was paradoxically highly associated with LNM and poor survival. We further investigated the cell-specific expression of MEG3 in single-cell thyroid cancer data and found expression was nearly isolated to cancer-associated fibroblasts (CAFs) and that knockdown of MEG3 in human fibroblasts downregulates the expression of matrix metalloproteases (MMPs) previously identified as contributors to cancer metastasis. Overall, our analysis identifies MEG3 expression as highly associated with LNM in thyroid cancer with a potential role in contributing to metastatic potential via its expression in CAFs.
Existing specimens from 44 patients who underwent thyroidectomy with fresh frozen thyroid tissue were collected between 2009 and 2013. All tumors had corresponding matched normal-adjacent tissue, and the diagnosis of PTC was validated by pathological examination. RNA extraction, preparation, and sequencing are as previously described [38]. An R-based data object for the NYMC dataset is hosted (github.com/umasstr/NYMC-PTC, accessed on 8 August 2020) with information regarding the download and visualization of these data included.
Gene biotypes were obtained from GENCODE [41] and genes classified as lncRNAs had one of the following biotype annotations: 3prime_overlapping_ncRNA, antisense, bidirectional_promoter_lncRNA, lincRNA, macro_lncRNA, non_coding, processed_transcript, sense_intronic, and sense_overlapping.
BRAFV600E mutations were detected from patient samples using TaqMan probes previously described by Benlloch et al. [42]. Briefly, 100ng genomic DNA was extracted from remaining TRIzol fractions after first removing the aqueous layer containing RNA and precipitating the DNA. Forward and reverse primers, as well as mutant and wild-type probes, were designed to detect BRAFV600E and BRAFWT DNA, respectively. Primer probe sequences can be found in Supplementary Table S1. Real-time PCR was performed using the TaqMan One-Step RT-PCR Master Mix Reagents kit (Applied Biosystems, Waltham, MA, USA), and amplification and detected were performed with the ABI PRISM 7900 (Applied Biosystems, Waltham, MA, USA). BRAF mutational status was validated via manual examination of aligned RNA-Seq reads using IGV (Broad Institute, Cambridge, MA, USA).
We performed WGCNA [43] with 20,512 genes passing filtering and constructed co-expression gene networks using the optimal power 7 as determined by the scale-free topology criterion [44] and a minimum of 20 genes per module. Nineteen modules of co-expressed genes were constructed with a range of 33 (light yellow) to 5992 (turquoise) genes. Gene sets within each module were subject to MSigDB Hallmark Gene Set Enrichment Analysis [45] to identify biological processes common to co-expressed genes.
Fusions events were detected and annotated using a combination of STAR alignments and the STAR-SEQR tool (https://github.com/ExpressionAnalysis/STAR-SEQR, accessed on 12 June 2019). STAR-SEQR hits were filtered with the following parameters: (1) Fusion genes are only present in PTC samples; (2) at least 5 reads overlapping the cross junction must be present; (3) fused genes must be translocated from different chromosomes, or genomic distance between the genes must be >150 kb. RT-PCR followed by gel electrophoresis was performed to validate filtered hits. Fusion details and primer sequences used are provided in Supplemental Table S2.
Level three RNA-Seq data were downloaded from the UCSC Xena Browser [46].
KEGG Pathway and Gene Ontology enrichment analyses were performed on Advaita’s iPathwayGuide (http://www.advaitabio.com/ipathwayguide, accessed on 6 June 2019) platform using DE genes (abs(log2FC) > 1.5 and q-value < 0.05). Statistical tests of pathway and GO term enrichment were adjusted using FDR correction.
We calculated the thyroid differentiation score using 16 thyroid metabolism and function genes first characterized by TCGA THCA study [47]. MAPK signaling activity was measured using the ERK signature score from TCGA using 52 MAPK signaling genes first described by Pratilas et al. [48].
Hierarchical clustering, heatmap generation, Spearman, and Pearson correlation analyses of DEGs were performed on R version 3.5.3. Pearson’s chi-square test or Fisher’s exact test (when samples were <5) was used to analyze categorical variables. The R package pheatmap (http://rpackages.ianhowson.com/cran/pheatmap/, accessed 10 January 2021) was used for heatmap generation and hierarchical clustering.
We used TIMER2.0 [49] to investigate the correlation between MEG3 expression and infiltration of CAFs in the TCGA THCA dataset. “Purity Adjustment” option was selected to account for the confounding effect of tumor purity and immune cell type infiltration.
Single-cell data from 5 previously described anaplastic thyroid cancer samples [50] were analyzed using the CancerSCEM webtool [51].
We analyzed transcriptomic data from 44 PTC samples with matched normal adjacent tissue (NAT) collected from patients undergoing thyroidectomy between 2009 and 2013 as part of the NYMC dataset [38]. Most patients in this cohort had indicators of aggressive disease, including high rates of BRAFV600E mutation (80%), capsular invasion (77.8%), multifocality (88.9%), and higher T stage (75.6% T3 or higher) (Table 1). Previous studies of PTC epidemiology report BRAFV600E mutations present in 40–60% of PTC cases [52,53], although after reclassification separating the follicular variant PTC (FVPTC) from classical PTC (cPTC), Yoo et al. found 71.4% of cPTC harbored BRAF mutations and more aggressive phenotypes compared to other subtypes [54]. Clinicopathological characteristics of the NYMC dataset showed no significant difference in age, tumor size, lymph node metastasis, or extracapsular invasion when comparing BRAFV600E and BRAFWT tumors, although statistical analysis may be impacted by the limited number of BRAFWT tumors.
Principal component analysis (PCA) on all specimens demonstrated distinct separation on the PC2 axis between PTC and normal adjacent tissue (Figure 1A). Next, we measured thyroid cell differentiation and activation of the MAPK signaling pathway using scoring methods developed by TCGA: the thyroid differentiation score (TDS) and ERK score (Figure 1C) [47]. Consistent with results from the TCGA and Song et al. 2018 [55], BRAFV600E-mutant PTC scored lower on the TDS compared to BRAFWT tumors (p = 4.5 × 10−6). Furthermore, BRAFV600E mutant samples displayed varying TDS scores ranging from −0.48 to −3.48, representing high and low differentiation, respectively, while the TDS of BRAFWT tumors ranged from –0.029 to –1.81. The ERK score, which represents no clear distinction was made between male and female tumors based on BRAF status, ERK score, or TDS (Figure 1C). KEGG pathway enrichment analysis of differentially expressed (DE) genes identified cell adhesion molecules and ECM-receptor interaction as well as pathways related to host immune function (Cytokine–cytokine receptor interactions and allograft rejection) as the most highly enriched among the NYMC dataset (Figure 1D). These findings are consistent with those by Song and colleagues that showed cell adhesion molecules and ECM-receptor interaction pathways were enriched among upregulated genes in PTC [55]. Four BRAFWT PTC tumors harbored fusion genes: CCDC6-RET, TRIM27-RET, ACBD5-RET, and TPM3-NTRK1. Validated fusion genes, breakpoint regions, and expression levels are available in Supplementary Table S2. All four fusion genes were previously reported in PTC [47,54,56,57].
lncRNAs play a key role in transcriptional regulation of protein-coding genes [58], though often in complex genetic circuits not easily reconciled with clinical phenotypes. Our analysis of the NYMC dataset identified 756 non-coding RNAs that underwent ≥1.5-fold change between tumor and normal (q-value ≤ 0.05) (Figure 1E). To identify lncRNAs related to available sample characteristics, we constructed 19 gene network modules from pairwise expression correlations of 20,512 coding and non-coding genes using WCGNA. Modules underwent MSigDB Hallmark Gene Set enrichment analysis, and their eigengenes (the first principal component of each module) were associated with clinicopathological features (Figure 2A). Among the clinical traits probed, lymph node metastasis (LNM) showed the strongest association to a gene module (black, p = 0.05). In total, 188 genes were upregulated and 482 were downregulated in the black module and hallmark pathways enriched included epithelial–mesenchymal transition (p = 1.33 × 10−81), TNFα Upregulation (p = 2.03 × 10−43), and Hypoxia (p = 1.82 × 10−17) (Figure 2B). Several genes that were previously shown to contribute to aggressive phenotypes in thyroid cancer, including SERPINE1 and TBX15 [59,60], were identified in this module and significantly correlated with LNM (Supplementary Table S3). We did not appreciate a gene cluster among black modules genes that would distinguish LNM+ and LNM- tumors (Figure 2C). Among the 74 lncRNAs co-expressed within the black (LNM) module, we examined those with the largest Gene Significance score (GS) (Table 2). Among these lncRNAs, LINC00346, CASC15, EGFR-AS1, DIO3OS, and LINC00702 were all previously reported to contribute to proliferation and invasion [61,62,63,64]. Interestingly, we identified NBAT1, a tumor suppressor gene in other cancer types [65], in the LNM module. Five lncRNAs were differentially expressed only in tumors with LNM; however, the fold change between tumor and normal was only significantly greater among LNM-positive tumors for NBAT1, RP11-815J21.4, and RP11-106D4 (Figure 2D). Ranked by module membership (MM) score denoting correlation between gene expression and eigengene, black module constituent, MEG3, was most predictive of LNM. Kaplan–Meyer analysis of MEG3 in the TCGA shows lower overall survival in patients with higher expression of MEG3; this effect intensifies in BRAF mutant patients (Figure 3A). We also examined TCGA PTC transcriptomes and found that MEG3 is expressed higher in metastatic tumors compared to normal, though the former is poorly represented in this study (n = 8) (Figure 3B). Using qPCR, Wang et al. [66] found MEG3 to be downregulated in LNM-positive PTC patient samples and that overexpression of MEG3 reduces migration and invasion in vitro via RAC1 inhibition. In contrast, our RNA-seq data show that MEG3 is downregulated in LNM-negative samples (q-value = 0.0045) and expression is unchanged in LMN-positives (q-value = 0.86) (Figure 3C). We hypothesized that qPCR transcript quantification may not capture the full library of MEG3 lncRNA variants expressed in PTC. To reconcile discordant trends in tumor MEG3 expression obtained by qPCR [66] and RNA-Seq, we surveyed all MEG3 isoforms found in at least 50% of samples in our dataset. Five isoforms (ENST00000455531, ENST00000398460, ENST00000522771, ENST00000398461 and ENST00000452120) passed filtering criteria. ENST00000452120 displayed the highest overall expression in tumor and normal tissue, was significantly downregulated in LMN-negative tumors, and showed higher (non-significant, p = 0.2) expression in LMN-positive tumors. No obvious isoform switch of the MEG3 gene was observed between LNM-positive, LNM-negative, and normal samples (Figure 4A). Furthermore, Wang et al. qPCR probes showed no enrichment bias toward any subset of MEG3 isoforms (Supplementary Figure S1). The study by Wang et al. used immortalized PTC cell lines in monoculture to study the role of MEG3 in invasion and metastasis. A potential reason for the discrepancy between that study’s results and our findings from the TCGA and NYMC dataset is that MEG3 plays unique roles in cell-autonomous mechanisms vs. its contribution to the tumor microenvironment. Tumors often recruit or modify members of the microenvironment, such as infiltrating immune cells, vascular endothelial and smooth muscle cells, and fibroblasts, to promote metastatic progression [67,68]. We therefore used TIMER2.0 to investigate the correlation between MEG3 expression in the TCGA dataset and infiltration across cell types in the tumor microenvironment. Cancer-associated fibroblasts were strongly associated with MEG3 expression across all four deconvolution algorithms that can measure this cell type (Figure 4B). Given this high correlation, we hypothesized that MEG3-expressing tumors may be secreting cytokines that recruit and activate tumor fibroblasts, including members of the TGFβ superfamily and PDGFα/β. Therefore, we calculated the Pearson correlation between MEG3 expression and these cytokines in our tumor samples and found TGFβ3 to be the most significantly associated with MEG3 expression (Pearson’s rho = 0.74). To determine the cell type within the thyroid cancer tumor environment that expresses MEG3, we aimed to use existing single-cell RNA-sequencing (scRNA-Seq) data from thyroid cancer samples with high metastatic and invasive potential. We therefore examined five anaplastic thyroid cancer samples, given they are the most aggressive form of thyroid cancer that frequently originates from the context of dedifferentiating PTC [69]. We found that four out of five samples showed that expression of MEG3 was nearly isolated to CAFs (Figure 5). Furthermore, the only sample lacking MEG3 expression had the highest cellular purity as scored, suggesting the single-cell suspension of this sample may be enriched with malignant cells and therefore lack sufficient CAFs to detect MEG3 expression (Supplemental Table S4). From the single-cell data we examined, there was clear heterogeneity in the expression of MEG3 among tumor-associated fibroblasts. To better understand functionally how MEG3-expressing fibroblasts differed from those lacking MEG3 expression, we examined gene expression data of human fibroblasts with MEG3 experimentally downregulated. We examined published data from Mondal and colleagues who performed RNA microarrays on human fibroblasts treated with MEG3 siRNAs [70]. Among genes significantly downregulated by MEG3 knockdown, as determined by a −2 fold-change from MEG3-knockdown to control, were MMP-1, MMP-9, and MMP-16, three metalloproteases with previously characterized roles in tumor metastasis [71,72,73].
Despite a generally favorable prognosis, papillary thyroid cancer can transition into aggressive subtypes and metastatic disease in select patients. A toolkit of pharmaceutical, surgical, and targeted radiation-based therapies has extended longevity of these individuals; however, it remains unclear which patients will benefit most from a given intervention in the setting of advanced PTC. As molecular profiling technologies—most prominently high-throughput sequencing—become cheaper and more accessible, novel genetic hallmarks in PTC could inform the clinical approach. In particular, the detection of LNM in the central and lateral neck compartments in the preoperative setting potentially alters the surgical management of patients [74,75]. Here, we analyzed a large set of PTC transcriptomes with a focus on lncRNAs, given their increasingly recognized role in a variety of cancer-related processes yet underutilization as biomarkers relative to protein-coding genes [17,76,77]. We sought to enrich lncRNAs tied to aggressive features of PTC. Using WGCNA, we identified a module of 729 genes associated with epithelial–mesenchymal transition that exhibits a strong correlation to LNM-positivity. Most notably, the lncRNA MEG3 was determined to have the highest module membership score, indicating it may be highly interconnected within this co-expression module as a potential hub gene. We further found increased MEG3 expression in PTC to be associated with LNM, worse overall survival, and higher infiltration with CAFs. MEG3 has been described as a tumor suppressor in many cancer types, including glioma, hepatocellular carcinoma, and even thyroid cancer [39,66,78,79]. However, these studies relied on the expression of MEG3 in tumor cell lines, bulk tissue with predominantly malignant cells, and animal models derived from xenografts of primary tumors. More recent investigations of the tumor microenvironment via single-cell technologies have started to show a diverse role of MEG3 depending on its cellular context. Pan and colleagues demonstrated using scRNA-seq of pancreatic ductal carcinomas that MEG3 expression was significantly enriched in CAFs of primary tumors, and MEG3 expression was significantly associated with epithelial-mesenchymal transition signatures [80]. Given our finding that the proportion of CAFs was highly associated with MEG3 expression in our bulk tumor samples, we aimed to determine if the MEG3 was being expressed by tumor cells that were recruiting CAFs, or if CAFs were directly expressing MEG3. To determine the cell types that express MEG3 in aggressive thyroid cancer, we analyzed existing scRNA-seq data from anaplastic thyroid cancer. Four out of five samples demonstrate MEG3 expression in CAFs but little expression in tumor cells, suggesting CAFs are the primary cell types expressing MEG3. We reasoned that the presence of MEG3-expressing CAFs drives metastatic potential through reorganization of the extracellular matrix to drive tumor invasion. We therefore examined gene expression data for MEG3-knockdown in human fibroblasts. MMP-1, MMP-9, and MMP-16 were downregulated in MEG3-knockdown fibroblasts, suggesting MEG3 regulates the expression of these metalloproteases with implications in CAF-driven metastasis. Mondal and colleagues showed that MEG3 regulates gene expression by targeting chromatin regions and forming RNA-DNA triplex structures at distal regulatory elements and recruiting polycomb repressive complex 2 (PRC2) to inhibit expression [70]. Interestingly, MEG3 was shown to downregulate TGFβ receptor 1 in fibroblasts by Mondal, which may appear discordant with our finding CAFs expressing MEG3 are associated with LNM-positive thyroid cancer since TGFβ signaling is needed for fibroblast activation. However, one possibility is that MEG3 expression may be downstream of TGF B-signaling and a component of the negative feedback loop of the TGFβ signaling cascade [81]. Furthermore, Terashima and colleagues demonstrated that MEG3 knockdown inhibits TGFβ-induced EMT in lung cancer cell lines [82]. A study of MEG3 expression in idiopathic pulmonary fibrosis using scRNA-seq demonstrated that MEG3 regulates the differentiation of bronchial cells through diverse mechanisms, including through YAP1, NOTCH, and SOX2 signaling [83]. Future functional studies are needed to further determine the biological role of MEG3 in CAF activation and its potential contribution to invasion and metastasis. A key limitation of our study is that normal adjacent tissue while carrying histologic features such as healthy tissue have distinct gene expression patterns and may represent an intermediate state or the effects of field cancerization [83]. A recent analysis of adjacent tissue and healthy donor tissue across eight tumor types, including thyroid cancer, found a majority of differentially expressed genes between tumor and adjacent tissue overlaps with gene differentially expressed between tumors and healthy donor tissue, and a limited number of genes showed discordant patterns of differential expression [84]. Nevertheless, future studies should validate coding and non-coding transcripts that we identified in this study by comparing healthy thyroid tissue to PTC. In conclusion, we utilized multiple transcriptomic datasets with matched-paired controls for the identification of lncRNA in a gene co-expression network associated with LNM and enriched in epithelial–mesenchymal transition gene set. The lncRNA MEG3 was identified as a hub of this co-expression module and an indicator of LNM and CAFs infiltration. The identification of MEG3-expressing CAFs rather than malignant cells via scRNA-seq suggests this lncRNA may be playing unique roles in tumorigenesis, invasion, and metastasis based on the cellular context. However, further investigation is needed to fully elucidate the diverse mechanisms MEG3 has and its potential use in personalizing management for PTC. | true | true | true |
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PMC9562898 | Eva Alegre-Cortés,Alberto Giménez-Bejarano,Elisabet Uribe-Carretero,Marta Paredes-Barquero,André R. A. Marques,Mafalda Lopes-da-Silva,Otília V. Vieira,Saray Canales-Cortés,Pedro J. Camello,Guadalupe Martínez-Chacón,Ana Aiastui,Roberto Fernández-Torrón,Adolfo López de Munain,Patricia Gomez-Suaga,Mireia Niso-Santano,Rosa A. González-Polo,José M. Fuentes,Sokhna M. S. Yakhine-Diop | Delay of EGF-Stimulated EGFR Degradation in Myotonic Dystrophy Type 1 (DM1) | 27-09-2022 | AKT,autophagy,DMPK,endosomes,LBPA,lysosomes,muscle atrophy | Myotonic dystrophy type 1 (DM1) is an autosomal dominant disease caused by a CTG repeat expansion in the 3′ untranslated region of the dystrophia myotonica protein kinase gene. AKT dephosphorylation and autophagy are associated with DM1. Autophagy has been widely studied in DM1, although the endocytic pathway has not. AKT has a critical role in endocytosis, and its phosphorylation is mediated by the activation of tyrosine kinase receptors, such as epidermal growth factor receptor (EGFR). EGF-activated EGFR triggers the internalization and degradation of ligand–receptor complexes that serve as a PI3K/AKT signaling platform. Here, we used primary fibroblasts from healthy subjects and DM1 patients. DM1-derived fibroblasts showed increased autophagy flux, with enlarged endosomes and lysosomes. Thereafter, cells were stimulated with a high concentration of EGF to promote EGFR internalization and degradation. Interestingly, EGF binding to EGFR was reduced in DM1 cells and EGFR internalization was also slowed during the early steps of endocytosis. However, EGF-activated EGFR enhanced AKT and ERK1/2 phosphorylation levels in the DM1-derived fibroblasts. Therefore, there was a delay in EGF-stimulated EGFR endocytosis in DM1 cells; this alteration might be due to the decrease in the binding of EGF to EGFR, and not to a decrease in AKT phosphorylation. | Delay of EGF-Stimulated EGFR Degradation in Myotonic Dystrophy Type 1 (DM1)
Myotonic dystrophy type 1 (DM1) is an autosomal dominant disease caused by a CTG repeat expansion in the 3′ untranslated region of the dystrophia myotonica protein kinase gene. AKT dephosphorylation and autophagy are associated with DM1. Autophagy has been widely studied in DM1, although the endocytic pathway has not. AKT has a critical role in endocytosis, and its phosphorylation is mediated by the activation of tyrosine kinase receptors, such as epidermal growth factor receptor (EGFR). EGF-activated EGFR triggers the internalization and degradation of ligand–receptor complexes that serve as a PI3K/AKT signaling platform. Here, we used primary fibroblasts from healthy subjects and DM1 patients. DM1-derived fibroblasts showed increased autophagy flux, with enlarged endosomes and lysosomes. Thereafter, cells were stimulated with a high concentration of EGF to promote EGFR internalization and degradation. Interestingly, EGF binding to EGFR was reduced in DM1 cells and EGFR internalization was also slowed during the early steps of endocytosis. However, EGF-activated EGFR enhanced AKT and ERK1/2 phosphorylation levels in the DM1-derived fibroblasts. Therefore, there was a delay in EGF-stimulated EGFR endocytosis in DM1 cells; this alteration might be due to the decrease in the binding of EGF to EGFR, and not to a decrease in AKT phosphorylation.
Myotonic dystrophy type 1 (DM1) is an inherited disease characterized by progressive muscle weakness and wasting. DM1 is the most common muscular dystrophy; its prevalence varies between 1 and 35 per 100,000 people [1,2]. It is an autosomal dominant disease caused by a nucleotide repeat expansion of cytosine–thymine–guanine (CTG) in the 3′ untranslated region (UTR) of the dystrophia myotonica protein kinase (DMPK) gene [1,3]. Unaffected individuals have 5–37 CTG repeats that remain stable over generations, whereas DM1 patients display more than 40 CTG repeats that tend to increase in successive generations [3]. DM1 is a multisystemic disorder that affects many organs and tissues and can result in endocrine system dysfunction, cataracts, respiratory failure, cancer, and cardiac defects, leading to sudden death in many cases [2,4]. Depending on the onset of the first clinical symptoms, DM1 is classified into five clinical forms: congenital (neonatal), infantile (1 month–10 years), juvenile (11–20 years), adult (21–40 years), and late-onset (40 years and older). Ninety-one percent of congenital forms and longer CTG repeats are associated with maternal inheritance. However, although severe symptoms have been related to maternal inheritance, they only represent 37% of DM1 patients [3]. The severity of muscle atrophy and wasting is positively correlated with the CTG expansion length. The CTG expansion length is related to the induction of cell death and autophagy in various DM1 models such as in the Drosophila DM1 (480 CTG) model [5], human DM1 neural stem cells (1000 CTG) [6], and human DM1 myotubes (90–1800 CTG) [7]. Autophagy is a catabolic mechanism that removes toxic proteins and damaged organelles; its impairment, and especially its exacerbation, have been associated with muscle atrophy in a DM1 mouse model [8]. This cellular process is altered in several DM1 models, such as in Drosophila [5], human skeletal actin (HSA) LR mice, and human muscle cells [9], due to deregulation of the mammalian target of rapamycin (mTOR)/AKT [6,7] and AMP-activated protein kinase (AMPK) pathways, which alter a suitable cellular response upon starvation in DM1 mice [9]. DM1 animals exhibiting severe muscle loss displayed increased AMPK activity and phosphatidylinositol 3-kinase (PI3K)/AKT pathway deregulation [8]. AKT acts upstream of mTORC1, and its decrease in phosphorylation (p-AKT) activates autophagy. Moreover, a decrease in AKT activity (p-AKT) is associated with muscle atrophy [10]. There are numerous discrepancies related to AKT/mTOR pathway regulation in DM1. On the one hand, muscle biopsies from DM1 patients [9] and human DM1 neural stem cells (NSCs) [6] show no significant changes in phosphorylated AKT (Ser473), but the mTOR downstream target, phosphorylated ribosomal protein S6, is decreased [6]. On the other hand, under starvation conditions, there is a decrease in AKT activity in DM1, while mTOR is not affected [9]. AKT signaling is regulated by endocytosis through the sorting of epidermal growth factor receptor (EGFR) towards degradation or recycling pathway [11]. The activation of EGFR upon EGF stimulation is sufficient to induce AKT phosphorylation (Thr308/Ser473) [12], which, in turn, leads to the activation of mTOR to promote protein synthesis [10]. Endocytosed receptors from the plasma membrane are conducted to early endosomes, where they can either be recycled to the cell surface or be transferred into late endosomes and then lysosomes for degradation [13]. The internalization of EGFR and its degradation in lysosomes attenuate receptor signaling, and therefore, the PI3K/AKT pathway [14]. Receptor recycling restores and maintains this signal [11] as well as signals of the downstream substrates (AKT/ERK) [15]. An inhibitor of AKT, AKTVIII has been reported to reduce EGFR degradation, but not completely. This inhibition is thought to reduce EGFR recycling [12]. It was previously reported that AKT phosphorylation is decreased in DM1-derived fibroblasts [16]. However, there are no data on the regulation of the endocytic pathway in DM1. In this study, we characterized the endosomal–lysosomal pathway in primary fibroblasts from healthy subjects (control) and DM1 patients. We observed that the size of endosomes and lysosomes were significantly enhanced in DM1 cells as compared with control (CTRL) cells. Thereafter, we stimulated primary fibroblasts from DM1 patients with a high concentration of EGF to promote EGFR internalization and subsequent lysosomal degradation of EGFR. EGF-stimulated DM1 cells showed a significant decrease in EGF binding and EGFR trafficking during the early steps of endocytosis. However, EGF-stimulated DM1 cells displayed an increase in the phosphorylation levels of AKT and ERK1/2 followed by a phase of decay, excluding an inhibition of the EGFR signaling. Therefore, there is a delay in EGF-stimulated EGFR endocytosis, suggesting an altered intracellular trafficking in DM1 cells.
Human fibroblasts (HFs) from skin biopsies were obtained from three healthy individuals (38–69 years old) and from three myotonic dystrophy type 1 (DM1) patients with 833, 333, or 500 CTG repeats (41–57 years old). Isolation of primary fibroblasts was performed as previously reported [16]. The experiments were performed in agreement with the Comité Ético de Investigación Clínica del Área Sanitaria de Gipuzkoa and with the written and informed consent of the participating subjects in accordance with the Declaration of Helsinki. The cells were maintained in Dulbecco’s modified Eagle’s medium (DMEM, Sigma-Aldrich, Merck KGaA, Darmstadt, Germany, D6546) supplemented with 1% L-glutamine (Sigma-Aldrich, G7513), 10 U/mL penicillin/100 µg/mL streptomycin (Gibco, Grand Island, NY, USA, 15140-122), and 10% fetal bovine serum (FBS, Sigma-Aldrich, F7524) [17]. In the experiments, HFs were seeded between 35,000 and 40,000 cells/mL.
Cells were seeded in 6-well plates 24 h prior to any treatment with the following compounds: bafilomycin A1 (BAF.A1, LC Laboratories, Woburn, MA, USA, R-5000, B-1080, 100 nM) [18]; rapamycin (RAPA, Fisher, Pittsburgh, PA, USA, BP2963.1, 1 µΜ) [19], Hegf (E9644, 100 ng/Ml), pepstatin A (P5318, 50–100 µM), DMSO as a vehicle (dilution factor 1:1000), all from Sigma-Aldrich; and leupeptin (Enzo, ALX-260–009, Farmingdale, NY, USA, 50–100 µM).
To analyze the protein expression levels, cell lysis was performed in buffer containing 0.5% Nonidet P40 (Roche, Mannheim, Germany, 11754599001), 100 mM Tris-HCl (pH 7.4), 300 mM NaCl, protease, and phosphatase inhibitors [20,21]. Proteins were resolved by SDS-gel electrophoresis, and the blots were probed with the following antibodies: HRP-β-actin (AC-15) (ab49900, 1:20,000), cathepsin B (CTSB, ab58802, 1:1000), and LAMP1 (#24170, 1:1000) from Abcam, Cambridge, UK; CTSB (H-5) (sc-365558, 1:1000), CTSC (D-6) (sc-74590, 1:1000), CTSD (D-7) (sc-377299, 1:1000), LAMP1 (H4A3) (sc-20011, 1:1000) and LAMP2 (H4B4) (sc-18822, 1:1000) from Santa Cruz Biotechnology, Dallas, DX, USA; EEA1 (#2411, 1:1000), EGFR (D38B1) (#4267T, 1:1000), Rab5A (#2143, 1:1000), Rab7 (D95F2) (#9367, 1:1000), phosphor-AKT (ser473, #9271), phosphor-ERK1/2(Thr202/Tyr204, #9101), phosphor-mTOR (ser2448, #2971, 1:1000), phosphor-S6 ribosomal protein (D57.2.2E) (ser235/236, #4858, 1:2000), α-tubulin (DM1A) (TUBB, #3873S, 1:1000) from Cell Signaling Technology, Danvers, MA, USA; GAPDH (MAB374, 1:5000) from Merk-Millipore, Burlington, MA, USA; CTSL (CPL33/1) (C4618, 1:1000) and LC3 (L7543, 1:5000) from Sigma-Aldrich; and SQSTM1/p62 (#H00008878, 1:5000) from Abnova, Taibei, China.
Cells were fixed with 4% paraformaldehyde (PFA) and permeabilized with either 0.1% Triton X-100 (Sigma-Aldrich, T9284) in PBS for 5 min [20] or 0.01% saponin (Fluka BioChemika, Merck KGaA, Darmstadt, Germany, #47036) in BSA (1 mg/mL) for one hour. Saponin was only used for endocytosis/lysosome labeling. Triton permeabilization was followed by a one-hour incubation in BSA. After permeabilization, the cells were incubated with primary antibodies against EEA1 (C45B10) (Cell Signaling Technology, Danvers, MA, USA, #3288P, 1:100), EGFR (D38B1) (Cell Signaling Technology #4267S, 1:100), LAMP1 (H4A3) (sc-20011, 1:200), and SQSTM1 (D-1) (sc-28359, 1:200) overnight at 4 °C or for one hour at RT. The cells were then incubated with Alexa Fluor® 568 (A11004)- or 488 (A11008)-conjugated secondary antibodies (ThermoFisher, Waltham, MA, USA) for 1 h at RT. Nuclei were stained with 4′,6-diamidino-2-phenylindole (DAPI [300 nM], Invitrogen D1306) [20]. Images were visualized using an Olympus IX51 inverted microscope equipped with a DP71 camera and with a confocal microscope (A1 confocal imaging system mounted on an inverted Eclipse Ti microscope (Nikon Corp., Tokyo, Japan). The scale of 8-bit images was set from pixels to microns, the threshold was adjusted, and the particle circularity was fixed between 0 and 1. The particle number and the average area occupied in µm2 by those particles were analyzed with ImageJ software 1.53f51, National Instiutes of Health, USA.
The cells were seeded in 6-well plates containing complete DMEM (as described above). The following day, HFs were washed with PBS and starved overnight in FBS-free DMEM supplemented with 0.1% BSA and L-glutamine (termed binding DMEM) [22]. The cells were then treated with or without hEGF (100 ng/mL) in binding DMEM for 0, 15, 30, or 60 min at 37 °C to monitor EGFR internalization and degradation. Depending on the aim of the experiment, the cells were pretreated with leupeptin or BAF.A1. To stop cell treatment, the plates were washed with ice-cold PBS and immediately stored at −80 °C until further use. For WB, the thawed cells were harvested on ice using lysis buffer (1% Triton X-100, 10% glycerol, 50 mM HEPES (pH 7.4), 150 mM NaCl, 2 mM EDTA, 2 mM EGTA, and protease inhibitors) [22] and centrifuged at 13,000 rpm for 15 min. The supernatant was quantified with a bicinchoninic acid (BCA) kit and loaded onto 4–20% gels.
Total RNA was extracted in 1 mL of TRIsure (Bioline, Luckenwalde, Germany, BIO-38032) containing 20% chloroform (Acros Organics, Bridgewater, NJ, USA, 404635000). DNA contamination was eliminated from the RNA samples by processing them with a DNase I kit (Sigma-Aldrich, AMPD1). RNA was reverse-transcribed into complementary DNA (cDNA) with a First Strand DNA synthesis kit (Nzytech, Lisboa, Portugal, MB12501). The cDNA was amplified by RT–qPCR with a KAPA SYBR® Fast kit (Kapa Biosystems, Cape Town, South Africa, KK4601) using the following primers from Integrated DNA Technologies: SQSTM1/p62 (FW: 5′-GGAGAAGAGCAGCTCACAGCCA-3′/RV: 5′-CCTTCAGCCCTGTGGGTCCCT-3′) and GAPDH (FW: 5′-AGCCACATCGCTGAGACA-3′/RV: 5′-GCCCAATACGACCAAATCC-3′) [23]. GAPDH gene expression was used as an endogenous control, and SQSTM1/p62 mRNA expression levels were determined by the 2(−ΔΔCt) ratio.
HFs were seeded on cover slips in 24-well plates. After 24 h, the cells were washed with PBS and starved in binding DMEM (as described above) for 1–2 h at 37 °C. Next, the cells were kept on ice for 10 min and subsequently incubated with 100 ng/mL Alexa-EGF-555 (Invitrogen, Willow Creek Road, OR, USA, E35350) that was diluted in binding medium. After 30 min of incubation on ice, unbound ligand was removed by washing the cells with cold PBS. Time 0 was immediately fixed with 4% PFA to stop the reaction. Warm binding medium was added to the other cover slips, and the internalization of the ligand was analyzed by incubating cells at 37 °C for 5, 10, 20, 30, and 60 min followed by PFA fixation at the indicated times. Images were visualized using an Olympus IX51 inverted microscope equipped with a DP71 camera. The EGF+ vesicles were analyzed with ImageJ software.
Plated cells were detached with trypsin and incubated for 15 min at 37 °C in complete DMEM containing 100 nM Lysotracker Red (LTR, Invitrogen L7528) [24]. LTR is a fluorescent probe that accumulates in acidic organelles (lysosomes and late-endosomes). The percentage of LTR+ fluorescence signal (n = 10,000 cells) was determined by flow cytometry (Beckman Coulter FC500-MPL).
Cell lysates were obtained in cathepsin (CTS) buffer containing 50 mM sodium acetate (pH 5.5), 0.1 M NaCl, 1 mM EDTA, and 0.2% Triton X-100. Protein samples (1–2 μg/µL, 5 µL) were incubated at 37 °C for 90 min in 100 µL of CTS buffer supplemented with 10 μM cathepsin D and E substrate (Enzo Life Sciences, BML-P145) and 25 µM leupeptin [25]. Pepstatin A (25 µg/mL), a CTSD inhibitor, was used as a negative control. To analyze CTSB activity, 1–2 μg/µL protein samples were incubated at 37 °C for 90 min in 100 µL of CTS buffer supplemented with 20 μM CTSB substrate Z-RR-AMC (Enzo Life Sciences, BML-P137) [26]. Leupeptin, a CTSB inhibitor, was used as a negative control. The enzyme activities were quantified with a TECAN (Infinite 200 PRO) plate reader (excitation: 360 nm; emission: 440 nm) and are presented as the relative fluorescence units (RFUs)/μg protein.
HFs were lysed in buffer containing 0.1% Triton X-100 and protease inhibitors. Five microliters (1–2 μg/µL protein) of sample was then incubated at 37 °C for 30 min in 100 µL of a solution containing 150 mM citrate, 0.2 M Na2HPO4 (pH 4.0) and 1.97 mM 4-methylumbelliferyl-N-acetyl-β-D-glucosaminide (Sigma-Aldrich, M2133), the substrate of β-hexosaminidase [26]. The reaction was immediately stopped by adding 190 µL of 0.3 M glycine-NaOH (pH 10.3). The β-hexosaminidase activity was measured with a TECAN infinite 200 PRO microplate reader (excitation: 360 nm; emission: 465 nm) and is represented as RFU/μg protein.
The activity of β-N-acetylglucosaminidase (NAG) was determined using a colorimetric kit assay (Sigma-Aldrich, CS0780). Ten microliters of cell lysate were incubated with 90 µL of substrate solution (1 mg/mL 4-nitrophenyl-N-acetyl-β-D-glucosaminide [NP-GlcNAc] in 90 mM citrate) for 30 min at 37 °C. The hydrolysis of NP-GlcNAc releases the product p-nitrophenol. The reaction was stopped by adding 200 µL of sodium carbonate solution and incubating at 37 °C for 10 min. The absorbance of the yellow product at 405 nm was measured by the TECAN microplate reader. The experiment was performed according to the manufacturer instructions. The results are presented in U/mL.
HFs were grown on coverslips and subsequently fixed in 2% PFA (16% EM grade, Electron Microscopy Sciences, Hatfield, PA, 15710S) and 2% glutaraldehyde (TAAB Laboratory Equipment Ltd., Aldermaston, England) in 0.1 M PHEM buffer (Electron Microscopy Sciences, 11162) for 30 min at room temperature. The samples were then osmicated and further processed for resin embedding [27]. Resin blocks were sectioned (Leica Microsystems, Wetzlar, Germany; UC7), and 70 nm ultrathin serial sections were collected on formvar-coated slot grids and stained with uranyl acetate and lead citrate. The samples were observed under a transmission electron microscope (Tecnai G2 Spirit, FEI) and imaged with an Orius SC1000B charge-coupled device camera using Digital Micrograph software (both Gatan).
Cells were stained with annexin V-FITC (Immunostep, ANXVF-200T) in PBS for 15 min at 37 °C. Propidium iodide (PI, Sigma-Aldrich, P4170, 0.1 mg/mL) [20,24] was subsequently added at the end of incubation to determine the percentage of cell death (apoptosis and/or necrosis) by flow cytometry (n = 10,000 events) (Beckman Coulter FC500-MPL).
The collected data were analyzed using Microsoft Excel and GraphPad Prism 8.0.2. Student’s t test, one-way ANOVA (Tukey’s multiple comparison tests), and two-way ANOVA (Tukey’s multiple comparison tests) were used to establish significant differences between control (CTRL) and DM1 cells and differences in the treatment effects. A p value < 0.05 indicated statistical significance.
Increased autophagy has been associated with DM1 muscle atrophy [8]; therefore, we assessed autophagy in CTRL and DM1 HFs by treating the cells with 1 µM rapamycin (RAPA) or 100 nM bafilomycin A1 (BAF. A1) for 2 h (Figure 1A–E). RAPA is an autophagy inducer that increases the autophagosome formation (LC3-II marker) via the downregulation of mTORC1, whereas BAF.A1 inhibits autophagy allowing the accumulation of LC3-II and the sequestration of substrates in the autophagosomes. RAPA (Figure 1A,B) or BAF.A1 (Figure 1D,E) significantly increased the level of LC3-II in CTRL and in DM1 HFs. Indeed, RAPA activates the formation of autophagosomes in both cell lines by significantly decreasing the phosphorylation levels of S6 (Figure 1A,C), a downstream target of mTOR. However, there were no significant differences in p-S6 levels between CTRL and DM1 cells under basal and RAPA conditions. BAF.A1 inhibits the lysosomal V-ATPase and lysosome-mediated degradation of LC3-II, thereby allowing its accumulation [28]. The difference in LC3-II between CTRL and DM1 cells was not significant under basal and RAPA conditions, but it was higher with BAF.A1 treatment (Figure 1D,E). This difference in the amount of LC3-II suggests an increase in the autophagy flux in DM1 HFs. To evaluate autophagic degradation, SQSTM1/p62 is used as an autophagy substrate due to its selective degradation [29]. In both cell lines, the analysis of SQSTM1/p62 immunostaining indicates a markedly increase in dots per cell with BAF.A1 treatment (Figure 1F,G), although this increase was lower in DM1 cells. There was also a slight reduction in SQSTM1/p62 levels between CTRL and DM1 cells under basal conditions. However, the decrease in SQSTM1 protein levels in DM1 compared with CTRL cells correlates with a diminution in SQSTM1 mRNA in the DM1 cells (Figure 1H). Therefore, the reduction in SQSTM1 protein cannot be only attributed to enhanced autophagy degradation in DM1 cells. The measuring of the autophagic flux of DM1 HFs treated with RAPA and/or BAF.A1 confirmed a significant increase in LC3-II protein levels with BAF. A1 and with the combined treatment (BAF.A1 and RAPA) (Figure 2A,B). Moreover, the difference in LC3-II levels between BAF.A1 and the combined treatment confirmed that autophagy is induced in DM1 cells. In fact, RAPA completely decreased the phosphorylation of S6 (Figure 2A,C). Increased autophagy flux in DM1, evidenced here (Figure 1D,E and Figure 2A,B) and by others, has been shown to be concomitant with an increase in apoptosis [5]. To test this event, cells were treated with RAPA for 24 h and then stained with annexin V and propidium iodide (PI). We observed that DM1 cells displayed a two-fold increase in annexin-V-positive cells (apoptosis) and PI-positive cells (necrosis) when compared with CTRL cells (Figure 2D,E). Furthermore, RAPA treatment maintained DM1-induced apoptosis (Figure 2D). Unexpectedly, it slightly decreased necrosis in DM1 (Figure 2E), although this decrease did not really reduce the significant ratio of necrotic cell death between CTRL and DM1 cells. Taken together, these data indicate that autophagy and cell death were activated in DM1-derived fibroblasts.
The delivery of endocytic cargo to lysosomes is initially routed to early endosomes (RAB5-positive vesicles) and then transferred to late endosomes (RAB7-positive vesicles) [30]. To better understand the endocytic degradative pathway in DM1 HFs, we first characterized the endosomes through the detection of the early endosomal antigen-1 (EEA1), a RAB5-effector that binds phosphatidylinositol-3 phosphate [PI(3)P] via its FYVE domain [31]. The EEA1 protein levels detected by Western blot were similar between CTRL and DM1 cells (Figure 3A,B). We distinguished two populations of EEA1-positive structures by immunofluorescence in both groups: a perinuclear endosomal subpopulation and a distal subpopulation (Figure 3C). Although the total number of EEA1-positive structures did not change between CTRL and DM1 cells (119 ± 12.09 vs. 120 ± 9.33, p = 0.67, respectively), the perinuclear early endosomes were morphologically larger in the DM1 HFs than in CTRL HFs. Indeed, the average area occupied by EEA1 structures is greater in the DM1 cells than in the CTRL cells (Figure 3D). This enlarged endosome subpopulation was also detected by transmission electron microscopy (Figure 3E). The conversion of RAB5 to RAB7 ensures the maturation of early endosomes into late endosomes [32]. The RAB7 protein levels (Figure 3F,G) did not change between cell lines, but the immunofluorescence analysis of lyso-bisphosphatidic acid (LBPA), another late endosomal marker [33], showed an increase in LBPA-positive structures in DM1 cells when compared with CTRL cells (Figure 3H,I). All these data indicate that the endosome morphology in DM1 cells is different from that of CTRL cells.
Lysosomes are acidic organelles that receive material from autophagosomes and endosomes to be degraded [29]. We observed that levels of lysosomal-associated membrane protein (LAMP) 1 (Figure 4A–D) and LAMP2 (Figure 4E,F) were not significantly different between CTRL and DM1 cells. Despite the comparable expression levels of lysosomal proteins and the number of lysosomes (142.5 ± 11.78 vs. 129.8 ± 10.97, p = 0.43 with Student’s t-test), the lysosome size was increased in DM1 cells (Figure 4C), as shown by the average % area significantly occupied by LAMP1+ structures (Figure 4D). Consequently, we stained cells with LTR, a fluorescent probe that selectively accumulates in acidic vesicles, especially in lysosomes and in late endosomes [34]. Interestingly, there were significantly more LTR+ signals in the DM1 cells (Figure 4G), as previously demonstrated in the DM1 fly model and in DM1 myoblasts [5]. We think that the increment in LTR signal is related to the increased lysosomal size in DM1 cells. Lysosomal enzymes are essential for the degradation of lysosomal cargoes, and an increased expression of cathepsin B (CTSB) protein level has been reported in human DM1-NSCs [6]. We investigated whether there were differences in the levels of cathepsin (CTS) enzymes between CTRL and DM1 cells. Pro and intermediate enzyme forms were classified as immature CTS. Variations in CTS protein levels were clearly observed within each group of cell line; however, the mature forms of CTSB (Figure S1A,B), CTSC (Figure S1D,E), CTSL (Figure S1G,H), and CTSD (Figure 4H,I) were not different between the two cell types. A similar result was observed when determining the mCTS/immature ratio (Figure S1C,F,I). When measuring the enzyme activities, CTSB (Figure 4J) and β-HEX (Figure 4K) levels were not different between the two cell types. However, the NAG (Figure 4L) and CTSD (Figure 4M) activities were increased in DM1 cells when compared with CTRL cells; similar results were observed in dystrophic muscles [35]. Therefore, DM1-derived fibroblasts exhibited increased lysosomal size and a significant increase in CTSD activity, suggesting a degree of lysosome functionality.
Endosomes (Figure 3C) and lysosomes (Figure 4C) are enlarged in DM1 cells when compared with CTRL cells; therefore, we examined their impact in the degradative endocytic pathway by incubating fibroblasts with Alexa-555-EGF (555-EGF) for 30 min on ice and followed the evolution of endocytosed 555-EGF by immunofluorescence microscopy at different time points (Figure 5A). At time zero, 555-EGF binding was significantly reduced in DM1 cells compared with CTRL cells (Figure 5B). During the incubation of the fibroblasts at 37 °C, the amount of 555-EGF was quantified at different times from 5 to 60 min. Given the difference in 555-EGF binding, the percentage of 555-EGF+ in each group was considered to be 100 at time zero. Firstly, we observed an increase in 555-EGF+ vesicles in CTRL and DM1 HFs at 10 and 20 min, respectively (Figure 5C). Subsequently, the amount of endocytosed 555-EGF begin to decrease and we observed a significant delay in 555-EGF degradation in DM1 cells compared with CTRL at 20 min. Such a delay disappeared around 60 min of incubation in DM1 cells. We then conclude that there was a decrease in the fluorescent EGF binding to EGFR in DM1, followed by a delay in 555-EGF trafficking and degradation during the first 20 and 30 min of endocytosis. To corroborate the defect in the endocytosis trafficking of 555-EGF in DM1 cells, we assessed the EGFR protein level in HFs upon EGF ligand stimulation. Serum-starved cells were treated with 100 ng/mL EGF for 15, 30, and 60 min (Figure 5D). EGF treatment stimulates and triggers the activation and internalization of the EGF receptor (EGFR) via the endocytic pathway. At time zero, the level of EGFR protein between CTRL and DM1 cells was similar (100 ± 15.81 vs. 101.44 ± 32.44, respectively). Nevertheless, the percentage of EGFR in each group was considered to be 100 at time zero. This percentage started to decrease progressively in CTRL and DM1 cells from 15 min to 60 min (Figure 5E). Additionally, the degradation of EGFR was slower in DM1 cells than in CTRL cells at 15 min (p = 0.02). Interestingly, this difference in EGFR protein level tended to disappear from 30 min (p = 0.07) and become similar at 60 min in CTRL cells and in DM1 cells. Overall, these results sustain a delay in EGF-stimulated EGFR degradation in DM1 cells between 0 and 30 min.
EGF-induced EGFR activation stimulates downstream signaling pathways such as AKT and ERK1/2 [36], which results in an increase in their phosphorylation levels and EGFR endocytosis [37]. To study whether EGFR signaling is activated in DM1 cells, serum-starved cells were treated with EGF for 0, 20, and 60 min. Upon EGF stimulation, the phosphorylation levels of AKT (Ser473) and ERK1/2(Thr202/Tyr204) significantly increased in both cell lines at 20 min (Figure 6). This increase was markedly reduced at 60 min, suggesting that the phosphorylation observed at 20 min was followed by a phase of decay, which results in an attenuation of the EGFR signaling. It is important to note that despite the decrease in EGF binding to EGFR, the EGFR downstream signaling was activated at 20 min in DM1 cells as compared with time zero. However, there was a sustained decrease in p-AKT in DM1 cells as compared with CTRL cells at 20 and 60 min. These data allow us to conclude that EGF-activated EGFR is able to signal from endosomes and its delay in the endocytic trafficking does not affect the downstream (AKT and ERK1/2) signaling pathways in DM1 cells, but highlights a difference in p-AKT levels between cell lines.
To determine whether EGF-stimulated EGFR is sorted to lysosomes, serum-starved cells were treated with EGF (100 ng/mL) and co-labeled with EGFR and LAMP1 antibodies (Figure 7A). EGFR was significantly perinuclear in unstimulated DM1 cells (Figure 7A,B). This result can explain, at least in part, the lower binding of EGF to EGFR in DM1 cells compared with the control cells. This perinuclear distribution persisted and was unchanged upon EGF treatment in DM1 cells, unlike in CTRL cells. In agreement with this intracellular distribution of EGFR, the fluorescence intensity of EGFR significantly decreased upon EGF stimulation for 60 min in CTRL and DM1 cells (Figure 7C). We then evaluated the colocalization of EGFR and LAMP1. Despite the significant difference between CTRL and DM1 cells under basal conditions, the colocalization of EGF-stimulated EGFR with LAMP1 was similar in both cell types at 60 min (Figure 7D). Subsequently, serum-starved cells were pretreated with the lysosomal inhibitor BAF.A1 (100 nM) for one hour and then stimulated for another hour with EGF. A significant accumulation of EGFR was observed in the BAF.A1-treated cells compared with EGF alone (Figure 7E,F), indicating that BAF.A1 reverses EGF-induced EGFR degradation in CTRL and in DM1 cells. Taken together, these results indicate that the degradation of EGF-stimulated EGFR occurs via the endosomal–lysosomal pathway in both cell lines, although the binding of EGF to its receptor is reduced in DM1 cells.
Human fibroblasts from DM1 patients displayed an increase in autophagic flux, despite the downregulated SQSTM1 expression. Most important, lysosomal enzyme activities such as CTSD and NAG were augmented. Moreover, DM1 cells exhibited enlarged perinuclear endosomes and an increase in lysosomal size, which was in correlation with the significant increase in LTR fluorescence signal. Additionally, EGF-stimulated EGFR was internalized and degraded in lysosomes, and such a degradation was prevented with BAF.A1 treatment in CTRL and DM1 cells. However, the binding of EGF to EGFR and EGFR trafficking were significantly reduced in DM1 cells. In spite of the activation of the EGFR signaling pathway, EGFR endocytosis was slowed in DM1 cells. Autophagy was upregulated in DM1-derived fibroblasts (Figure 1), and the impairment of this catabolic process has been widely reported in different DM1 models [5,6,7,9]. However, fibroblasts from three investigated DM1 patients differentiated into myotubes displayed a blocked autophagic flux under the combination of chloroquine treatment and/or starvation [9]. At the same time, chloroquine did not generate additional autophagic vacuoles over the already induced basal autophagy in DM1-NSCs [6]. In our models, LC3-II (an indicator of autophagosome formation) was significantly accumulated with BAF.A1 treatment (Figure 1D,E), which was accompanied by an increase in SQSTM1/p62 puncta (Figure 1F,G). Autophagy is negatively regulated by the Class I PI3K/AKT/mTOR pathway [38], and its exacerbation contributes to muscle atrophy. In muscle atrophy [10] and eventually in DM1, the phosphorylation level of AKT is downregulated and correlated with the reduction in DMPK and muscleblind-like 1 (MBNL1) proteins [16]. Rapamycin, an mTOR inhibitor, promoted LC3 lipidation in the DM1-derived fibroblasts (Figure 1A,B) but not in muscle tissue from HSALR mice [9]; however, it was reported to sufficiently improve muscle function. Hence, this effect was attributed to an mTOR-independent mechanism. In our study, rapamycin downregulated S6(Ser235/236) phosphorylation levels (Figure 2A,C) and did not reduce apoptosis in DM1 HFs after 24 h (Figure 2D). Consistent with these data, autophagy inhibition through Tor overexpression prevents CTG-induced muscle atrophy in DM1 model flies [5]. Another study reinforced that autophagy inhibition improved the proliferation of DM1 skeletal muscle satellite cells via the overexpression of MBNL1, which activates mTOR [39]. Although autophagy outcomes have been controversial among the studied DM1 models, there is evidence that AKT/mTOR pathway dysregulation [5,6,9] is involved in the pathogenesis of myotonic dystrophy. AKT phosphorylation is also regulated by the activation of tyrosine kinase receptors, such as the EGFR. Upon stimulation, EGFR triggers a downstream signaling cascade that involves ERK1/2 and AKT. The internalization and degradation of EGFR in lysosomes promotes signal attenuation [12]. To date, there are not sufficient data to fully clarify the role of endocytosis in DM1. Increased endocytosis was associated with dystrophic muscle fibers, as evidenced by the formation of vesicles from transverse (T) tubules [35,40]. T-tubules are essential for the coordination of calcium release and muscle contraction. Endocytosis ensures the formation of T-tubules from the sarcolemma by membrane sequestration and stabilizes its integrity through tight junctions with the sarcoplasmic reticulum [41]. Therefore, T-tubule alterations in DM1 [42,43] allow us to think that endocytosis may be altered in skeletal muscles cells. In this study, we demonstrated that DM1 HFs contained enlarged endosomes (Figure 3C–E) and lysosomes (Figure 4C,D). This phenotype suggested that the endocytosis pathway could be altered. Interestingly, the binding of EGF to EGFR was reduced and the receptor internalization was also decreased (Figure 5). Despite the enlarged perinuclear endosomes in DM1 cells, the endocytic trafficking was slowed during early EGFR trafficking, but it subsequently reached the EGFR level of the CTRL cells in the later phase of EGF stimulation (e.g., 1 h). A previous study attributed the decrease in EGFR degradation to complete AKT inhibition leading to an accumulation of non-degraded EGF–EGFR complex in EEA1-positive structures [12]. Accordingly, the decrease in AKT phosphorylation [16] could explain the endosome morphology in DM1 cells. Additionally, a crosstalk between autophagy and the endocytic pathway has been established, because autophagy inhibition has been shown to induce damaged endosomes, reduce EGFR recycling, and prevent EGF-mediated signaling [44]. The induction of autophagy in DM1 cells allows us to think that endosomes are not damaged in our experimental model. In addition, there was no co-localization between EEA1 and LAMP1 (data not shown). On the other hand, EGFR endocytosis depends on the expression and localization of the EGFR receptor and on its binding to the ligand [37]. We have not observed a significant difference in EGFR protein levels between cell lines, although it fluctuated in serum-starved CTRL and DM1 cells. In both cell lines, the EGFR-bound EGF resulted in a significant activation of AKT and ERK1/2, which was subsequently down-modulated (Figure 6), suggesting a degradation of EGFR [45]. Therefore, primary human fibroblasts are a good model to study EGFR-mediated signaling. We hypothesized that the decrease in EGF binding might delay the internalization of the receptor in DM1 cells but did not impede its sorting and its degradation in lysosomes, which was clearly prevented with BAF.A1 pre-treatment (Figure 7E,F). Similar results were expected with the addition of 50 µM leupeptin, but without success. This may be due to inadequate concentrations or very short treatment duration. Even though EGFR endocytosis was delayed in DM1 cells, we think that the significant increase in LBPA proteins and CTSD activity might be a compensatory mechanism that mediates the sorting and the degradation of EGF–EGFR complexes. We conclude that the delay in EGFR trafficking is not due to decreased receptor expression or inhibition of AKT in EGF-treated DM1-derived fibroblasts. However, it is the consequence of a perinuclear distribution of the receptor, which significantly reduces the binding of the ligand. Therefore, it will be interesting to stimulate DM1 cells with low EGF concentrations to promote EGFR recycling and to check whether the perinuclear distribution of EGFR will decrease and the ligand binding rate will be restored. The insulin receptor is a tyrosine kinase receptor which is endocytosed upon insulin binding to regulate metabolism [46]. Low insulin responsiveness has been attributed to the aberrant alternative splicing of insulin receptor in DM1 muscle cells [47]. Although descriptive, we think that our findings will provide new insights into the low-insulin-induced metabolic effects in DM1. Moreover, a subcellular distribution of insulin receptor might be a contributing factor to insulin resistance [46]. Nevertheless, further studies are required to fully elucidate EGFR activity in DM1, because altered EGFR signaling is associated with human cancers [48]. Several publications have indexed the overall risk of cancers in DM1 patients [4,49], with the most prevalent being skin cancers, specifically basal cell carcinoma [50,51]. To that end, we cannot exclude endocytic pathway alterations from the mechanism underlying the onset of cancers and/or metabolic diseases [52] in DM1 patients. This study was performed in DM1 primary human fibroblasts; therefore, it would be essential to elucidate the role of endocytosis in DM1 skeletal muscle cells. Impaired endocytosis could be involved in the etiology of DM1 by altering calcium homeostasis. This hypothesis seems to be supported by several studies that have reported a morphological alteration of the sarcoplasmic reticulum and/or the tubular system in myotonic dystrophy [42,43]. | true | true | true |
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PMC9563025 | Iva Marinovic,Maria Bartosova,Rebecca Herzog,Juan Manuel Sacnun,Conghui Zhang,Robin Hoogenboom,Markus Unterwurzacher,Thilo Hackert,Aurelio A. Teleman,Klaus Kratochwill,Claus Peter Schmitt | Understanding Cell Model Characteristics—RNA Expression Profiling in Primary and Immortalized Human Mesothelial Cells, and in Human Vein and Microvascular Endothelial Cells | 05-10-2022 | mesothelium,endothelium,RNA sequencing,in vitro,cell models | In vitro studies are essential in pre-clinical research. While choice of cell lines is often driven by handling and cost-effectiveness, in-depth knowledge on specific characteristics is scant. Mesothelial cells, which interact with endothelial cells, are widely used in research, including cancer and drug development, but have not been comprehensively profiled. We therefore performed RNA sequencing of polarized, primary peritoneal (HPMC) and immortalized pleural mesothelial cells (MeT-5A), and compared them to endothelial cells from umbilical vein (HUVEC) and cardiac capillaries (HCMEC). Seventy-seven per cent of 12,760 genes were shared between the 4 cell lines, 1003 were mesothelial and 969 were endothelial cell specific. The transcripts reflected major differences between HPMC and MeT-5A in DNA-related processes, extracellular matrix, migration, proliferation, adhesion, transport, growth factor- and immune response, and between HUVEC and HCMEC in DNA replication, extracellular matrix and adhesion organization. Highly variable shared genes were related to six clusters, cell tissue origin and immortalization, but also cell migration capacity, cell adhesion, regulation of angiogenesis and response to hypoxia. Distinct, cell type specific biological processes were further described by cellular component-, molecular function- and Reactome pathway analyses. We provide crucial information on specific features of the most frequently used mesothelial and endothelial cell lines, essential for appropriate use. | Understanding Cell Model Characteristics—RNA Expression Profiling in Primary and Immortalized Human Mesothelial Cells, and in Human Vein and Microvascular Endothelial Cells
In vitro studies are essential in pre-clinical research. While choice of cell lines is often driven by handling and cost-effectiveness, in-depth knowledge on specific characteristics is scant. Mesothelial cells, which interact with endothelial cells, are widely used in research, including cancer and drug development, but have not been comprehensively profiled. We therefore performed RNA sequencing of polarized, primary peritoneal (HPMC) and immortalized pleural mesothelial cells (MeT-5A), and compared them to endothelial cells from umbilical vein (HUVEC) and cardiac capillaries (HCMEC). Seventy-seven per cent of 12,760 genes were shared between the 4 cell lines, 1003 were mesothelial and 969 were endothelial cell specific. The transcripts reflected major differences between HPMC and MeT-5A in DNA-related processes, extracellular matrix, migration, proliferation, adhesion, transport, growth factor- and immune response, and between HUVEC and HCMEC in DNA replication, extracellular matrix and adhesion organization. Highly variable shared genes were related to six clusters, cell tissue origin and immortalization, but also cell migration capacity, cell adhesion, regulation of angiogenesis and response to hypoxia. Distinct, cell type specific biological processes were further described by cellular component-, molecular function- and Reactome pathway analyses. We provide crucial information on specific features of the most frequently used mesothelial and endothelial cell lines, essential for appropriate use.
In vitro studies using specific cell models are an integral part of biomedical research, allowing for high throughput analysis of complex cellular systems. They are required for understanding (patho)physiology and for identifying interventions to then be validated experimental in-vivo studies and subsequent clinical trials. The choice of the in vitro cell model depends on the scientific questions, but also on the availability, handling and costs, but should primarily be driven by the suitability of the cells to provide a valid answer. Therefore, in-depth knowledge of specific cellular features is necessary. Mesothelial cell (MC) monolayers line the peritoneal, pleural and pericardial cavities and the reproductive organs. They secrete lubricants to facilitate friction-free organ movement and play a critical role in local homeostasis and immune response, secreting inflammatory mediators, growth factors, extracellular matrix components and procoagulant agents [1]. MCs control fluid and solute transport [2] and they undergo mesothelial-to-mesenchymal transition (MMT) to mediate physiological tissue repair and, in case of pathological settings, angiogenesis and fibrosis [3]. Immortalized pleural mesothelial cells (MeT-5A) and human primary peritoneal mesothelial cells (HPMC) are the most frequently used in vitro models of mesothelial cells, with the latter being suitable for a few passages only and requiring repeated, standardized isolation from human tissue. Extended studies including mesothelial gene KO models are usually performed in MeT-5A [4]. MCs are attached to the basal membrane, and the subjacent submesothelial connective tissue, providing blood supply via capillaries and nerves [5]. Endothelial cells (EC) form the inner lining of the vascular system. They are metabolically highly active, play a critical role in the flow of solutes and fluids into and out of the surrounding tissue [6], and control hemodynamics, coagulation and immune responses. Endothelial alterations are an essential part of a plethora of diseases, such as cardiovascular disease and cancer, the two leading causes of death worldwide [7]. ECs are tissue- and vessel type-specific [8,9]. The most widely used human umbilical vein endothelial cells (HUVEC) represent the large, venous part of the vessel tree, whereas human cardiac microvascular endothelial cells (HCMEC) are representative of microvessels. Both are primary cell lines, with HCMEC being more expensive and more difficult to culture. To overcome the lack of essential knowledge on MC and EC lines, we performed RNAseq analyses of the four most widely MC and EC cell lines, grown on Transwells for specific polarisation. MCs and ECs are both polarized cells, but when grown on plastic or glass surfaces in vitro, they do not develop polarisation, which is a prerequisite for the expression of specific proteins [10]. Our comprehensive and in-depth analysis provides essential information on the suitability of each cell line for specific research questions based on their specific gene expression profiles.
Human endothelial umbilical vein cells (HUVEC), human cardiac microvascular endothelial cells (HCMEC) and the immortalized mesothelial cell line (MeT-5A) were purchased from established vendors (HUVEC and HCMEC from Promocell, Heidelberg, Germany; MeT-5A (ATCC® CRL-9444™) from LGC Standards, Wesel, Germany). Endothelial cells were grown in endothelial cell growth medium (Promocell, Heidelberg, Germany) with supplements and antibiotics according to the manufacturer’s instructions. MeT-5A were cultured in Medium 199 (M199, 31150022, Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% (v/v) foetal bovine serum (FBS, Gibco, Thermo Fisher Scientific, Waltham, MA, USA), 1% (v/v) penicillin/streptomycin (P/S, Gibco, Thermo Fisher Scientific, Waltham, MA, USA). Human peritoneal mesothelial cells (HPMC) were isolated from four non-uremic patients and cultured as previously described [11], as approved by the Ethics Committee of the Medical Faculty, Heidelberg University (S-501/2018). Informed written consent was signed by the patients. The cells were grown in M199 medium supplemented with 10% FBS, 1% penicillin/streptomycin, 0.5 μg/mL insulin, 0.5 μg/mL transferrin, 0.4 μg/mL hydrocortisone and 2 mM L-glutamine (all from Merck, Darmstadt, Germany).
Cells were seeded at a density of 2 × 105 cells per well on polyester mesh (24 mm Transwell®, 0.4 µm pore size, 6-well type; Corning, MA, USA) under normal culture conditions in 3 technical replicates per group. HCMEC and HPMC were pooled (4 donors) before seeding while HUVEC were bought pooled. The insert and outer chamber were filled with 1.5 and 3 mL of cell culture medium, respectively. Transepithelial electrical resistance (TER) was measured daily by EVOM volt/ohm meter with STX-2 electrodes (World Precision Instruments, Sarasota, FL, USA) and cell pellets were collected after reaching plateau. Total RNA isolation was performed using RLT buffer with 1% ß-mercaptoethanol and purified using Micro RNAeasy Kit with on column DNA digestion (Qiagen, Hilden, Germany) following the manufacturer’s procedure. The RNA concentration was measured using a Qubit kit (Invitrogen, Heidelberg, Germany). RNA integrity quantification was performed using RNA screen tape (Agilent, Santa Clara, CA, USA). Detected RNA integrity number (RIN) values of samples were over 9.0 and 500 ng/sample were used for sequencing. The library was prepared using the TruSeq Stranded mRNA Library Prep Kit (Illumina, San Diego, CA, USA). Paired-end 100 bp sequencing was performed on an Illumina Novaseq™ 6000 (LC-Bio Technology CO., Ltd., Hangzhou, China) following the vendor’s recommended protocol. The raw RNAseq data has been submitted to ArrayExpress under the accession number E-MTAB-12021.
Data processing was performed using R (www.r-project.org, accessed on 10 October 2021). Background correction was performed using negative control probes which represented an empty line containing no cell material. The R package Rsubread (available from http://www.bioconductor.org, accessed on 11 October 2021) was used for genome alignment, mapping of reads and producing a matrix of counts [12,13,14]. Out of 60,666 ProbeIDs on the chip, 12,760 protein-coding transcripts remained after filtering out transcripts with an average raw count value < 100, or delta < 1000 and raw count value < 200 in one of the groups. For non-protein-coding transcripts raw counts > 3 were included. For comparisons of two cell models, only the two groups in focus were considered for applying the exclusion criteria. Data normalization and quantitation of differential abundances were performed using the R package DESeq2 [15]. Student’s t-test p-values were additionally corrected for multiple testing with the Benjamini-Hochberg method.
Gene ontology (GO) enrichment analysis was conducted on three different aspects: biological process (BP), cellular component (CC), and molecular function (MF) using ClueGO (Cytoscape app, v.2.5.8., GO database 19 September 2021) [16] and PANTHER online database (https://doi.org/10.5281/zenodo.5228828, released: 18 August 2021). Reactome pathway enrichment analysis was performed using ClueGO. For the gene set enrichment analysis (GSEA) tool, the gene sets were ranked by log2-fold change (FC) value (HUVEC vs. HCMEC, HPMC vs. MeT-5A). The ranked gene list was imported into the GSEA software (v.4.1.0., http://www.gsea-msigdb.org/gsea/index.jsp, accessed on 28 September 2021) [17]. The gene set database “GO: Gene Ontology gene sets (c5.all.v7.5.1.)” was downloaded from MSigDB and queried for pathway enrichment analysis. The size of detected gene sets was limited to 15 to 350 genes. Resulting pathways were selected using FDR Q < 0.05. The EnrichmentMap add-on (Cytoscape) was applied to represent the significant gene sets, to collapse redundant pathways into single biological themes and to visualize the regulation network [18]. Enriched pathways were clustered according to shared genes, applying a minimum gene overlap of 37.5% for shown edges in the network. Heatmap visualisation of DEGs was performed using the R package pheatmap [19]. Column and row clustering were performed by Ward clustering (agglomeration method “Ward.D2”) and Euclidean distance of similarity. The clusters underwent GO enrichment analysis. All significantly enriched terms of biological processes were clustered by ClueGO based on similarity. The statistical significance threshold level for all gene ontology enrichment analysis was FDR Q < 0.05 (Benjamini and Hochberg corrected for multiple comparisons). Data were visualized using R package ggplot [20].
We performed next-generation RNA-seq starting from total RNA from polarized cells. Out of 19,962 unique protein-coding transcripts, 12,760 passed the filtering criteria. From these transcripts, 9853 were shared between all cell lines and 366, 631, 99 and 87 transcripts were HPMC-, MeT-5A-, HUVEC- and HCMEC-specific, respectively. Shared transcripts are given in Figure 1. From 4367 non-protein-coding transcripts 1890 were non-coding RNAs and 2477 were pseudogenes. Mesothelial cell lines expressed 969 transcripts more than endothelial cell lines, with enriched biological functions comprising metabolic, cardiac, neuron, adhesion and ion transport functions (Supplementary Figure S1). Mesothelial cell lines shared 393 mesothelial cell-specific genes, endothelial cell lines shared 235-cell specific genes and their enriched processes and pathways are given in Supplementary Figure S2A,B and Tables S3 and S4. Direct comparison of differentially expressed genes shared by mesothelial and endothelial cells yielded 174 significant genes (Supplementary Figure S2C), which were related to apoptosis, regulation of Notch and Rho signalling, anion and vesicle transport, response to hypoxia, connective tissue development, cell shape and response to bacteria (Supplementary Figure S2D and Table S5). The top 50 genes most variably expressed in mesothelial vs. endothelial cells are given in a heatmap (Supplementary Figure S2E).
HPMC and MeT-5A shared 10,624 transcripts (Figure 2A). Seven hundred and seventy-one were HPMC specific and 944 were MeT-5A specific. Transcripts unique to HPMC were related to the GO terms cell adhesion, immune response, angiogenesis, ECM organization and channel activity (Figure 2B), while transcripts unique to MeT-5A were related to catabolic processes, detection of chemical stimulus and DNA binding (Figure 2C). Of the shared transcripts, 612 were significantly more abundant and 488 less abundant in HPMC versus MeT-5A cells (Figure 2D) (FDR Q-value < 0.05, abs(log2FC) > 2). The list of all enriched cell specific gene sets is provided in Supplementary Table S1. Differential GSEA on the shared genes (Supplementary Table S6) revealed higher abundance of 632 and lower abundance of 453 GO terms in HPMC vs. MeT-5A (FDR < 0.05). GO terms enriched amongst the highly abundant genes were immune and growth factor response, cell migration, proliferation and adhesion, ECM and junction organization, transport, ROS metabolic processes, proteoglycan binding and apoptosis (Figure 3). GO terms identified amongst transcripts less abundant in HPMC cells compared to MeT-5A cells were DNA recombination, telomere maintenance, mitosis, DNA damage response, RNA processing, ATP production and biosynthesis of bases, which reflects the transformation status of the primary versus immortalized cell lines. The largest node of GO terms amongst high abundance transcripts in HPMC related to numerous immune functions (Figure 3) and shared genes with angiogenesis, vasculature development, epithelial and smooth muscle cell proliferation and branching and cell migration, proliferation and adhesion. The term cell adhesion included focal adhesion, cell junction and actin filament organisation, and tyrosine kinase activity. GO term extracellular matrix (ECM) comprised ECM organisation, ECM structural constituent, collagen metabolism, connective tissue development and regulation of MMP activity. Transport related nodes of GO terms associated with transcripts that were more abundant in HPMC than MeT-5A involved metal ions, amino acids, fatty acids and endocytosis.
HUVEC and HCMEC shared 10,534 transcripts (Figure 4A). Four hundred and fifteen were HUVEC specific and 421 were HCMEC specific. Transcripts unique to HUVEC were related to parental terms embryonic development and transcription factor activity (Figure 4B), while transcripts unique to HCMEC were related to tissue and organ development, angiogenesis, mineralization, cellular response and binding processes (Figure 4C). Of the shared genes, 60 genes were significantly more abundant and 148 less abundant (Figure 4D) in HUVEC versus HCMEC (FDR Q-value < 0.05, abs(log2FC) > 2), suggesting higher similarity between endothelial cells compared to mesothelial cells. The list of all enriched cell specific gene sets is given in Supplementary Table S2. We identified 82 differential GO terms enriched amongst the higher abundance genes and 81 GO terms amongst the lower abundance genes (Supplementary Table S7) in HUVEC vs. HCMEC (FDR < 0.05). Highly abundant GO terms were related to chromosome segregation, DNA replication and nucleosome organisation; lowly abundant GO terms were mainly related to cell adhesion, ECM organization and structure (Figure 5).
From 9853 differentially expressed genes common to all cell lines, genes with variance greater than 0.5 (n = 2566) were grouped into six clusters (C1–C6) based on their co-expression (Figure 6A). Column clustering revealed a higher level of similarity between HUVEC and HCMEC, which belongs to one parent cluster shared with HPMC. MeT-5A were distinct from the other three cell lines. The largest cluster, cell cycle process, was more abundant in the immortalized MeT-5A only. Circulatory system development was more abundant in endothelial cells. Regulation of vasculature development, however, was more abundant in HPMC and HCMEC, unchanged in HUVEC and suppressed in MeT-5A. The cell migration cluster was more abundant in the endothelial cell lines, unchanged in HPMC and less abundant in MeT-5A. Cell adhesion and positive regulation of angiogenesis cluster was more abundant in HPMC, the response to hypoxia was more abundant in mesothelial cells and markedly less abundant in the endothelial cell lines (Figure 6). These findings demonstrate highly cell type specific expression profiles. The detailed terms of the individual clusters are given in Figure 6C. To further describe the functional relevance, the cellular localisation, and downstream signalling of the identified clusters, we analysed all identified clusters by cellular component (CC), molecular function (MF) and Reactome pathway analysis (Supplementary Figures S3–S8) which reflect the distinct biologic processes.
In vitro cell studies are an integral part of biomedical research and drug development, with the choice of in vitro models often driven by availability, handling and costs, while lacking essential knowledge on the suitability. This is especially true for MC cell lines, MeT-5A, i.e., immortalized MC derived from pleura and human primary peritoneal MC cells, all of which are currently frequently used. MCs play a key role in serosal cavity homeostasis and related diseases in oncology, cardiology, pulmonology, gynaecology, surgery and in nephrology, specifically in the context of peritoneal dialysis. We now provide the first comprehensive analysis of gene expression profiles of the two types of most frequently used MCs for in vitro research. Since mesothelial and endothelial cells interact in vitro in co-culture systems [21] and in vivo [22], we compared the two MC types with the most frequently used EC types, HUVEC, which are large human vessel endothelial cells, and HCMEC, which are human microvessel endothelial cells. All cells were grown on Transwell filters to assure cell polarization similar to physiological conditions. This approach increases the sensitivity and specificity in detection of differential gene expression related to bioprocesses such as angiogenesis, cell adhesion, migration and the extracellular matrix [23,24]. The four cell types, which are all derived from the same developmental origin, the mesoderm [23], share a large number of expressed transcripts under control conditions. MCs and ECs both represent functional barriers lining the serosal cavities and the vasculature, respectively. In our analysis, MCs express roughly 8% more genes than endothelial cells, with biological functions related to the local physiology of their respective organs and tissues, e.g., the heart, and specific functions of the serosa such as pain perception [25]. Comparing HPMC to MeT-5A, 7% of all transcripts expressed by the two MC types are cell specific and not shared between the MC cell lines. MeT-5A specific profiles are enriched for DNA related processes and mitosis, which is in line with their higher proliferation as compared to HPMC, and for catabolic processes and detection of chemical stimulus. HPMC specific transcript clusters are related to cell adhesion, immune response, angiogenesis, ECM organization and channel activity. When comparing the overlapping but differentially expressed genes, cells adhesion, immune response, angiogenesis, ECM organisation and transport related processes were most prominent. These findings demonstrate fundamental differences in suitability for specific research questions, as discussed below. The higher expression of cell cycle related genes in MeT-5A may be related to immortalisation process. The higher expression of immune related genes in HPMC may be observed due to the tissue origin, with peritoneal MC possibly being exposed more often to pathogens invading from the intestine into the peritoneal cavity than pleural MC. As for MC, most of the transcripts expressed under control conditions were shared between HUVEC and HCMEC, but again with distinct differences in expression levels. Gene sets enriched in transcripts that were more abundant in HUVEC as compared to HCMEC involved chromosome segregation and cell division, gene sets enriched in less abundant transcripts related to extracellular matrix regulation and cell adhesion. Genes specific to HUVEC regulate embryonic development and reflect their foetal origin, while 15 HCMEC specific gene sets were identified and comprise an array of important biological functions, including angiogenesis. Synthesis and angiogenic response to angiogenic factors differs substantially between HUVEC and HCMEC [26]. Likewise, the response of HUVEC to retinoic acid also differs compared to dermal and pulmonary microvascular endothelial cells [27]. The vascular system is diverse in structure and physiology and lining endothelial cells have distinct gene expression programs, which impact their response to experimental manipulation, and their interaction with other cell types [28]. Careful endothelial cell selection is necessary when studying specific processes, as discussed below. We recently compared the proteome of human omental arterioles and HUVEC cells and found a considerable overlap in regulated proteins. Differences regarded immune system processes, hardly detectable in HUVEC and proteins associated with the extracellular region were less evident [29]. Comparison of the most variable transcripts that were still common to all four cell types in this study showed the highest degree of similarity between the two endothelial cell types, followed by primary mesothelial cells, while MeT-5A were the most distant. As expected, the circulatory system development represented the most specific endothelial cluster. Reactome analysis revealed the RhoGTPases as most enriched, but were comparable between both types of endothelial cells. The second cluster, including genes involved in cell migration processes and vesicular transport, was heavily downregulated in MeT-5A cells, while being preserved in the three cell lines. The cluster summarized as cell cycle process, was associated with transcripts with higher abundance in the MeT-5A. These findings suggest major functional differences, possibly related to the immortalisation status. MeT-5A were immortalized with SV40 early region genes, which have been shown to induce the expression of cytoprotective calretinin [30] in mesothelial cells and to disrupt the actin cytoskeleton and tight junctions in kidney epithelial cells [31]. The cluster regulation of vasculature development and response to growth factor stimulus was pronounced in HPMC and HCMEC, less so in HUVEC and completely suppressed in MeT-5A. Mesothelial cells impact angiogenesis in peritoneal tissues via secretion of proangiogenic factors such as VEGF, angiopoietin and chemokines such as CXCL1 [22], and even more so after transition to a mesenchymal cell type [3]. This is relevant in the context of PD, with peritoneal vessel density predicting peritoneal membrane transport function [32], but also in the context of peritoneal carcinomatosis [33]. In view of the present findings, in co-culture experiments for in-depth understanding of cellular interactions of MC and EC, HPMC or MeT-5A should be carefully selected depending on the readout of the experiments. Mesothelial cells are exposed to major mechanical shear stress, and thus, tight adhesion to the peritoneal basement membrane is needed to prevent the exceeding loss of the mesothelial cell lining. Consistent with this, HPMC showed, by far, the strongest expression of genes involved in cell adhesion, while MeT-5A were similar to HUVEC and HCMEC. These venous and capillary endothelial cells are exposed to low blood pressure and thus less shear stress, as for example, aortic endothelial cells. Use of MeT-5A in experimental studies in this context again should be critically assessed and obtained results should be evaluated in HPMC. The last cluster identified in the comparison of the four cell lines was the response to hypoxia, with similar gene expression levels in both MC lines. This is in line with a previous study, demonstrating a similar HIF-1α mediated MMT response of rat primary peritoneal MC and MeT-5A in response to hypoxia [34]. The significantly lower expression levels of genes involved in the response to hypoxia in HUVEC and HCMEC may reflect the differences in physiological oxygen supply, which is persistently high for the endothelial lining of the umbilical vein and microvessels. Mesothelial cells, however, cover basement membranes of the intestine and the lung, with oxygen supply achieved by diffusion only, and possibly fluctuating with mechanical stress [35]. In addition to the cluster analysis providing a categorization of overarching differences between the four cell lines, we further described the specific biological processes by cellular component-, molecular function- and Reactome pathway analyses, allowing for detailed search for processes of interest when designing experimental in vitro studies. Noteworthy, 771 and 944 genes were only expressed in HPMC and MeT-5A, respectively. A total of 415 genes were HUVEC and 421 genes HCMEC-specific. This represents essential information when specific components of biological processes and gene regulation studies are envisaged. The commercially available HUVEC are from pooled donors. For adequate comparisons we therefore pooled HCMEC and HPMC from four individual donors, introducing donor-specific variations. Despite this, we obtained highly consistent findings when comparing the cell lines and technical variability was excellent. We previously described the transcriptome of HPMC from four different donors [36], the heterogeneity between different donors was low. We cultured all cell lines in Transwell systems to obtain cell polarization. While this increased the sensitivity and specificity of our comparative analyses, we cannot rule out that different findings may have been obtained when comparing cells cultured on conventional plates. The latter, however, should rather decrease the validity of the cell model studies as compared to the in vivo setting, where endothelial and mesothelial cells adhere to a basement membrane on the basolateral site and interact with the peritoneal and vascular lumen on the apical site.
Our in-depth RNAseq analysis of the MC and EC types most frequently used in in vitro studies provides a plethora of essential information on cell specific features, necessary for appropriate use in experimental single cell line and cell co-culture studies. | true | true | true |
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PMC9563422 | Xiaxia Niu,Ting Wu,Qishuang Yin,Xinsheng Gu,Gege Li,Changlong Zhou,Mei Ma,Li Su,Shu Tang,Yanan Tian,Ming Yang,Hongmei Cui | Combination of Paclitaxel and PXR Antagonist SPA70 Reverses Paclitaxel-Resistant Non-Small Cell Lung Cancer | 01-10-2022 | PTX resistance,PXR,Tip60,SPA70,acetylation of α-tubulin,mitosis defect | Paclitaxel (PTX) is one of the most efficient drugs for late-stage non-small cell lung cancer (NSCLC) patients. However, most patients gradually develop resistance to PTX with long-term treatments. The identification of new strategies to reverse PTX resistance in NSCLC is crucially important for the treatment. PTX is an agonist for the pregnane X receptor (PXR) which regulates PTX metabolism. Antagonizing PXR, therefore, may render the NSCLC more sensitive to the PTX treatment. In this study, we investigated the PXR antagonist SPA70 and its role in PTX treatment of NSCLC. In vitro, SPA70 and PTX synergistically inhibited cell growth, migration and invasion in both paclitaxel-sensitive and paclitaxel-resistant A549 and H460 lung cancer cells. Mechanistically, we found PTX and SPA70 cotreatment disassociated PXR from ABCB1 (MDR1, P-gp) promoter, thus inhibiting P-gp expression. Furthermore, the combination regimen synergistically enhanced the interaction between PXR and Tip60, which abrogated Tip60-mediated α-tubulin acetylation, leading to mitosis defect, S-phase arrest and necroptosis/apoptosis. Combination of PXT and SPA70 dramatically inhibited tumor growth in a paclitaxel-resistant A549/TR xenograft tumor model. Taken together, we showed that SPA70 reduced the paclitaxel resistance of NSCLC. The combination regimen of PTX and SPA70 could be potential novel candidates for the treatment of taxane-resistant lung cancer. | Combination of Paclitaxel and PXR Antagonist SPA70 Reverses Paclitaxel-Resistant Non-Small Cell Lung Cancer
Paclitaxel (PTX) is one of the most efficient drugs for late-stage non-small cell lung cancer (NSCLC) patients. However, most patients gradually develop resistance to PTX with long-term treatments. The identification of new strategies to reverse PTX resistance in NSCLC is crucially important for the treatment. PTX is an agonist for the pregnane X receptor (PXR) which regulates PTX metabolism. Antagonizing PXR, therefore, may render the NSCLC more sensitive to the PTX treatment. In this study, we investigated the PXR antagonist SPA70 and its role in PTX treatment of NSCLC. In vitro, SPA70 and PTX synergistically inhibited cell growth, migration and invasion in both paclitaxel-sensitive and paclitaxel-resistant A549 and H460 lung cancer cells. Mechanistically, we found PTX and SPA70 cotreatment disassociated PXR from ABCB1 (MDR1, P-gp) promoter, thus inhibiting P-gp expression. Furthermore, the combination regimen synergistically enhanced the interaction between PXR and Tip60, which abrogated Tip60-mediated α-tubulin acetylation, leading to mitosis defect, S-phase arrest and necroptosis/apoptosis. Combination of PXT and SPA70 dramatically inhibited tumor growth in a paclitaxel-resistant A549/TR xenograft tumor model. Taken together, we showed that SPA70 reduced the paclitaxel resistance of NSCLC. The combination regimen of PTX and SPA70 could be potential novel candidates for the treatment of taxane-resistant lung cancer.
Lung cancer is the most lethal cancer in the world and the leading cause of cancer death [1]. Over 80~85% of lung cancer types are non-small cell lung cancers (NSCLC), and the 5-year survival rate of NSCLC in stage IV is less than 18% [2]. Some patients with later stages of NSCLC respond to and benefit from immunotherapy using immune checkpoint inhibitors (ICIs) (e.g., ipilimumab, atezolizumab, nivolumab) to disrupt T-lymphocyte-associated protein 4 (CTLA-4) or programmed cell death protein 1 (PD-1)/programmed cell death protein 1 ligand (PD-L1) pathways, thus reactivating T-cell response to kill tumor cells [3]. However, chemotherapy and targeted therapy are still the main strategies for the majority of lung cancer patients [3,4]. As one of the most efficient clinical chemotherapeutic drugs for lung cancer, paclitaxel (PTX) arrested the tumor cell cycle in the G2/M phase, leading to cancer cell death through stabilization of microtubules [5,6,7]. However, long-term treatment with PTX results in drug resistance though overexpressed P-glycoprotein (P-gp, encoded by gene ABCB1/MDR1), altered tubulin acetylation, and other resistance mechanisms [8]. A regimen targeting overexpressed P-gp and β-tubulin-III (TUBB3) in resistant sublines [9], interfering with microtubule dynamics and spindle checkpoint [10], or inhibiting HDAC1 activity [11], has been proven to exert reversal effects on PTX resistance. It has been reported that the acetylation status of α-tubulin manipulates the microtubule dynamics, and MYST histone acetylate transferase (HAT) Tip60 affects α-tubulin acetylation levels of microtubules [12], therefore, Tip60 and its regulatory mechanisms may be involved in PTX resistance. Over 50% of xenobiotics, including a wide range of therapeutic drugs, are metabolized through the pregnane X receptor (PXR, NR1I2)-regulated metabolic detoxification system. PTX has been shown to be an agonist of PXR, which activates CYP3A4 and MDR1 gene expression [13,14,15]. The PXR is a ligand-dependent orphan nuclear receptor that is important for drug metabolism, and as such plays a major role in the process of therapeutic resistance during cancer treatment [16,17,18,19]. The PXR is enriched in liver and colon tissue [20], however, NSCLC cells such as A549 and H460 cells also contain PXR, suggesting that PXR plays a role in regulating drug resistance in lung cancer therapeutic resistance [14,15,21,22]. Antagonizing PXR, therefore, may render the lung cancer cells sensitive to the PTX treatment. SPA70 (1-(2,5-Dimethoxyphenyl)-4-[[4-(1,1-dimethylethyl)phenyl]sulfonyl]-5-methyl-1H-12,3-triazole,LC-1) (Figure 1A) has been shown to be a very potent and specific PXR antagonist [23]. It dramatically inhibits rifampicin (RIF)-induced Cyp3A expression, while strengthens the RIF-induced protein expression of PXR [23]. Additionally, SPA70 augments the association of PXR with co-repressors (NCoR and SMRT), while it has no effects on the association of co-activators (SRC-1 or TIF2) with PXR [23]. PXR protein contains 434 amino acids, including N-terminal ligand-independent activation function 1 (activation function 1, AF1), highly conserved DNA-binding domain (DBD), hinge region, C-terminal ligand binding domain (LBD) and activation function 2 domain (AF-2) [24,25]. Ligand-bound PXR forms heterodimers with the retinoid x receptor (RXR), then is translocated from the cytoplasm to the nucleus to initiate the downstream gene’s transcription [26]. The drug-resistant gene MDR1 has a direct repeats (DR)-4 responsive element in the promoter region and can be recognized and transcriptionally regulated by PXR [27,28]. Overexpression of PXR and MDR1 was observed in PTX-resistant NSCLC sublines and highly correlated with PTX resistance [29,30]. Therefore, PXR antagonists bearing the potential to inhibit PXR-regulated P-gp expression offer a promising strategy to reverse PTX resistance [31,32,33]. Recent studies showed that PXR played a role in chromosome segregation during mitosis [34]. Structurally, there is a nuclear localization sequence (NLS) and two zinc-finger structures of C4 type residing in the DBD region [34,35]. The region of PXR (R66-76R) governs its nuclear translocation and regulates PXR interaction with the mitotic chromatin [34]. Additionally, the function of PXR is finely tuned by certain transcriptional co-regulators. The agonist binding of PXR causes conformational changes of PXR, leading to disassociation of co-repressors (HDAC/SMRT/NCoR) and recruitment of co-activators, such as steroid receptor co-activator 1 (SRC-1) and RXRα [36,37,38,39]. Co-activators display HAT activity to loosen the highly condensed chromosome structure, thus facilitating PXR transcriptional activation [39]. A recent study showed that PXR augmented the HAT activity of Tip60 and promoted colon cancer cell adhesion and migration [40]. Therefore, fine tuning the PXR-Tip60 activity by PXR antagonist may overcome PTX resistance. In this study, we examined the in vivo and in vitro effect of the combination regimen of PTX and the specific PXR antagonist SPA70 on PTX-sensitive and PTX-resistant NSCLC subline A549 and H460. Furthermore, in order to investigate whether SPA70 derivatives also bear clinical potential to overcome PTX resistance, we developed two analogues based on the scaffold of SPA70 and evaluated their efficiency. Understanding how the PXR antagonist reverses multidrug resistance and ascertaining how PXR regulates cellular mitosis will help us reveal the role of PXR in regulating drug resistance and develop an effective strategy for the treatment of taxane-resistant lung cancer.
A549 and H460 cells (NSCLC) from American Type Culture Collection (ATCC, Manassas, VA, USA) were cultured in RPMI 1640 medium (BOSTER, China) containing 10% fetal bovine serum (Biological Industries, Shanghai, China) and 1% penicillin/streptomycin solution (Meilunbio, Dalian, China). Cells were tested to be mycoplasma-free by using a Mycoplasma Stain Assay Kit (Beyotime, C0296) (Contains Hoechst) according to the manufacturer’s instructions. PTX-resistant A549/TR cells and H460/TR cells were obtained by selection with PTX. We started with 10 nM PTX. Briefly, A549 and H460 cells were cultured in RPMI complete medium with 10 nM PTX and then in PTX-free medium after dead cells were removed. After the cells recovered, the cells were cultured in medium containing an increased concentration of PTX, and then in PTX-free medium after dead cells were removed for recovery. The process was repeated for three months. Stable A549/TR (IC50 = 0.50 μM) and H460/TR cells (IC50 = 0.80 μM) were generated. Resistant index = IC50 of the PTX-resistant cell/IC50 of the parental cell. To generate PXR knockdown cells, PXR KO plasmid (sc-400824-KO-2) and PXR HDR plasmid (sc-400824-HDR-2) were introduced into A549/TR cells by transfection. A total of 0.5 μg/uL puromycin was used for selection for 2 days. Next, the PXR knockdown pool clones were collected and confirmed using Western blotting. Flag-Tip60 and GST-Tip60 was kindly provided by Dr. Yi Tang (Albany Medical College). Transfections were carried out according to the manufacturer’s instructions. PTX (APExBIO, A4393), SPA70 (sigma, SML2662) (Figure 1A) were dissolved in DMSO (ATCC) at a stock solution of 20 mM and stored in −20 °C in a freezer.
Around 5000 cells in 50 μL cell culture medium per well were seeded in 96-well plates. A stock solution of 20 mM PTX or SPA70 was diluted to 0.002~60 μM. On the next day, 50 μL cell culture medium containing the indicated compound at different concentrations was added into the well to make the final drug concentration ranging from 0.001~30 μM. After 72 h, 10 μL CCK-8 solution (APExBIO, K1080) was added for 1~4 h and cell viability was measured with absorbance at 490 nm. The OD value was input to the GraphPad Prism software 8.0.2 (San Diego, CA, USA) and the half maximal inhibitory concentration (IC50) values were calculated.
Around 1000 cells were seeded with triplicates in 12-well plates and were treated with different compounds. After 8~10 d, surviving colonies were fixed with 10% formalin and then stained with 0.1% of crystal violet. After washing, stained colonies were dissolved with buffer containing SDS, and measured by a microplate reader at 490 nm absorbance.
Wound healing assay was used to determine the migration potential of A549 or H460 cells. Around 10,000 A549 or H460 and A549/TR or H460/TR cells were firstly seeded into 12-well plates with triplicates until attached. Next, a 200 μL pipet tip was used to make a straight line through the attached cells in order to create uniform identical scratches. After cellular debris was removed, the fresh new medium containing PTX (2 nM), SPA70 (10 μM), PTX (2 nM) + SPA70 (10 μM) was added. At 72 h after drug treatment, the photographs were taken. In the cell invasion assay, cells in a FBS-free medium were added into the top chamber which contained Matrigel (24-well Matrigel Invasion Chambers, Corning, Biocoat), and treated with different compounds. In the meantime, 10% FBS as an attractant was added in the lower chamber. After 48 h, the invaded cells on the bottom of the upper chamber were fixed and stained with crystal violet, and captured by a microscope.
In order to test P = −gp transporter activity, we measured Rhodamine-123 (Rh-123) accumulation in A549/TR cells by flow cytometric analysis (FACS). Cells were seeded in 6-well plates, and treated with compounds, together with 10 μM Rh-123, for 48 h. After washing with PBS, cells were re-suspended for FACS analysis. We also used a fluorescence microscope to confirm Rh-123 uptake in the cells that attached on glass coverslip.
A ChIP assay kit (Beyotime, P2078) was used to perform ChIP assay. Briefly, A549/TR cells were treated with the indicated regimen for 48 h, then were cross-linked with formaldehyde and processed following the manufacturer’s recommendation. The precipitated DNA product was analyzed by PCR in triplicates with three independent experiments. The MDR1 promoter fragment (−7975 to −7013) containing the cluster of PXR response elements [28] was amplified by PCR with primers: forward 5′-TCATGGTCTGCTAGCAGTGT-3′ and reverse 5′-ACCAAACCCTTTGCCCTAAGA-3′.
The cells were starved in serum-free medium for 24 h, then were treated with paclitaxel (2 nM) and/or SPA70 (10 μM). At 48 h after treatment, cells were pre-fixed in ice-cold ethanol (70%) overnight, then washed with PBS on the second day and incubated with a staining buffer containing 50 μg/mL propidium iodide (PI), and 10 μg/mL RNase for 1 h at dark, and analyzed by flow cytometry. For apoptosis assays, the cells were incubated with annexin V-FITC reagents in the kit (Elabscience, annexin V-FITC/PI fluorescent double staining apoptosis detection kit). The data was acquired by a Bio-Rad ZE5 flow cytometer and was analyzed by ModFit LT 2.0 and FlowJo v10.4 software.
A549/TR cells were treated with the indicated compounds for 48 h, and then were fixed with fresh-made 4% paraformaldehyde (PFA) and permeabilized with 0.2% Triton X-100 in PBS solution. α-tubulin antibody (Thermo Scientific, Waltham, MA, USA, 1:400) was used to stain microtubules, and then labeled with Alexa Fluor 647 goat anti-mouse IgG (Santa cruz) at dark for 1 h. The coverslips were washed with PBS and mounted in a glass slide with anti-fade media containing DAPI (Vectorlabs, H-1200). The photographs were taken with a fluorescent microscope (Olympus BX-53).
Total RNA was extracted by TRIzol (Life Technologies Corporation) and was reverse-transcribed to complete DNA by using a reverse transcriptase kit (Takara). The cDNA as templates were used for real-time quantitative PCR. Amplifications were performed in the iQ5 Optical Module (Bio-Rad) by using SYBR Green Master Mix (Applied Biosystems). The TNFα PCR primers used were forward 5′-CCTCTCTCTAATCAGCCCTCTG-3′ and reverse 5′-GAGGACCTGGGAGTAGATGAG-3′. The MLKL PCR primers used were forward 5′-AGGAGGCTAATGGGGAGATAGA-3′, and reverse 5′-TGGCTTGCTGTTAGAAACCTG-3′. The NF-κB PCR primers used were forward 5′-GAACTCCTCCATTGTGGAACC-3′ and reverse 5′-TCGGAAGCCTCTCTGCTTAG-3′. The GAPDH was used as a housekeeping gene for normalization, and the primers were forward 5′-AACGGATTTGGTCGTATTGGG-3′, and reverse 5′-CCTGGAAGATGGTGATGGGATT-3′.
Cells were lysed in modified RIPA buffer and protein was extracted. The proteins were separated in SDS-PAGE gels and detected using corresponding antibodies. The antibodies and the dilution ratios were: PXR (Santa Cruz, Santa Cruz, CA, USA, sc-48340, 1:1000), Tip60 (Cell Signaling, Danvers, MA, USA, #12058, 1:1000), HA antibody (Santa Cruz, sc-805, 1:200), FLAG (Millipore Sigma, Burlington, MA, USA, F3165, 1:4000), β-actin (Millipore Sigma, A5441, 1:5000), p-AKT (Ser473) (Cell Signaling, #9271, 1:1000), AKT (Cell Signaling, #9272, 1:1000), cleaved PARP (Cell Signaling, #9185, 1:1000), P-gp (Beyotime, Shanghai, China, AF2245, 1:1000), acetylated lysine (Cell Signaling, #9441, 1:1000), and Acetyl-α-Tubulin (Lys40) (Cell Signaling, #3971, 1:1000). For GST-pulldown assays, IPTG-induced GST or GST fusion proteins were incubated with in vitro translated proteins (5 μL) in a buffer containing 100 mM NaCl at 4 °C overnight. On the next day, after extensive washes with a similar buffer containing 150 mM NaCl, GST agarose beads (Sigma)-bound proteins were eluted by boiling in the loading buffer and determined by Western blotting. Every Western blot was repeated three times and the protein band density was quantified by Image J to analyze statistical significance. For co-IP assay, cell lysates were incubated with the indicated antibody in RIPA buffer containing 100 mM NaCl at 4 °C overnight. Protein A/G agarose (Sigma) was then added at 4 °C for another 5 h. After extensive washes with the same RIPA buffer containing 150 mM NaCl, bounded proteins were boiled and detected by Western blotting.
All animal experiments followed the protocol that was approved by the Institutional Animal Care and Use Committee (IACUC) of Lanzhou University (China). 16 BALB/c-Nude male mice (6–8 weeks) were provided by Hunan SJA Laboratory Animal Co., Ltd. A total of 1 × 108/100 μL A549/TR cells were suspended in a solution of PBS mixed with Matrigel (BD Matrigel™ Basement Membrane Matrix, #356234) at a ratio of 2:1 right before use. A total of 100 μL of mixture was inoculated subcutaneously to the right-side dorsal flank of each mouse. Once the tumor reached around 100 mm3, drugs were injected into the mouse. Tumor volume was calculated as length × width 2 × 0.5. PTX and SPA70 were diluted in a vehicle solution (90% PBS, 5% PEG300 and 5% ethanol). All the compounds were applied through intraperitoneal injection, three times per week for four continuous weeks. Four groups were used in this animal study, including vehicle treatment, 5 mg/kg PTX, 30 mg/kg SPA70, and combination group (5 mg/kg PTX + 30 mg/kg SPA70). At the end of the experiments, the mice were euthanized, and tumor xenografts were isolated for pathologic analysis. One-way ANOVA was used to statistically compare tumor size and body weight for in vivo xenograft study. Tumor growth inhibition (TGI) was calculated according to the method which was previously reported [41].
The isolated tumor tissues and other major organs (heart, liver, spleen, lung, kidney) were collected and fixed in 10% formalin solution and embedded in paraffin. The antibodies were used with rabbit anti-Ki67 (#9027, Cell Signaling Technology), rabbit anti-cleaved-caspase 3 (#9664, Cell Signaling Technology), P-gp (AF2245, Beyotime Biotechnology), PXR (sc-48403, Santa Cruz Biotechnology, Inc.), Tip60 (#12058, Cell Signaling Technology). Slides were imaged with microscope and analyzed by image J.
Briefly, sulfonyl chloride SI-1 (5.00 g, 16.5 mM) was added with Na2SO3 (4.17 g, 33.1 mM) and NaHCO3 (2.78 g, 33.1 mM) to form sodium sulfinate SI-2. SI-2 in DMF (58 mL) was added to chloroacetone (2.75 mL, 34.5 mM), stirred for 12 h at room temperature, and then saturated aqueous NaHCO3 (100 mL) was added. The resulting mixture was extracted with EtOAc (3 × 100 mL), and the combined organic phases were washed with brine, dried over with anhydrous MgSO4, filtered, and concentrated under reduced pressure. The residue was purified by flash chromatography on silica gel to create sulfonyl acetone SI-3. SI-3 (1.00 g, 3.09 mM) and MeONa (333 mg, 6.17 mM) in MeOH (10 mL) were added to a solution of azide SI-4 (663 mg, 3.70 mmol) in MeOH (2 mL) over 2 min. The reaction mixture was heated to 85 °C and stirred for 10 h. Upon completion, the reaction was quenched with saturated aqueous NaHCO3 (20 mL), and the resulting mixture was extracted with DCM (3 × 50 mL). The combined organic phases were washed with brine, dried over anhydrous MgSO4, filtered, and concentrated under reduced pressure. The residue was purified by flash chromatography to develop triazole YM-1 (223 mg, 15% yield) as a white solid. PhMgBr (31.0 µL, 2.0 M in THF, 0.06 mM) was added to the solution of triazole YM-1 (10.0 mg, 0.02 mM) and Pd (PPh3)4 (4.8 mg, 0.004 mM) in THF (0.4 mL) at 0 °C. The reaction was warmed to room temperature and stirred for 2 h before it was quenched slowly with saturated aqueous NH4Cl (2 mL). The resulting mixture was extracted with EtOAc (4 × 5 mL). The isolated organic phases were washed with brine, dried over anhydrous MgSO4, filtered, and concentrated under reduced pressure. The residue was purified by flash chromatography to synthesize triazole YM-2 (7 mg, 78% yield) as a white solid.
Data were analyzed using GraphPad Prism software 8.0.2 (San Diego, CA, USA). Student’s t-test or one-way ANOVA were used to compare the statistical significance between indicated groups.
Cell viability assays were carried out to evaluate the efficacy of PTX and SPA70 on parental A549, H460 and PTX-resistant sublines A549/TR and H460/TR. As expected, PTX exhibited the highest potency in parental cells yet had no effect on PTX-resistant cell lines (A549/TR and H460/TR) (Table 1). In comparison, SPA70 displayed similar potency to induce cell death on both parental and resistant lung cancer cells, and the resistance index (RI) was small (A549/TR compared with A549, RI = 2.33; H460/TR compared with H460, RI = 1.53), indicating that SPA70 could overcome clinically relevant PTX resistance in lung cancer. We calculated the combination index (CI) to evaluate whether PTX and SPA70 have a synergistic effect. The result showed that the CI value for PTX and SPA70 was less than 1.0 in both PTX-sensitive and PTX-resistant cells (Table 2), indicating that a combination regimen with PTX and SPA70 has a strong synergistic effect in tested cell lines. The combination of PTX and SPA70 significantly suppressed the colony formation in A549 (22.8% of control, p = 0.003) and H460 (44.9% of control, p = 0.003) cells (Figure 1B and Supplemental Figure S1A). Similarly, combination treatment retained the highest drug effects to inhibit colony formation in A549/TR (40.0% of control, p = 0.002) and H460/TR (43.6% of control, p = 0.006) cells (Figure 1B and Supplemental Figure S1A). Strikingly, after 72 h, the combination of PTX and SPA70 showed significantly higher inhibition on wound closure in A549/TR and H460/TR cells (50.8%, p = 0.004 and 50.6%, p = 0.001) compared with the control group (Figure 1C and Supplemental Figure S1B). These results suggested that combination treatment has great potential to abrogate cancer cell migration in clinically taxane-resistant relevant phenotypes. Additionally, the cell invasive capability was also determined by invasion assay. The combination regimen showed a remarkable inhibition of cell invasion in comparison with the vehicle control in tested cells (A549: p = 0.001; A549/TR: p = 0.005) (Figure 1D). These results suggested that SPA70 synergized with PTX inhibits tumor cell proliferation, migration and invasion in both PTX-sensitive and PTX-resistant lung cancer cells.
It is well documented that overexpression of transmembrane efflux protein P-gp leads to drug resistance [8,14]. We further determined P-gp expression in these PTX-resistant cell lines to test whether our developed A549/TR and H460-TR sublines have clinically relevant drug resistance properties. The results demonstrated that PXR and P-gp were indeed highly expressed in A549/TR and H460/TR cells (Figure 2A,B, Supplemental Figure S2A–C). SPA70 was shown to have a dramatically inhibitory effect on CYP3A mRNA and protein levels in LS180 cells [23]. Consistently, in A549/TR cells, CYP3A4 protein levels were also strongly inhibited (Figure 2A, Supplemental Figure S2A). We also noticed elevated PXR expression in resistant cell lines, and knockdown of PXR correspondingly decreased with P-gp expression (Figure 2B, Supplemental Figure S2B), which is consistent with the role of PXR in the regulation of P-gp [27]. The combined administration of PTX and SPA70 inhibited P-gp protein expression (Figure 2A, Supplemental Figure S2A). Since Rh-123 acts as a P-gp substrate and it can serve as an indicator of efflux activity of P-gp, flow cytometry analyses revealed that there was a lower accumulation of Rh-123 in the combination treatment group (Figure 2C), which seems contradictory with decreased P-gp expression. However, there was remarkable cell death induced by the combination treatment (Figure 1B), and both uptake of Rh-123 and P-gp activity might be abrogated, which explains the parallel changes of P-gp and Rh-123 accumulation in A549/TR cells. Furthermore, as shown in Figure 3C, SPA70 had no effect on Rh-123 accumulation, which excluded the possibility that SPA70 is a P-gp substrate. We next performed chromatin immunoprecipitation assay (ChIP) assays to analyze the effects of combination treatment on the regulatory effects of PXR in the MDR1 promoter; our results revealed that the combination treatment indeed disassociated PXR from the promoter region of MDR1, leading to dramatically diminished mRNA expression of MDR1 (60% of that in the control group) (Figure 2D). Western blot results revealed that the combination regimen dramatically increased the expression level of cleaved PARP in both sensitive and resistant cell lines (Figure 2A), suggesting the apoptosis of the cancer cells resulted from combination treatment.
Compared with parental cell lines, diminished HAT enzyme Tip60 expression was observed in PTX-resistant cell lines, whereas elevated Tip60 appeared when PXR was knocked down. This observation indicated that PXR-regulated Tip60 expression plays a role in PTX resistance (Figure 2A,B). Indeed, there was direct and specific interaction between PXR and Tip60 as determined by the co-immunoprecipitation assay, while agarose beads conjugated with either GST or IgG antibody failed to pull down PXR (Figure 3A,B). Domain mapping results indicated that Tip60 bound to the LBD of PXR through the Tip60 catalytic MYST domain including acetyl-CoA binding domain (Figure 3C,D). Co-expression with PXR decreased Tip60 protein expression in H1299 cells (Figure 3E). Furthermore, PXR shortened Tip60 protein half-life and destabilized Tip60 (Figure 3F). We next measured the Tip60 ubiquitination level in the presence of PXR. We found that PXR expression dramatically increased the amount of ubiquitinated Tip60 protein level (Figure 3G). Therefore, we concluded that PXR destabilized Tip60 by augmenting its ubiquitination level. In order to determine whether the combination regimen affects the binding between PXR and Tip60, we subjected cells to PTX, SPA70, and combination treatment, and incubated cell lysates with either GST or GST-Tip60 for endogenous pulldown assays [42]. The results showed that the interaction between PXR and Tip60 was enhanced by combination treatment (Figure 3H). Since Tip60 is a MYST histone acetylate transferase and it affects α-tubulin acetylation [12], we aimed to investigate whether PXR-Tip60 interaction affects α-tubulin acetylation. By using α-tubulin antibody to precipitate total acetylated lysine, we found that the acetylated α-tubulin indeed became significantly reduced (Figure 3I). These results suggested that a combination regimen-induced PXR-mediated degradation of Tip60 ultimately decreased acetylation of α-tubulin. The acetylation status of α-tubulin will lead to altered dynamics of tubulin and ultimately impair cellular mitosis [8]. Indeed, immunofluorescence microscopy revealed that cells treated with either SPA70 or the combination regimen displayed multipolar spindle apparatus (Yellow arrow, “T” type) and bridged α-tubulin (Figure 3J). The proportion of multipolar nuclei in the SPA70 group was 12% (p = 0.002), whereas the combination group increased to 17% (p = 0.003). Figure 3K graphically illustrates the mechanisms by which PXR interacts physically and functionally with Tip60 and regulates Tip60 activity in PTX-resistant lung cancer cells. Combination treatment with SPA70 facilitates Tip60 degradation by PXR, thus inhibiting α-tubulin acetylation. Consequently, the decreased acetylation of α-tubulin affects tubulin dynamics and induces mitosis defect. Misassembled spindles led to chromosome mis-segregation and abnormal numbers of chromosomes, which are characteristic of mitosis catastrophe. Indeed, we also observed some multinucleated giant cells, which indicated that either SPA70 or the combination regimen induces mitosis catastrophe, leading to cell death, including cell apoptosis and necroptosis, thus sensitizing PTX-resistant lung cancer cells and overcoming drug resistance.
To further explore the mechanism of observed cytotoxic effects, next we investigated the capabilities of the indicated compounds to induce apoptosis. While cells treated with the vehicle control in A549/TR showed 7.3% apoptotic population, treatment with paclitaxel, SPA70, or PTX plus SPA70 showed 6.62, 6.31% and 15.25% apoptotic fractions, respectively (Figure 4A). Since the oxidative stress with elevated ROS induced by effective therapeutics is critical for the apoptotic ending of cancer cells, we analyzed the ROS levels in the resistant cells under different treatment conditions by staining with DCFH-DA fluorescence dye, and our results showed a dramatic increase of ROS production in the combination group (Figure 4B). In order to test whether the combination regimen directly affected the cell cycle in PTX-resistant NSCLC cells, FACS analyses were performed using PI staining. Although a similar G2/M cell cycle arrest presented in every treatment, a mildly increased S-phase arrest occurred in combination group (Supplemental Figure S3). Correspondingly, the dramatically lower Edu incorporation in the S-phase (48.6% of control group) was observed in this combination administration group (Figure 4C). In order to further investigate whether combination treatment-induced S-phase arrest was associated with PXR-Tip60 interaction, we first treated cells with PTX and SPA70 together for 24hs, then arrested cells in specific cell cycles with deoxyribonucleotide thymine (Tdr) and nocodazole, using PXR antibody to precipitate Tip60, and the result demonstrated that the interaction between PXR and Tip60 indeed increased in the S-phase (Figure 4D).
It is well-documented that PTX induces G2/M arrest, thus leading to apoptosis [43]. However, we observed that SPA70 treatment seems to not induce much cell death neither in PTX-sensitive nor in PTX-resistant lung cancer cells (Figure 1B, Supplemental Figure S1A). This leads us to explore cell death mechanisms other than apoptosis. Necroptosis is a kind of programmed, regulated necrosis and it is mediated by the RIPK1 (receptor-interacting protein kinase 1, RIP1)-RIPK3 (RIP3)-MLKL (mixed lineage kinase domain-like pseudo kinase) pathway that regulates necrotic cell death [44]. TNFα was viewed as a critical proinflammatory cytokine leading to the activation of the RIPK1 kinase, subsequently promoting cell death through either necroptosis or apoptosis. Activated RIPK1 forms complex IIb with RIPK3, which subsequently activates and phosphorylates MLKL, inducing necroptosis [44]. Phosphorylated MLKL traffics from cytosol to the damaged plasma membranes, leading to necroptosis, thus MLKL serves as an obligate effector determining the process of necroptosis [45]. In order to investigate whether SPA70 could induce necroptosis in PTX-resistant lung cancer cells, we double-stained cells with Hoechst 33342 (for apoptotic cells) and PI (for necroptotic cells). We found that the combination regimen indeed exhibited strong staining of Hoechst 33342 and PI, indicating both apoptosis and necroptosis occurred in these groups (Figure 5A). Additionally, SPA70 profoundly induced necroptosis, together with significantly higher TNFα mRNA expression compared with the control group and PTX group (Supplemental Figure S4). The levels of the critical necroptosis factors were determined by Western blotting, and marked RIP1 inhibition and elevated p-MLKL were found in the combination regimen-induced cells undergoing necroptosis (Figure 5B), suggesting activation of RIP1-RIP3-MLKL necroptosis pathways.
We further investigated the combination regimen treatment for its therapeutic effects in a mouse xenograft model. PTX-resistant A549/TR xenografts were established in BALB/c-Nude mice and then the mice received 5 mg/kg paclitaxel with or without 30 mg/kg SPA70 intraperitoneal injection for three days per week. Notably, the combination regimen dramatically repressed xenograft tumor growth compared with the other groups (p < 0.05) (Figure 6A,B). During administration, the body weight of mice in all groups did not show significant alteration (Figure 6C). PTX treatment showed slightly better tumor growth inhibition (TGI), about 58.4% more than SPA70 single treatment (TGI 32.0%), whereas the combination treatment significantly repressed tumor growth by 89.5% after 4 weeks of continuous administration to the PTX-resistant xenograft tumor model (Table 3). Of note, although the combination regimen of PTX and SPA70 showed a synergistic effect in cellular experiments, in the in vivo animal model, the combination regimen seemed to work in an additive mode, since the TGI value in the combination group (89.5%) equaled the summarization of that in both the PTX (58.4%) and SPA70 (32.0%) treatment groups. Hematoxylin and eosin (H&E) staining of tumor tissues suggested that the tumor cells had pathological alterations, including cell shape changes, together with nuclei shrinkage, some of which even lost membranes, underlining the antitumor effect of the combination regimen (Figure 6D). Immunohistochemistry (IHC) staining results suggested that tumor cell proliferation was inhibited (Ki67), cell apoptosis (cleaved caspase 3) increased, and P-gp, PXR, and Tip60 expression remarkably reduced in the combination treatment group. Overall, the above evidence proved that a combined regimen of the PXR antagonist SPA70 with PTX had a stronger inhibitory effect on PTX-resistant tumor growth than single compound treatment, indicating SPA70 might be a potent candidate to overcome PTX resistance in NSCLC cells.
As we showed above, the PXR antagonist SPA70 exhibited great potential in overcoming PTX resistance. In order to test whether the SPA70 analogues also has clinical potential, we synthesized compounds YM-1 and YM-2 based on SPA70 scaffold (Figure 7A). We combined YM-1 and YM-2 with PTX to treat parental A549 and PTX-resistant A549/TR cells. The results showed that the combination regimen synergistically suppressed colony formation of A549 and H460 (p < 0.05). The magnitude of suppression was higher in PTX-sensitive cell lines than those in PTX-resistant cell lines (Figure 7B). Moreover, it seems that YM-2 has a better effect than YM-1 on the inhibition of A549 cell migration, as wound healing assays demonstrated that PTX with YM-2 had 18% coverage area of control whereas treatment with PTX and YM-1 showed 32% coverage area of control (Figure 7C). In case of resistant cell lines, both YM-1 and YM-2 treatments gained comparable inhibition of migration when combined with PTX (Figure 7C). Similarly, both SPA70 analogues had inhibitory effects on cell invasion, in which YM-2 showed much potent synergistic effects with PTX (Figure 7D). Collectively, these results suggest that all of these three PXR antagonists have high potential to sensitize PTX treatment.
Xenobiotic metabolism pathways, regulated by xenobiotic sensors such as PXR, play an important role in preventing chemical-induced damage/mutation to the genome [46,47]. Meanwhile, elevated PXR pathways also contribute to the development of therapeutic resistance. Resistance to PTX is frequently observed in cancer patients who go through long-term administration and finally fail the clinical cancer therapy. Until now, many strategies have been applied to reverse PTX resistance, however, overcoming drug resistance is still a huge challenge in a clinical setting. The mechanisms of PTX resistance in NSCLC are quite complicated, which has been thoroughly reviewed in references [8,48]. In recent years, the interactions between PXR and other proteins have attracted substantial attention, especially the interactions between PXR and histone acetyltransferase, kinase and ubiquitination enzymes. In the present study, we investigated the interactions between PXR and the HAT enzyme Tip60. Indeed, PXR binds to Tip60 at the catalytic MYST domain, overlapping with the acetyl-CoA binding site. PXR-Tip60 interaction directly led to the repression of the Tip60 HAT activity, as acetylation of α-tubulin decreased (Figure 3). This effect is similar to that of activating transcription factor 2 (ATF2), which also binds Tip60 at MYST domain spanning the acetyl-CoA binding site, thus repressing Tip60 HAT activity [49]. Indeed, posttranslational modifications (e.g., deubiquitination) of Tip60 alter its HAT activity, as ATF3-recruited USP7 was shown to stabilize Tip60 and augment its HAT activity, in which ATF3 bound Tip60 in the region adjacent of the HAT domain [42]. In the present study, PXR-inhibited Tip60 HAT activity resulted from Tip60 ubiquitination and degradation. This effect might be mediated by an unknown mechanism that PXR recruits certain E3 ligase to degrade TIP60, which is reasonable, as a study reported that the association between PXR and E3 ligase carboxy terminus of Hsc70 interacting protein (CHIP) occurred both in nuclear and the cytoplasm [50]. Phosphorylated PXR further recruited CHIP to regulate cancer cell autophagy [50]. Alternatively, PXR may bear an undefined function that affects Tip60 stabilization. Structurally, the DNA binding domain of PXR is composed of two zinc finger RING sequences, which is quite similar to that in the peroxisome proliferators-activated receptors γ (PPARγ), and PPARγ was proved as an E3 ligase to degrade NF-κB through RING region [51]. Our recent study demonstrated that PXR negatively regulates E3 ligase MDM2 protein expression [20]. However, whether the zinc finger RING sequences can endow E3 ligase activity to PXR remains to be investigated. In line with these findings, the negative regulation of Tip60 by PXR was visualized in a PTX-resistant NSCLC model, and the interaction existed in all phases of the cell cycle, especially the S-phase, suggesting that PXR-regulated Tip60 protein post-translational modifications contribute to the development of PTX resistance, and might be the potential target to overcome PTX-resistance. Interestingly, Tip60 as a tumor suppressor promotes DNA damage response and regulates homology recombination (HR) to promote DNA repair [42,52]. The direct outcome of the inhibition of HAT activity of Tip60 is the decrease of the acetylation of α-tubulin. The status of α-tubulin acetylation determined the dynamics of tubulin during mitosis. In the case of the combined application of PTX and a PXR antagonist, SPA70, microtubule dynamics were dampened, and multipolar spindle apparatus appeared thus to inhibit normal chromosomal segregation. Our current experimental results emphasized that the alteration of α-tubulin acetylation is very important in the sensitization of PTX-resistant cancer cells. Most importantly, we speculated SPA70 to be an antagonist of PXR bearing post-translational modification capability on Tip60, as indicated by increased interaction between PXR and Tip60, and decreased Tip60-acetylated α-tubulin (Figure 3). PXR is well known for its promiscuous interaction with the broad spectrum of structurally diverse ligands, and as such it is an important factor contributing to drug resistance. Targeting PXR, therefore, is an important route for overcoming drug resistance [25]. Antagonists of PXR show great potential to overcome drug resistance. For example, PTX combined with resveratrol can sensitize PTX-resistant breast cancer cells, and sulforaphane combined with PTX can overcome PTX resistance [53,54]. However, the toxic effects of PXR antagonists cannot be avoided [55,56]. For instance, ketoconazole can inhibit the expression of PXR and the hepatoxicity of ketoconazole attracted much attention [57]. In this experiment, given that SPA70 has low toxicity [23], we studied the synergistic effects of PTX and SPA70 on PTX-resistant NSCLC cells in vitro and in vivo. Our experiment demonstrated that combination treatment with PTX and SPA70 has multifaceted mechanisms to sensitize PTX-resistant lung cancer cells. When PTX and SPA70 are combined, SPA70 disassociates PXR from the MDR1 promoter, abrogating PXR-induced MDR1 expression, thus overcoming drug resistance (Figure 2). In line with the observance of mitosis defect, apoptosis and RIP1-RIP3-MLKL-mediated necroptosis was implicated in the mechanism of combination regimen-induced cell death. We found that SPA70 not only induced S-phase genetic toxicity but also produced a remarkable ROS level (Figure 4). Given that SPA70 displays promising potential in overcoming PTX resistance and it has been granted a patent, we started with sulfonyl chloride SI-1 and synthesized two analogues of SPA70. These derivatives are also PXR antagonists and exhibited a synergistic effect with PTX in both parental and PTX-resistant lung cancer cell lines. These results strongly indicated that SPA70 and its derivatives as PXR antagonists have promising potential in overcoming drug resistance. Future research directions will focus on more specific PXR reversal agents bearing capabilities of posttranslational modifications on biomarker proteins in multi-drug resistance, thus regulating cell cycles and sensitizing the resistant cells to death. Nowadays, rational drug combination strategies have displayed substantial therapeutic effects, in particular in malignant tumors, and it is hoped that these novel findings bear huge potential to overcome clinical drug resistance and finally benefit patients. | true | true | true |
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PMC9563431 | Xue Wen,Qi Zhang,Lei Zhou,Zhaozhi Li,Xue Wei,Wang Yang,Jiaomei Zhang,Hui Li,Zijun Xu,Xueling Cui,Songling Zhang,Yufeng Wang,Wei Li,Andrew R. Hoffman,Zhonghui Liu,Ji-Fan Hu,Jiuwei Cui | Intrachromosomal Looping and Histone K27 Methylation Coordinately Regulates the lncRNA H19-Fetal Mitogen IGF2 Imprinting Cluster in the Decidual Microenvironment of Early Pregnancy | 05-10-2022 | decidualization,recurrent spontaneous abortion,long noncoding RNA,epigenetics,H3K27 methylation | Recurrent spontaneous abortion (RSA) is a highly heterogeneous complication of pregnancy with the underlying mechanisms remaining uncharacterized. Dysregulated decidualization is a critical contributor to the phenotypic alterations related to pregnancy complications. To understand the molecular factors underlying RSA, we explored the role of longnoncoding RNAs (lncRNAs) in the decidual microenvironment where the crosstalk at the fetal–maternal interface occurs. By exploring RNA-seq data from RSA patients, we identified H19, a noncoding RNA that exhibits maternal monoallelic expression, as one of the most upregulated lncRNAs associated with RSA. The paternally expressed fetal mitogen IGF2, which is reciprocally coregulated with H19 within the same imprinting cluster, was also upregulated. Notably, both genes underwent loss of imprinting, as H19 and IGF2 were actively transcribed from both parental alleles in some decidual tissues. This loss of imprinting in decidual tissues was associated with the loss of the H3K27m3 repressive histone marker in the IGF2 promoter, CpG hypomethylation at the central CTCF binding site in the imprinting control center (ICR), and the loss of CTCF-mediated intrachromosomal looping. These data suggest that dysregulation of the H19/IGF2 imprinting pathway may be an important epigenetic factor in the decidual microenvironment related to poor decidualization. | Intrachromosomal Looping and Histone K27 Methylation Coordinately Regulates the lncRNA H19-Fetal Mitogen IGF2 Imprinting Cluster in the Decidual Microenvironment of Early Pregnancy
Recurrent spontaneous abortion (RSA) is a highly heterogeneous complication of pregnancy with the underlying mechanisms remaining uncharacterized. Dysregulated decidualization is a critical contributor to the phenotypic alterations related to pregnancy complications. To understand the molecular factors underlying RSA, we explored the role of longnoncoding RNAs (lncRNAs) in the decidual microenvironment where the crosstalk at the fetal–maternal interface occurs. By exploring RNA-seq data from RSA patients, we identified H19, a noncoding RNA that exhibits maternal monoallelic expression, as one of the most upregulated lncRNAs associated with RSA. The paternally expressed fetal mitogen IGF2, which is reciprocally coregulated with H19 within the same imprinting cluster, was also upregulated. Notably, both genes underwent loss of imprinting, as H19 and IGF2 were actively transcribed from both parental alleles in some decidual tissues. This loss of imprinting in decidual tissues was associated with the loss of the H3K27m3 repressive histone marker in the IGF2 promoter, CpG hypomethylation at the central CTCF binding site in the imprinting control center (ICR), and the loss of CTCF-mediated intrachromosomal looping. These data suggest that dysregulation of the H19/IGF2 imprinting pathway may be an important epigenetic factor in the decidual microenvironment related to poor decidualization.
Spontaneous abortion is the most common complication of pregnancy, affecting >20% of recognized pregnancies [1,2]. Most spontaneous abortions are sporadic and occur prior to the second trimester [3,4]. A subset of women suffer from recurrent spontaneous abortion (RSA), defined as three or more consecutive spontaneous abortions before 20 weeks of gestation. This common gynecological emergency poses significant challenges to future fertility and general psychological health. A successful pregnancy depends upon complex crosstalk between the developmentally competent embryo and the receptive maternal endometrium [5,6]. Upon implantation, embryos elicit a complex response in the decidua, characterized by transformation of stromal fibroblasts into secretory, epithelioid-like decidual cells, accompanied by the influx of specialized uterine immune cells and vascular remodeling. Decidual cells produce growth factors and cytokines [7,8], including insulin-like growth factor binding protein 1 (IGFBP1) and prolactin (PRL), which can be used as biomarkers for decidualized cells. Abnormal endometrial receptivity is a key factor leading to implantation failure. However, the molecular factors that regulate this crosstalk in decidualization reactions remains largely uncharacterized. Longnoncoding RNAs (lncRNAs) act as prominent epigenetic factors in normal development and numerous diseases, often by interacting with chromatin remodeling complexes [9,10,11]. Differential expression and risk analyses have identified multiple lncRNAs that are associated with recurrent miscarriage [12]. However, little is known about the specific mechanisms of these lncRNAs. Decidualization of the endometrium plays an essential role for the establishment of a successful pregnancy. In order to identify key RNA molecules that mediate the crosstalk at the fetal–maternal interface, we explored RNA transcriptome sequencing datasets from RSA patients. We found that H19, an imprinted lncRNA that is expressed from the maternal allele [13,14], and its reciprocally coregulated IGF2, a fetal mitogen gene that is expressed from the paternal allele [15,16], were highly upregulated in decidual tissues. Genomic imprinting of the H19/IGF2 cluster is regulated by the methylation status of CpG islands in the imprinting control region (ICR) located upstream of the H19 gene. The ICR contains seven CTCF binding sites. The sixth CTCF binding site is differentially methylated [17] and serves as a CTCF “boundary insulator” [18]. Specific binding of CTCF to the unmethylated maternal allele orchestrates the formation of an intrachromosomal loop that links the IGF2 promoters. CTCF recruits polycomb repressive complex 2 (PCR2) via the docking factor SUZ12, leading to allelic histone 3 lysine 27 (H3K27) methylation that silences the maternal IGF2 allele. On the other hand, paternal-specific methylation of the ICR prevents CTCF binding and permits expression of IGF2 while silencing H19 from the paternal allele. As a result, differential methylation at the CTCF site serves as an “imprint” to ensure the reciprocal imprinting of these two neighboring genes [19]. Importantly, imprinting is dynamically regulated in gametes and in early development. Imprinting defects, including those at the H19/IGF2 locus, are associated with increased risk of developmental disorders [20,21]. Aberrant DNA methylation of the CTCF binding sites in the ICR is associated with an increased risk for abortion [22] and for male infertility [23]. Furthermore, imprinting is frequently dysregulated in IVF embryos [24,25]. Given the critical role of H19 in in vitro fertilization (IVF) [24] and male infertility [26], we examined the imprinting status of the H19/IGF2 cluster in decidual tissues. We show that there is loss of imprinting of both H19 and IGF2 in some decidual tissues. Using human primary endometrial stromal cells as an in vitro model, we studied the epigenetic mechanisms underlying abnormal H19/IGF2 imprinting in decidualization.
To search for key factors that might be involved in fetal–maternal regulatory crosstalk in RSA, we explored the differentially expressed lncRNAs in GSE178535, which contained the RNA-seq data of decidual tissues from three RSA patients and three healthy control subjects. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed associations with cytokine–cytokine receptor interaction, ECM–receptor interaction, hematopoietic cell lineage, chemokine signaling pathway, PI3K-Akt signaling pathway, as well as signaling pathways in the regulation of stem cell pluripotency (Figure S1, Table S2). We focused on the role of the imprinted lncRNA H19 (Figure 1A, Table S3). In normal tissues, H19 is expressed only from the maternal allele, while the paternal allele is silenced. Aberrant imprinting of the H19 gene occurs frequently in tumors [19]. Using an in vitro fertilization model, we previously showed that H19 imprinting was frequently lost in IVF embryos [24]. We were therefore interested in examining if aberrant regulation of lncRNA H19 in decidual tissues played a role in the fetal–maternal regulatory crosstalk in RSA. We quantitated the expression of H19 in decidual tissues from 32 patients with RSA. For comparison, decidual tissues were also collected from 57 healthy adult women at 7–10 weeks of gestation who were undergoing early pregnancy termination (Table S4). Using EF1A (EEF1A1) as the RT-qPCR control, we found that the expression of H19 was significantly higher in decidual tissues from the patients with RSA than in decidua from healthy subjects (Figure 1B, p < 0.01). The H19 gene is located in an imprinting cluster on human chromosome 11 and is coregulated with the adjacent gene IGF2, a gene that encodes a mitogen that is required for normal fetal growth. The hierarchical cluster heat map analysis showed that IGF2 was among the top six of the differentially expressed genes in the analysis (Figure S1B), despite the variability among the subjects (Figure S1C). Therefore, we also quantitated the mRNA abundance of IGF2 in decidual tissues using quantitative PCR and found that, like H19, IGF2 was significantly upregulated in decidual tissues derived from patients who had RSA (Figure 1C, p < 0.01). Similar data were also obtained by using β-Actin (ACTB) as the RT-qPCR control (Figure S1D,E).
To examine the status of H19 and IGF2 imprinting in decidual tissues, we genotyped genomic DNA using single nucleotide polymorphisms (SNPs) in H19 and IGF2. Heterozygous SNPs were used to distinguish between the two parental alleles, and the imprinting status was examined in those tissues that were SNP-informative. Twenty-one of the decidual tissues derived from patients who had RSA were informative for H19 heterozygosity and 20 were informative for IGF2 heterozygosity. We found that H19/IGF2 imprinting was lost in 39% (11/28) of H19/IGF2 informative decidual tissues from the RSA cases (Figure 2A, left panel). Among them, 2 out of 21 samples (9.5%) showed loss of H19 imprinting, and 7 out of 20 samples (35%) exhibited IGF2 LOI. Two samples (#22 and #U20) showed loss of imprinting of both H19 and IGF2 (Table 1). Imprinting was also lost in some decidual tissues collected from the controls (Figure 2A, right panel). As an example, the decidual tissue from Control #13 showed normal imprinting of H19 (maintenance of imprinting) (Figure 2B, left top panel). The genomic DNA carried both the “A” and “C” alleles, but the cDNA showed the exclusive expression of the “A” allele. The “C” allele was silenced. The decidual tissues from two cases (#U18 and #M22) were also informative for the SNP (Figure 2B, left panels 2–3). However, both the “A” and “C” alleles were detected in their cDNA samples, demonstrating loss of imprinting (LOI). Similarly, the genotyping of an SNP at the 3′-UTR of IGF2 showed the presence of the “C/T” alleles. In normal informative decidual tissue #4, only the “T” allele was expressed (Figure 2C, top right panel). However, in two cases of RSA (U11, M22), both the “C” and “T” alleles were expressed in decidual tissues (LOI) (Figure 2C, right panels 2–3). In case U29T, however, both H19 and IGF2 maintained normal imprinting. Loss of IGF2/H19 imprinting is an early oncogenic event that is detected in tumor-paired adjacent normal tissues [19]. Therefore, we examined the allelic expression of IGF2/H19 in decidual samples of control subjects. We also detected the presence of IGF2/H19 LOI in the decidua of several control subjects (Table S5), suggesting epigenetic vulnerability in the decidual microenvironment of early embryo development. The chi-squared analyses showed more LOI cases in the RSA case group for IGF2 (p < 0.05, χ2= 6.93), but not for H19 (p = 0.721, χ2= 0.407) (Figure S2). The quantitative expression data of IGF2 and H19 in LOI and maintenance of imprinting subgroups are presented in Figure S3. Polymorphic imprinting has been observed in placenta [27,28]. Thus, imprinting erosion as observed in both RSA and normal decidual tissues here may represent a decidua-specific polymorphic imprinting trait.
In vitro cell-induced decidualization is a good model for studying the complex process of implantation [29,30]. We thus cultured two human primary endometrial stromal cell lines (U29T and N45T) (Figure S4A). N45T cells were cultured from the decidual tissues collected from a normal control subject. U29T cells were derived from an RSA case who had suffered four spontaneous abortions (Figure S4B). Genotyping of genomic DNA showed that U29T cells were informative for both H19 and IGF2. N45T cells, however, were only informative for H19. No informative SNPs were available for IGF2 in N45T cells to distinguish the two parental alleles. We examined the role of altered epigenotypes in this in vitro decidualization model. We pretreated U29T and N45T cells with the histone deacetylase inhibitor valproic acid (VPA) (Figure 3A), which is known to modify epigenotypes and alter allelic expression [31]. Following VPA treatment, cells were induced for decidualization. We found that this VPA treatment upregulated IGF2 and H19, particularly in cells with induced decidualization (Figure 3B). However, two decidualization markers (PRL and IGFBP1) were significantly lower in VPA-treated decidualized cells (Figure 3C), suggesting an impaired decidualization process in VPA-induced cells.
We then used informative SNPs to examine the allelic expression in decidualized cells (Figure S5A). Both U29T and N45T cells were informative for H19 through gDNA genotyping and both maintained normal H19-IGF2 imprinting after being placed in culture. Maintenance of H19 imprinting was also observed after induced decidualization, with only the “C” allele expressed in U29T cells and the “A” allele expressed in N45T cells (Figure S5B, CTL-Induced cDNA). However, VPA pretreatment induced biallelic expression of H19 in both decidualized cell lines (Figure S5B, VPA-Induced cDNA). These data suggest that pretreatment with a histone deacetylase inhibitor predisposed endometrial stromal cells to lose imprinting control during decidualization. By using informative SNP rs680, we also examined the imprinting status of IGF2 in U29T cells (Figure S5C). The untreated cells maintained normal imprinting, with only the “T” allele expressed (Figure S5D, CTL cDNA). However, IGF2 imprinting was lost, with both parental alleles (C/T) expressed in the decidualized cells (both CTL-induced and VPA-induced cDNA). IGF2 and H19 expression are normally tightly coordinated and reciprocally controlled by an “enhancer competition” mechanism [32]. The data from these treated primary endometrial stromal cells, however, suggest that the control of IGF2 and H19 imprinting can be uncoupled.
We then examined the epigenetic mechanisms underlying the loss of imprinting in these two decidualized cell lines. The expression of IGF2 is driven by four promoters, including an upstream nonimprinted P1 promoter and three downstream imprinted promoters (P2–P4). While they are rich in CpG islands, promoters P2–P4 are not regulated by DNA methylation. Instead, gene silencing of the maternal IGF2 allele is mediated by polycomb repressive complex 2 (PCR2) component SUZ12-catalyzed H3K27 methylation [19]. We thus focused on the status of H3K27 methylation in the three imprinted IGF2 promoters (Figure 4A) [32]. Using antibodies specific for H3K27me3, we examined H3K27 methylation in IGF2 promoters in U29T cells that exhibited IGF2 LOI. We found that H3K27 methylation in the first two IGF2-imprinted promoters (P2, P3) was significantly reduced in decidualized cells (Figure 4B). As a control, the 5′-Ctl site upstream of the nonimprinted P1 promoter showed no significant change in the H3K27me3 mark during decidualization. In N45T cells that kept normal imprinting after in vitro decidualization, however, the ChIP signal for H3K27me3 was increased following in vitro decidualization (Figure 4C). It is known that the key decidual marker gene IGFBP1 in decidualization is controlled by H3K27 methylation [33]. It was therefore used as the positive control in the ChIP assay. We confirmed the reduction of H3K27 methylation in the IGFBP1 promoter in both N45T and U29T cells following decidualization (Figure S6A,B). As expected, decidualization did not alter the status of H3K27 methylation in the negative control gene GPD1 (Figure S6C,D).
The status of histone 3 lysine 27 (H3K27) in the IGF2 promoters is determined by CTCF-orchestrated intrachromosomal looping [34,35]. CTCF binds to unmethylated DNA motifs in ICR located between the H19 and IGF2 genes and orchestrates the formation of an intrachromosomal loop, where polycomb repressive complex 2 (PCR2) is recruited via the docking factor SUZ12, leading to allelic H3K27 methylation which then silences the imprinted allele [36]. We used chromosome conformation capture (3C) methodology to examine the chromatin three-dimensional (3D) structure surrounding the IGF2/H19 locus, with the focus on the CTCF-binding site in the ICR [37]. Using the β-Globin gene (HBB) as a positive control, we detected intrachromosomal looping between the LCR (locus control region) and the 3′-enhancer in two decidualized cell lines (Figure S7). In the same 3C samples, we detected an intrachromosomal loop structure between the ICR-enhancers and ICR-IGF2 promoters in untreated U29T primary decidual cells (Figure 5A). The 3C products were purified, and DNA sequencing confirmed the loop joint separated by the Bgl2/BamH1, Bgl2/Bgl2, and BamH1/BamH1 ligation sites (Figure 5B). However, after induced decidualization in vitro, all three intrachromosomal loops were abolished (Figure 5C) in parallel with the loss of IGF2 imprinting. The intrachromosomal looping, however, was not significantly affected in decidualized N45T cells that maintained normal imprinting (Figure 5D). Thus, as was previously reported in cancer cells with LOI [34], CTCF-orchestrated intrachromosomal looping may be essential for maintaining normal imprinting of IGF2 in decidual tissues.
Allelic expression of IGF2 is regulated by the methylation status of CpG islands in the ICR. We examined allele-specific DNA methylation in the ICR for decidual tissues that were informative for two SNPs in the ICR and one SNP in the H19 promoter (Figure 6A). The status of CpG DNA methylation was examined using sodium bisulfite sequencing. After converting the unmethylated cytosines into uracils by sodium bisulfite, the ICR and H19 promoter regions were amplified with DNA methylation-specific primers and cloned into a pJet vector for DNA sequencing. As expected, a typical semimethylated pattern was observed in control #Z4 that had normal monoallelic expression of H19 and IGF2 (Figure S8). Case #M22, derived from a patient with RSA, was homozygous for the two SNPs, and therefore, we were not be able to distinguish the two parental alleles. However, we detected hyper-methylation in the ICR and the H19 promoter (Figure 6B, top panel). Case U11, which was heterozygous for the ICR SNP, had a hyper-methylated “AA” allele and increased DNA methylation in the “AG” allele (36.5%) (left top panel). We also observed increased CpG DNA methylation at the ICR CTCF6 site (AA allele, 19.2%) in decidualized U29T cells that exhibited IGF2 LOI, as compared with the control cells (AA allele, 4.6%) (Figure S9). These data suggest that aberrant imprinting of H19/IGF2 may be associated with CpG DNA epimutations in the ICR region.
The molecular mechanisms underlying the spontaneous loss of a pregnancy are unknown [38]. Decidualization plays a critical role in the implantation of the embryo through a regulatory network that coordinates trophoblast invasion of the maternal decidua-myometrium and remodeling of maternal uterine spiral arteries [39,40]. Many factors, including locally secreted cytokines and growth factors, are involved in this complicated network. We have identified the lncRNA H19 as one of the most upregulated RNA molecules in decidual tissue, where the molecular crosstalk at the fetal–maternal interface occurs. H19 is also significantly upregulated in the decidua derived from patients with RSA. IGF2, a gene that encodes an important fetal mitogen, is located at the adjacent chromosomal locus. IGF2 is also increased in the decidua in patients who have suffered an RSA. In most normal tissues, the H19/IGF2 locus is imprinted. Notably, we demonstrate that there is loss of H19 and IGF2 imprinting in decidual tissues of some RSA patients. Loss of imprinting also occurs following induced decidualization in primary endometrial stromal cells. Mechanistically, we show that this aberrant imprinting in decidual tissues was associated with the loss of the H3K27m3 repressive histone mark as well as with the loss of intrachromosomal looping and CpG demethylation in the imprinting control center. Pretreatment with histone deacetylase inhibitor VPA predisposed primary endometrial stromal cells to develop abnormal in vitro decidualization. Collectively, these studies suggest that the disturbance of H19/IGF2 epigenetic regulation, in addition to the locally secreted cytokines and growth factors, may be an epigenetic risk factor for poor decidualization (Figure 6C). Both the maternal and paternal genomes are necessary for normal embryogenesis and fetal development [41,42]. H19 is a maternally expressed imprinted gene, and its transcription gives rise to a fetal lncRNA that also functions as a precursor to microRNA miR675 [43], which negatively affects cell proliferation and tumor metastasis [44]. H19 is abundantly expressed prior to implantation or shortly thereafter, and its expression is specifically confined to progenitor cells of the placenta and extraembryonic tissues [45,46]. H19 is expressed coordinately with its neighboring gene Igf2, a gene that plays a key role in regulating fetal–placental development [47,48]. Genomic deletion of Igf2 causes placental and fetal growth restriction. In contrast, overexpression of Igf2 induces placental and fetal overgrowth via paracrine and/or autocrine IGF pathways. The serum levels of IGF-II have been positively linked to infant birth weight. H19 and Igf2 regulate embryonic development [49,50]. The allelic expression of IGF2/H19 is coordinately controlled by a differentially methylated imprinting control region upstream of the H19 promoter [19,51]. In this study, we demonstrate that both H19 and IGF2 are upregulated in decidual tissues of RSA patients as compared with the control cohorts. Moreover, there is loss of imprinting of both genes in many decidual tissues. Major epigenetic events take place in the embryo both in preimplantation development and in postimplantation stages, including the genome-wide resetting of imprints in the PGCs [52,53]. Aberrant methylation of imprinted genes correlates with the risk of abortion [22]. Specifically, CpG hypomethylation in the ICR is correlated with recurrent pregnancy loss [54]. As a result, the periconceptional stage is very sensitive to environmental stressors, leading to epigenetic disturbances. Loss-of-imprinting has been linked to a number of diseases characterized by abnormal growth phenotypes and behavioral disorders, including Beckwith–Wiedemann syndrome, Silver–Russell syndrome, Angelman syndrome, and Prader–Willi syndrome [55,56], as well as multiple malignancies [57]. Placental-specific imprinting plays a critical role in coordinating the crosstalk between nutrient acquisition and fetal development. Human placentas exhibit widespread placental-specific imprints inherited from the oocyte, including maternally biased DNA methylation DMRs and histone modifications [45,50]. In particular, H19 shows a unique placenta epigenotype, with the paternal allele-specific DNA methylation covering the core ICR to the gene body [58]. In this study, we also observed more loss of imprinting of H19/IGF2 in RSA decidual tissues. Pretreatment of two human primary endometrial stromal cells with a histone deacetylase inhibitor induced loss of imprinting and reduced in vitro decidualization. Loss of imprinting in the placenta is associated with intrauterine growth restriction [27,59]. Future studies are needed to elucidate whether dysregulated imprinting plays a role in regulating fetal growth as well as other pregnancy-related pathologies. It is noteworthy that the mouse and human genome contain a subset of genes that undergo polymorphic imprinting, including IGF2, IGF2R, WT1, SLC22A2, and HTR2A, with the imprinting status varying among individuals and tissues. For example, human WT1 is biallelically expressed in kidney, but is monoallelically expressed in brain. In the placenta, WT1 is maternally expressed in ~60% of the population. The human nc886 gene, encoding a tumor-suppressing ncRNA at chromosome 5q31 is another typical example of nonplacental polymorphic imprinting, with allele-specific methylation predominantly found on the maternal allele in many tissues [60]. Moreover, profiling of placental-specific imprinted DMRs shows that human placenta preferentially maintains maternal germline-derived imprint marks and appears to be highly polymorphic in the population [28]. Thus, the biallelic expression of H19 and IGF2 as observed in the present study may be associated with a decidua-specific polymorphic imprinting trait. It should be noted that this study also has several weaknesses. First, two primary endometrial stromal cells yielded some discrepancies in in vitro decidualization. U29T cells, derived from the decidua of an RSA patient, were more vulnerable to hormone induction and exhibited loss of IGF2 imprinting following in vitro decidualization. N45T cells derived from a normal subject, on the other hand, maintained normal imprinting unless they were also pretreated with histone deacetylase inhibitor. Although this discrepancy may be related to the polymorphic imprinting trait in primary endometrial stromal cells, we still do not know the specific mechanisms by which these differences arise. Second, several other lncRNAs are also upregulated in the decidual samples of RSA cases. For instance, MALAT1 was the most upregulated lncRNA on the list. NEAT1 was also upregulated in RSA decidual tissues. Neat1 knockout mice stochastically show decreased fertility due to corpus luteum dysfunction and concomitant low progesterone [61], suggesting a critical role of Neat1 in the establishment of pregnancy. Thus, future studies are needed to address if these lncRNAs are also involved in the dysregulated decidualization related to RSA. In summary, this study reveals the first evidence that the imprinting status of H19/IGF2 is dysregulated in decidual tissues. Using primary endometrial stromal cells as a model, we demonstrate that the in vitro decidualization process is affected by altered epigenotypes induced by a histone deacetylase inhibitor. The loss of imprinting in decidual tissues was associated with a dysregulated H3K27m3 histone marker and altered CTCF-mediated intrachromosomal looping. Altered levels of H19 lncRNA and/or IGF-II protein in fetal decidua may alter normal fetal–placental development. It would be interesting to explore whether epigenetic targeting of the H19/IGF2 epimutation [19] may provide an alternative strategy to prevent the poor decidualization seen in some pregnancy-related disorders.
To identify RSA-associated lncRNAs, we downloaded the RSA dataset GSE178535 from the NIH GEO database website. The dataset contained the RNA-seq data of decidual tissues from three RSA patients and three healthy control subjects [62] (Next Generation Sequencing Facilitates Quantitative Analysis of healthy controls and RSA patients Transcriptomes. Available online: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178535, accessed on 22 June 2021). The in vitro decidualization of embryonic stem cells (ESCs) was induced using differentiation media containing 0.5 mM dibutyryl cAMP, 1 µM medroxyprogesterone 17-acetate, and 10 nM β-estradiol. Decidualized cells were used for RNA-seq [63]. Differentially expressed RNAs were calculated as the log2-transformed gene expression values (Fold Change). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis (KEGG_PATHWAY) was carried out using DAVID Bioinformatics Resources 6.8 (https://david.ncifcrf.gov, accessed on 21 September 2022) [64,65]. Hierarchical Cluster Heatmap was generated using HIPLOT (https://hiplot.com.cn, accessed on 21 September 2022) [66]. LncRNAs with the fold-change >2 and p < 0.001 were chosen for further functional characterization.
Decidual tissue samples were collected at The First Hospital of Jilin University between 2017–2022. Ethical approval for this study was provided by the Research Ethics Board of the First Hospital of Jilin University, and written informed consent was obtained from all patients prior to sample collection. A total of 32 decidual tissues were collected from women with unexplained RSA. The inclusion criteria for this group were women aged under 40 years with a history of > three consecutive pregnancy losses. Clinical examination showed that they had normal uterine cavity shape and size; normal follicle-stimulating hormone (FSH), estradiol (E2), prolactin (PRL), luteinizing hormone (LH), and thyroid-stimulating hormone (TSH) levels at menstrual day 2–3; no mutations detected in Factor V (Leiden) and prothrombin gene analysis; normal antithrombin III, protein C, and S activity; negative results for lupus anticoagulant evaluation; cardiolipin antibody; beta2-glycoprotein antibody; and normal karyotype. Their partners have normal semen analyses and normal karyotype. None of the patients had received a prior infertility treatment. In addition, 57 decidual samples were obtained as the control group from healthy adult women at 7–10 weeks of gestation undergoing legal elective termination. The inclusion criteria were women aged under 40 years with regular menstrual cycles, at least one live birth, no previous miscarriages, no history of infertility/treatment, and no associated gynecologic (endometriosis, fibroids, active or history of pelvic inflammatory disease) or other medical comorbidities (e.g., hyperprolactinemia, thyroid disease). The male partners of control subjects had normal semen analysis results and karyotypes. The characteristics of RSA patients and controls are listed in Table S5. All the decidual samples were collected by the same pathology lab technician at Jilin University First Hospital. The placenta was rinsed with saline to remove blood. Decidual tissues were collected by carefully dissecting the maternal basal plate of the placenta. Collected tissues were rinsed with 1× PBS, frozen with liquid nitrogen, and saved in –80 °C freezer for analysis.
Primary endometrial stromal cells were cultured from U29T and N45T decidual tissues that were H19-IGF2 informative and that maintained normal imprinting. N45T cells were cultured from the decidual tissues collected from a normal control subject. U29T cells were derived from an RSA case who had suffered four spontaneous abortions (Figure S4). After curettage, the tissues were immediately collected under sterile conditions into prechilled PBS and divided into decidua and villi. Two or three pieces of decidual tissues were collected and washed 2–3 times again with prechilled PBS to exclude villous contamination. Fresh tissues were cut into approximately 2 mm3 fragments, washed in DMEM (high glucose; Sigma, MO, USA), and directly cultured at 37 °C in 5% CO2 by attaching to the substratum in a 10 cm dish with complete medium consisting of DMEM medium (Sigma, St. Louis, MO, USA) supplemented with 10% (v/v) fetal bovine serum (Sigma, St. Louis, MO, USA), 100 U/mL of penicillin sodium, and 100 µg/mL of streptomycin sulfate (Invitrogen, Carlsbad, CA, USA). After approximately 12 days in culture, cells migrated out from the edges. Migrating cells were collected with 0.1% trypsin and 0.25 mM EDTA and passaged for allelic study and in vitro decidualization assays (Figure S4). After culturing, cells were aliquoted and stored in liquid nitrogen for further studies.
In vitro artificially induced decidualization was performed following the method as described in [29]. Briefly, U29T and N45T primary endometrial stromal cells were cultured in complete medium containing 10 nM E2, 1 µM P4, and 0.5 mM 8-Br-cAMP. Culture medium was changed every 2 days. Cells were harvested for subsequent experiments 96 h after the treatment.
To examine the role of aberrant epigenotypes in in vitro decidualization, we pretreated primary endometrial stromal cells with the histone deacetylase inhibitor valproic acid (VPA), which is known to modify epigenotypes and alter allelic expression [31]. U29T and N45T cells were treated with 2 mM VPA. Cells treated with equal volume of PBS were used as the control (Ct). Culture medium was changed daily. Forty-eight hours after VPA treatment, cells were used for in vitro decidualization experiments. After 96-h treatment, cells were collected for imprinting assays.
Decidual tissues and cells were collected and total RNA was extracted by TRIzol reagent (Sigma, St. Louis, MO, USA) and stored at −80 °C. cDNA was synthesized using RNA reverse transcriptase (Invitrogen, CA, USA), and target amplification was performed with a Bio-Rad Thermol Cycler. PCR of 1 cycle at 95 °C for 2 min; 32 cycles at 95 °C for 15 s, 60 °C for 15 s, and 72 °C for 15 s; and 1 cycle at 72 °C for 10 min. EF1A (EEF1A1) and β-Actin (ACTB) were used as the internal controls. Quantitative real-time PCR was performed using SYBR GREEN PCR Master (Applied Biosystems, Foster City, CA, USA); the threshold cycle (Ct) values of target genes were assessed by quantitative PCR in triplicate using a sequence detector (ABI Prism 7900HT; Applied Biosystems, Foster City, CA, USA) and were normalized over the Ct of the EF1A or β-Actin controls. Primers used for PCR quantitation are listed in Table S1.
Genomic DNA and total RNA extraction from decidual tissues and cDNA synthesis were performed as previously described. Decidual tissues were first genotyped for heterozygosity of SNPs in IGF2 exon 9 and H19 exon 5 (Figure 2A). Target amplification was performed with a Bio-Rad Thermol Cycler. PCR of 1 cycle at 95 °C for 2 min; 32 cycles at 95 °C for 15 s, 60 °C for 15 s, and 72 °C for 15 s; and 1 cycle at 72 °C for 10 min using primers specific for two polymorphic restriction enzymes (ApaI, AluI) in the last exon of human IGF2 and H19 exon 5. To determine the status of IGF2 imprinting, the amplified products were sequenced by Comate Bioscience Co, Ltd. (Changchun, China). Decidual tissues that maintain normal imprinting expressed a single parental allele, while the LOI showed biallelic expression of IGF2 and H19. PCR primers used for IGF2 imprinting are listed in Supplementary Table S1.
Genomic DNA was collected from tissues or cells using dBIOZOL Genomic DNA Extraction Reagent (BioFlux, BSC16M1, Hangzhou, China) following the manufacturer’s instructions. DNA was treated with EZ DNA Methylation-GoldTM Kit (ZYMO RESEARCH, D5005, Irvine, CA, USA), and PCR was performed using DNA methylation-specific primers designed for the promoter of H19 and CTCF binding sites (Table S1). To examine the status of DNA methylation in every CpG site, the amplified PCR DNAs were cloned into pJET1.2/blunt cloning vector (Thermo, K1231, Waltham, MA, USA) and transformed into TOP10. Plasmid DNA was collected by Wizard® Plasmid DNA Purification kit (Promega, A1223, MO, USA) and sequenced.
Furthermore, 3C assays were performed to determine long-range intrachromosomal interactions as previously described [35,67,68,69]. Briefly, 1.0 × 107 cells were cross-linked with 2% formaldehyde and lysed with cell lysis buffer (10 mM Tris (pH 8.0), 10 mM NaCl, 0.2% NP-40, supplemented with protease inhibitors). Nuclei were collected and suspended in 1× restriction enzyme buffer. An aliquot of nuclei (2 × 106) was digested with 800 U of restriction enzyme BamH1/Bgl2 at 37 °C overnight. After stopping the reaction by adding 1.6% SDS and incubating the mixture at 65 °C for 20 min, chromatin DNA was diluted with NEB ligation reaction buffer, and 2 μg DNA was ligated with 4000 U of T4 DNA ligase (New England BioLabs, Irvine, CA, USA) at 16 °C for 4 h (final DNA concentration, 2.5 μg/mL). After treatment with 10mg/mL proteinase K at 65 °C for 4h to reverse cross-links and with 0.4 μg/mL RNase A for 30 min at 37 °C, DNA was extracted with phenol-chloroform, ethanol precipitated, and detected by PCR amplification of the ligated DNA products. Furthermore, 3C PCR products were cloned and sequenced to validate the intrachromosomal interactions by assessing for the presence of the BamH I/Bgl II ligation site. The 3C interaction was quantitated by qPCR and was standardized over the 3C ligation control. For comparison, the relative 3C interaction was calculated by setting the control as 1. As the 3C quality control, human β-Globin (HBB) gene was used as a positive control. Unlike IGF2 promoters P2-P4, IGF2 promoter 1 (P1) is not imprinted and is biallelically expressed in all tissues. Thus, we chose a Bgl2 site upstream of P1 promoter as the 3C negative control. Human Primers used for 3C assay are listed in Supplementary Table S1.
As previously described, a ChIP assay was used to quantitate the status of histone modifications following the manufacturer’s protocol (Upstate Biotechnology, Lake Placid, NY, USA). Briefly, 1.0 × 107 cells were fixed with 1% formaldehyde and then sonicated for 180 s (10 s on and 10 s off) on ice with a sonicator with a 2mm microtip at 40% output control and 90% duty cycle settings. The sonicated chromatin was collected by centrifugation, aliquoted, and stored at −80 °C. Protein A/G Magnetic Beads and a specific anti-trimethyl-histone H3 (Lys27) antibody (Merck Millipore, Darmstadt, Germany) were incubated with rotation for 30 min at room temperature. The sonication supernatant and beads were incubated with antibody at 4 °C on a rotating rack for 4–16 h or overnight. To reduce the ChIP background, we modified the manufacturer’s protocol by adding two more washing steps following immunoprecipitation. As previously reported [35], anti-IgG was used as the ChIP control in parallel with testing samples. Precipitated DNA was subjected to qPCR and expressed as fold-enrichment compared to the IgG chromatin input. For the ChIP assay, IGFBP1, a key decidual marker gene controlled by H3K27 methylation in decidualization, was used as the positive control. The housekeeping gene GPD1 (G3PDH) was used as the negative control in the assay.
All the experimental data are presented as mean ± standard deviation (SD) and were derived from at least three biological replicates. Statistical analyses were performed using GraphPad Prism v7.0 (GraphPad Software, San Diego, CA, USA). Unpaired two-tailed Student’s t-tests were used for comparison between two groups. One-way ANOVA with Bonferroni’s multiple comparison test was used to compare statistical differences for variables among three or more groups. Chi-squared tests were used to examine the association between the H19/IGF2 imprinting status (loss of imprinting and maintenance groups) and the risk of RSA occurrence (RSA and control groups). The level of significance was indicated as * p < 0.05, ** p < 0.01, and *** p < 0.001, unless stated otherwise. | true | true | true |
Subsets and Splits